U.S. patent application number 11/698230 was filed with the patent office on 2008-07-24 for modeling of mpges-1 three-dimensional structures: applications in drug design and discovery.
This patent application is currently assigned to The University of Kentucky. Invention is credited to Adel Hamza, Xiaoqin Huang, Chang-Guo Zhan.
Application Number | 20080177521 11/698230 |
Document ID | / |
Family ID | 39642111 |
Filed Date | 2008-07-24 |
United States Patent
Application |
20080177521 |
Kind Code |
A1 |
Zhan; Chang-Guo ; et
al. |
July 24, 2008 |
Modeling of mPGES-1 three-dimensional structures: applications in
drug design and discovery
Abstract
This invention relates to representations of prostaglandin
synthase three-dimensional structures. Such representations are
suitable for designing agents that modulate the activity of the
enzyme by binding to the substrate binding domain.
Inventors: |
Zhan; Chang-Guo; (Lexington,
KY) ; Huang; Xiaoqin; (Lexington, KY) ; Hamza;
Adel; (Lexington, KY) |
Correspondence
Address: |
CROWELL & MORING LLP;INTELLECTUAL PROPERTY GROUP
P.O. BOX 14300
WASHINGTON
DC
20044-4300
US
|
Assignee: |
The University of Kentucky
Lexington
KY
|
Family ID: |
39642111 |
Appl. No.: |
11/698230 |
Filed: |
January 24, 2007 |
Current U.S.
Class: |
703/11 ;
530/333 |
Current CPC
Class: |
G16B 15/00 20190201;
C12N 9/90 20130101; C12Y 503/99003 20130101; G16B 30/00 20190201;
C07K 1/00 20130101 |
Class at
Publication: |
703/11 ;
530/333 |
International
Class: |
G06G 7/48 20060101
G06G007/48; C07K 1/00 20060101 C07K001/00 |
Claims
1. A method of identifying a set of candidate structures of a
polypeptide, the method comprising: a) obtaining a first amino acid
sequence derived from a query polypeptide; b) obtaining a second
amino acid sequence derived from a template polypeptide, wherein
the second sequence comprises: i) a predetermined three-dimensional
structure; and ii) at least 50% sequence homology with the first
sequence; c) performing a sequence alignment between the first
sequence and the second sequence, and identifying common secondary
structures; d) generating a plurality of candidate topological
structures by applying predetermined geometric parameters to the
secondary structures of c) and transforming each topological
structure in to the amino acid residues associated with the
secondary structures; e) generating a first conformation set by
screening the plurality of candidate topological structures of d)
with the predetermined geometric parameters and identifying the
structures that correspond to the parameters; f) generating a
second conformation set by applying energy minimization functions
to the first conformation set and identifying energetically-favored
conformations; and g) generating a final conformation set by
selecting those structures that exhibit an energy gradient having a
root mean square deviation (RMSD) of less than 0.001 kcal
mol.sup.-1 .ANG..sup.-1, wherein the final conformation set
represents the set of candidate structures of the query
polypeptide.
2. The method of claim 1 wherein the sequence alignment is
generated by ClusterW with the Blosum scoring function.
3. The method of claim 1 further including generating the sequence
alignment by generating the reciprocal position of the conserved
residues.
4. The method of claim 1, wherein the query polypeptide comprises
membrane-spanning regions of amino acids.
5. The method of claim 4, wherein the query polypeptide is a member
of the membrane-associated proteins involved in eicosanoid and
glutathione metabolism (MAPEG).
6. The method claim 5, wherein the query polypeptide is microsomal
prostaglandin E synthase-1 (mPGES-1)
7. The method of claim 1, wherein the template polypeptide is a
member of the membrane-associated proteins involved in eicosanoid
and glutathione metabolism (MAPEG).
8. The method claim 7, wherein the template polypeptide is
microsomal glutathione-S-transferase-1 (MGST-1).
9. The method of claim 1, wherein the polypeptide comprises a
substrate binding domain.
10. The method of claim 1, wherein the secondary structures
comprise alpha-helices.
11. The method of claim 1, wherein the structural parameters
comprise coordinates derived from 3D electron projection maps of
MGST1.
12. The method of claim 11, wherein the structural parameters
further comprise the coordinates derived from 2D electron
projection maps of mPGES-1.
13. The method of claim 1, wherein the structural parameters
correspond to the coordinates set forth in Table 1.
14. The method of claim 1, wherein the energy minimization function
comprises the Sander module of Amber7.0 program suite.
15. The method of claim 1 further comprising: g) modeling the
interaction of each member of the final conformation set with at
least one substrate, wherein the modeling comprises molecular
docking using binding site searching and/or interaction energy
scoring; and h) identifying amino acid residues associated with the
SBD that interact with the substrate.
16. The method of claim 15, wherein the substrate is PGH2 or
GSH.
17. The method of claim 15, wherein the amino acid residues that
interact with the substrate comprise amino acid residues Q36, R110,
T114, Y130, and Q134 of mPGES-1.
18. The method of claim 15 further comprising: i) modifying at
least one amino acid residue that interacts with the substrate; and
j) determining the effect of the modification on substrate binding
to the modified polypeptide.
19. The method of claim 18, wherein the modification is a
substitution.
20. The method of claim 19, wherein the substitution is a
conservative amino acid substitution.
21. The method of claim 19, wherein the substitution is a
non-conservative amino acid substitution.
22. The method of claim 18 further comprising: k) producing the
modified polypeptide in vivo or in vitro; and l) assaying the
activity of the modified polypeptide in vivo or in vitro.
23. A representation of a three-dimensional structure of the
mPGES-1 substrate binding domain (SBD) characterized in that: a)
amino acid residues Q36, R110, T114, Y130, and Q134 of mPGES-1 are
associated with the PGH2-binding site of the SBD; b) amino acid
residue Y130 of mPGES-1 is associated with the peroxy head of
prostaglandin H2 (PGH2) when PGH2 occupies at least a portion of
the binding site; c) amino acid residue Y130 of mPGES-1 is
associated with the --SH group of glutathione (GSH) when GSH
occupies at least a portion of the binding site; d) amino acid
residues R110, T114, and Q36 of mPGES-1 are associated with the
carboxyl tail of PGH2; e) the calculated binding free energy
(.DELTA.G) for an SBD-PGH2 complex is between -5.0 kcal/mol and
-9.0 kcal/mol; and f) the calculated binding free energy (AG) for
an SBD-GSH complex is between -4.0 kcal/mol and -8.0 kcal/mol.
24. The representation of claim 23, wherein PGH2 interacts with GSH
through hydrogen binding between the peroxy group of PGH2 and the
--SH group of GSH.
25. A representation of a three-dimensional structure of an mPGES-1
trimer characterized in that: a) each monomer of the trimer
comprises a representation of a three-dimensional structure of the
mPGES-1 substrate binding domain (SBD) as set forth in claim 23; b)
the trimer comprises a C.sub.3-fold symmetry; and c) the
representation of the trimer comprises a homology model based on
the crystallographic structure of subunit 1 of cytochrome c
oxidase.
26. A method of structure-based identification of candidate
compounds for regulation of interactions of mPGES-1 with its
cognate ligands, comprising: a) providing a three dimensional
structure of mPGES-1, the three dimensional structure being
selected from the group consisting of: i) the mPGES-1 substrate
binding domain as set forth in claim 23; and ii) the mPGES-1 trimer
as set forth in claim 25; b) identifying at least one candidate
compound for interacting with the three dimensional structure of a)
and performing structure based drug design.
27. A machine-readable medium embedded with information that
corresponds to the three-dimensional structural representation of
the mPGES-1 substrate binding domain (SBD) as claimed in claim
23.
28. A machine-readable medium embedded with information that
corresponds to the three-dimensional structural representation of
the mPGES-1 trimer as claimed in claim 25.
29. A computer system comprising: a) a representation of the
three-dimensional structure of the mPGES-1 substrate binding domain
(SBD) as claimed in claim 23; and b) a user interface to view the
representation.
30. A computer system comprising: a) a representation of the
three-dimensional structure of the mPGES-1 trimer as claimed in
claim 25; and b) a user interface to view the representation.
31. A method for conducting a biotechnology business comprising: a)
identifying one or more candidate compounds for regulation of
interactions of mPGES-1 with its cognate ligands by the method of
claim 26; b) generating a machine-readable medium, or data signal
embodied in a carrier wave, embedded with information that
corresponds to the three-dimensional structural representation of
the candidate compound; and c) providing the medium or data signal
to an end user.
Description
TECHNICAL FIELD
[0001] Computational methods for determining the three-dimensional
structure of one or more polypeptides are provided. Also provided
are three-dimensional models of a microsomal prostaglandin synthase
molecule and computer-implemented methods for identifying compounds
that interact with the molecule.
BACKGROUND
[0002] Prostaglandin (PG) E2 is produced by a variety of cells and
tissues and exhibits potent diverse bioactivities. Its production
is mediated by three enzymatic reactions involving phospholipase A2
(PLA2), cyclooxygenase (COX), and PGE2 synthase (PGES). In this
biosynthetic pathway, arachidonic acid (AA) releases from membrane
phospholipids by cytosolic or secretory PLA2 and is converted to
prostaglandin H2 (PGH2) by COXs. PGH2 is then isomerized to
prostaglandin E2 (PGE2) by terminal PGES enzymes. PGES enzymes,
that lie downstream of COXs, occur in three forms in mammalian
cells. Among them, the microsomal and membrane-bound synthase
(namely mPGES-1) has received much more attention and established
as a novel drug target in the areas of inflammation, tumorigenesis,
and bone disorders. Hence, mPGES-1 is involved in a number of
diseases including arthritis, burn injury and pain diseases,
atherosis, cancer, and even the exacerbation of Alzheimer's
disease. Recently reported studies have led to the characterization
of its inducible distribution, expression, enzymatic kinetics, and
biological and pathological functions. The expression of mPGES-1 is
up-regulated by pro-inflammatory stimuli and down-regulated by
anti-inflammatory glucocorticoids, often in accordance with that of
COX-2. The protein mPGES-1 has been identified as the central
switch during immune-induced pyresis, and deletion of mPGES-1 would
reduce inducible and basal PGE2 production and alter the gastric
prostanoid profile. Compared to its up-stream enzymes, inhibition
of mPGES-1 does not block normal functions of other PGs and,
therefore, lacks the unexpected side effects produced by the
inhibition of COXs, making it more attractive for the development
of potential therapeutics, especially for the treatment of
inflammation-related diseases. However, no clinically useful
inhibitor of mPGES-1 has been identified. To date, only two types
of compounds, i.e. the COX-2 inhibitor NS-398 and
5-lipoxygenese-activating protein (FLAP) inhibitor MK-886 (see FIG.
9) and similar compounds (see e.g., Riendeau et al., Bioorg. Med.
Chem. Lett., 15:3352-3355), have been found to be able to inhibit
mPGES-1. None of these compounds is selective for mPGES-1. It is
highly desirable to develop more potent and selective inhibitors of
mPGES-1 based on the structure and function of the enzyme for
development of the next-generation therapeutics.
[0003] Initially, mPGES-1 was discovered as recombinant human
microsomal glutathione-S-transferase (GST)-1-like 1 (MGST1-L1) and
recognized as a member of membrane-associated proteins involved in
eicosanoid and glutathione (GSH) metabolism (MAPEG) superfamily. It
shows significant homology with other MAPEG proteins, especially
with the nearest subfamily member MGST1. Hydropathy analysis
suggests that all the MAPEG proteins have similar three-dimensional
and membrane-spanning topological properties. Site-directed
mutagenesis revealed that R110 has an essential role in the
catalytic function of mPGES-1, whereas the mutation on either R51
or R70 did not affect the activity. Unfortunately, further
structure-function investigation is restrained by the lack of the
detailed three-dimensional structure of this membrane-bound
protein, making the structure-based design of drugs targeting
mPGES-1 difficult. A two-dimensional (2D) electron projection map
(with a resolution of 10 .ANG.) of mPGES-1 revealed a trimer
structure (Thoren, et al., J. Biol. Chem. 2003, 278, 22199-22209)
which is very similar to that of MGST1, but the resolution of 10
.ANG. is insufficient for the purpose of building a
three-dimensional model of mPGES-1.
[0004] Accordingly, more precise models of the three-dimensional
structure of mPGES-1 are needed so that potent and selective
modulators of mPGES-1 activity can be identified.
SUMMARY
[0005] Provided herein are three-dimensional structures of the
substrate binding domain (SBD) of the microsomal prostaglandin E2
synthase-1 (mPGES-1), and three-dimensional structures of mPGES-1
trimers, useful for designing and identifying compounds that
modulate the activity of the synthase. Also provided are novel
methods for generating a set of candidate structures of mPGES-1,
the mPGES-1 substrate binding domain (SBD) and mPGES-1 trimers.
Also provided are methods of identifying compounds that bind to an
mPGES-1 structure provided herein, including those that bind to the
SBD of mPGES-1.
[0006] Accordingly, in one embodiment a method for identifying a
set of candidate structures includes a) obtaining a first amino
acid sequence derived from a query polypeptide; b) obtaining a
second amino acid sequence derived from a template polypeptide,
wherein the second sequence comprises: i) a predetermined
three-dimensional structure; and ii) at least 50% sequence homology
with the first sequence; c) performing a sequence alignment between
the first sequence and the second sequence, and identifying common
secondary structures; d) generating a plurality of candidate
topological structures by applying predetermined geometric
parameters to the secondary structures and transforming each
topological structure into the amino acid residues associated with
the secondary structures; e) generating a first conformation set by
screening the plurality of candidate topological structures with
the predetermined geometric parameters and identifying the
structures that correspond to the parameters; f) generating a
second conformation set by applying energy minimization functions
to the first conformation set and identifying energetically-favored
conformations; and g) generating a final conformation set by
selecting those structures that exhibit an energy gradient having a
root mean square deviation (RMSD) of less than 0.001 kcal
mol.sup.-1 .ANG..sup.-1, wherein the final conformation set
represents the set of candidate structures of the query
polypeptide.
[0007] In some embodiments, methods of identifying a set of
candidate structures of a polypeptide further include generating
the sequence alignment by generating the reciprocal position of the
conserved residues. In other embodiments, such methods further
include modeling the interaction of each member of the final
conformation set with at least one substrate, wherein the modeling
comprises molecular docking using binding site searching and/or
interaction energy scoring; and identifying amino acid residues
associated with the SBD that interact with the substrate.
[0008] In other embodiments, the methods further include
identifying at least one amino acid residue that interacts with the
substrate and determining the effect of the modification on
substrate binding to the modified polypeptide. In general the
modification is a substitution, such as a conservative or
non-conservative amino acid substitution. In yet another
embodiment, the methods further include producing the modified
polypeptide in vivo or in vitro and assaying the activity of the
modified polypeptide in vivo or in vitro.
[0009] In one aspect, a query polypeptide includes
membrane-spanning regions of amino acids. Such polypeptides include
the membrane-associated proteins involved in eicosanoid and
glutathione metabolism (MAPEG). In other aspects, the query
polypeptide is microsomal prostaglandin E synthase-1 (mPGES-1).
[0010] In another aspect, the template polypeptide is a member of
the membrane-associated proteins involved in eicosanoid and
glutathione metabolism (MAPEG), such as microsomal
glutathione-S-transferase-1 (MGST-1). Structural parameters can
include coordinates derived from 3D electron projection maps of a
template polypeptide, such as MGST1. In some aspects, the
structural parameters further include coordinates derived from 2D
electron projection maps of the query polypeptide, such as mPGES-1.
Structural parameters can correspond to the coordinates set forth
in Table 1.
[0011] In another embodiment, a representation of a
three-dimensional structure of the mPGES-1 substrate binding domain
(SBD) is provided. The representation is characterized in that: a)
amino acid residues Q36, R110, T114, Y130, and Q134 of mPGES-1 are
associated with the PGH2-binding site of the SBD; b) amino acid
residue Y130 of mPGES-1 are associated with the peroxy head of
prostaglandin H2 (PGH2) when PGH2 occupies at least a portion of
the binding site; c) amino acid residue Y130 of mPGES-1 is
associated with the --SH group of glutathione (GSH) when GSH
occupies at least a portion of the binding site; d) amino acid
residues R110, T114, and Q36 of mPGES-1 are associated with the
carboxyl tail of PGH2; e) the calculated binding free energy
(.DELTA.G) for an SBD-PGH2 complex is between -5.0 kcal/mol and
-9.0 kcal/mol; and f) the calculated binding free energy (AG) for
an SBD-GSH complex is between -4.0 kcal/mol and -8.0 kcal/mol.
[0012] In another embodiment, a representation of a
three-dimensional structure of an mPGES-1 trimer is provided. The
representation is characterized in that: a) each monomer of the
trimer comprises a representation of a three-dimensional structure
of the mPGES-1 substrate binding domain (SBD); b) the trimer
comprises C.sub.3-fold symmetry; and c) the representation of the
trimer comprises a homology model based on the crystallographic
structure of subunit 1 of cytochrome c oxidase.
[0013] In yet another embodiment, a method of structure-based
identification of candidate compounds for regulation of
interactions of mPGES-1 with its cognate ligands, is provided. The
method includes a) providing a three dimensional structure of
mPGES-1, the three dimensional structure being selected from the
group consisting of: i) the mPGES-1 substrate binding domain as set
forth in claim 23; and ii) the mPGES-1 trimer as set forth in claim
25; b) identifying at least one candidate compound for interacting
with the three dimensional structure of a) and performing structure
based drug design.
[0014] In another embodiment, a machine-readable medium embedded
with information that corresponds to the three-dimensional
structural representation of the mPGES-1 substrate binding domain
(SBD), is provided. Also provided is a machine-readable medium
embedded with information that corresponds to the three-dimensional
structural representation of the mPGES-1 trimer.
[0015] In one embodiment, a computer system including a
representation of the three-dimensional structure of the mPGES-1
substrate binding domain (SBD) and a user interface to view the
representation, is provided. Also provided is a computer system
that includes a representation of the three-dimensional structure
of the mPGES-1 trimer and a user interface to view the
representation.
[0016] The various methods and computer-generated structures
provided herein are suitable for use in conducting a biotechnology
business. Such a business can include identifying one or more
candidate compounds for regulation of interactions of mPGES-1 with
its cognate ligands, generating a machine-readable medium, or data
signal embodied in a carrier wave, embedded with information that
corresponds to the three-dimensional structural representation of
the candidate compound and providing the medium or data signal to
an end user.
[0017] In general, structures derived from the computer-generated
models provided herein encompass structures having coordinates that
differ by a root mean square deviation (RMSD) of less than about
1.5 .ANG., 0.75 .ANG., or 0.35 .ANG., or any deviation in this
range. In some aspects, the query polypeptide includes an amino
acid sequence having at least 75%, at least 85%, or at least 95%,
or any percent in this range, amino acid sequence identity to the
template polypeptide.
[0018] In other embodiments, a structure of a synthase molecule
provided herein also includes a ligand complexed with the synthase
molecule. In some aspects, the ligand is a small molecule.
[0019] The details of one or more embodiments of the disclosure are
set forth in the accompanying drawings and the description below.
Other features, objects, and advantages will be apparent from the
description and drawings, and from the claims.
BRIEF DESCRIPTION OF DRAWINGS
[0020] The file of this patent contains at least one drawing
executed in color. Copies of this patent with color drawing(s) will
be provided by the Patent and Trademark Office upon request and
payment of the necessary fee.
[0021] FIG. 1 depicts a sequence alignment of mPGES-1 with MGST1.
Stars refer to identical residues, whereas filled period or double
filled period refer to conservative substitutions. All these
positions (with stars and filled periods) give the total homology
of mPGES-1 with MGST1 as 73%. Helices of mPGES-1 are labeled.
Mutated residues are numbered below the sequence.
[0022] FIG. 2 depicts the second set of 1934 conformations
clustered into four groups based on their energies and C-alpha root
mean square deviation (RMSD) values relative to the initial
topological model. Group I (1232 candidates) was discarded due to
their positive potential energies, whereas groups II (285
candidates), III (286 candidates) and IV (131 candidates) were used
to derive the final set of 27 candidates. The selected 27
candidates are shown as triangles.
[0023] FIG. 3 depicts conformational root-mean square deviation
(RMSD) from the initial topological model for the finally selected
27 candidates of the SBD model of mPGES-1.
[0024] FIG. 4A depicts a top view from outside of the membrane of
an optimized complex model of the SBD of mPGES-1 binding with
substrates PGH2 and GSH. The SBD of mPGES-1 is represented as
ribbon, and the two substrates are shown in stick.
[0025] FIG. 4B depicts PGH2 binding with the enzyme. Residues in
the SBD of mPGES-1 within 5 .ANG. around PGH2 are shown and labeled
in stick, the electrostatic interaction is represented as the plus
(+) and minus (-) signs, and the hydrogen bonding is indicated with
dashed line.
[0026] FIG. 4C depicts GSH binding with the SBD of mPGES-1.
Residues in the SBD of mPGES-1 within 5 .ANG. around GSH are shown
and labeled.
[0027] FIG. 5 depicts the cell membrane portion of mPGES-1
expression in E. coli. Bars represent the percentage of expression
for the five mutants (Q36E, R110T, T114V, Y130I, and Q134E)
relative to the wild-type (WT) of mPGES-1.
[0028] FIG. 6 depicts the relative enzymatic activity of mPGES-1
and its mutants. The relative activity is obtained by normalization
from its expression level in FIG. 5 and the wild-type served as a
standard of 100 units.
[0029] FIG. 7 depicts experimentally measured K.sub.M of mPGES-1
and its mutants.
[0030] FIG. 8 depicts the calculated K.sub.d values of PGH2 binding
with wild-type mPGES-1 and its mutants in comparison with the
experimentally derived K.sub.M.
[0031] FIG. 9 depicts the chemical structures of PGH2, PGE2, and
COX-2 inhibitors NS-398 and 5-lipoxygenese-activating protein
(FLAP) inhibitor MK-886.
[0032] FIG. 10 depicts a flow diagram of an exemplary "ab initio"
rationale for generating three-dimensional models of
polypeptides.
[0033] FIG. 11A depicts an exemplary view of three-dimensional
model #1 obtained for the mPGES-1 trimer.
[0034] FIG. 11B depicts another an exemplary view of
three-dimensional model #1 obtained for the mPGES-1 trimer.
[0035] FIG. 11C depicts yet another exemplary view of
three-dimensional model #1 obtained for the mPGES-1 trimer.
[0036] FIG. 12 depicts a sequence alignment of human mPGES-1 (SEQ
ID NO:12) with the cytochrome c template (SEQ ID NO:11). The
alpha-helices are underlined.
[0037] FIG. 13A and FIG. 13B depict three-dimensional model #2 of
the mPGES-1 trimer complexed with an inhibitor (i.e. MK-886) in
each substrate binding domain (SBD).
[0038] Like reference symbols in the various drawings indicate like
elements.
DETAILED DESCRIPTION
[0039] Three-dimensional (3D) representations, methods, and
computer programs for the ab initio prediction of three-dimensional
structures of proteins are provided. Specifically, provided herein
are representations of novel three-dimensional structures of a
microsomal prostaglandin E synthase-1 (mPGES-1) molecule, and the
structure of the mPGES-1 trimer. Also provided are methods of
generating such representations and methods of using such
information to identify, design and/or modify compounds that
modulate the activity of an mPGES-1 molecule. In addition, computer
systems that include such information are provided.
[0040] Throughout the present disclosure the term "microsomal
prostaglandin E synthase-1 (mPGES-1) molecule" or "synthase
molecule" are used describe various embodiments of the inventions.
It is understood that these terms encompass a single molecule of
mPGES-1 (e.g., a monomer), fragments of mPGES-1 (e.g., the
substrate binding domain (SBD)), and/or multimers of mPGES-1 (e.g.,
an mPGES-1 trimer).
Methods of Identifying Sets of Conformations
[0041] Provided herein are computer-implemented methods for
homology modeling by comparing the amino acid sequence of a query
polypeptide (e.g., mPGES-1) with the amino acid sequence of a
template polypeptide (e.g., a membrane-associated protein involved
in eicosanoid and glutathione metabolism (MAPEG)). The query
polypeptide shares sequence homology with the template polypeptide.
Structural information associated with the template polypeptide
(e.g., atomic coordinates based on NMR or x-ray crystallographic
data) can be used to generate a model of the query polypeptide. The
model can be further refined by subjecting the preliminary model to
energy minimization to yield an energy minimized model and
remodeling regions of the energy minimized model where
stereochemistry restraints are violated. These refinements yield
sets of conformations that can be further subjected to, for
example, in silico interactions with a suitable substrate.
[0042] The term "protein" is understood to include the terms
"polypeptide" and "peptide" (which, at times, may be used
interchangeably herein) within its meaning. In addition, proteins
comprising multiple polypeptide subunits (e.g., dimers, trimers or
tetramers), as well as other non-proteinaceuos catalytic molecules
will also be understood to be included within the meaning of
"protein" as used herein. Similarly, "protein fragments," i.e.,
stretches of amino acid residues that comprise fewer than all of
the amino acid residues of a protein, are also within the scope of
the invention and may be referred to herein as "proteins."
Additionally, "protein domains" are also included within the term
"protein." A "protein domain" represents a portion of a protein
comprised of its own semi-independent folded region having its own
characteristic spherical geometry with hydrophobic core and polar
exterior.
[0043] The methods provided herein can be employed in those cases
where a sequence comparison indicates possible local structural
similarity of the query protein to protein(s) of known structure.
For example, a small structural motif (a long helix, helical
hairpin, fragment of a beta-sheet) can be used as a modeling
"template". Such a template can provide a folding scaffold, thereby
reducing the conformational space to be searched in order to
assemble the remaining portions of the structure of the query
protein.
[0044] The structural motif can be associated with, for example, a
"functional site." The term "functional site" or "functional
domain" generally refer to any site in a protein that confers a
function on the protein. Representative examples include active
sites (i.e., those sites in catalytic proteins where catalysis
occurs), protein-protein interaction sites, sites for chemical
modification (e.g., glycosylation and phosphorylation sites), and
ligand binding sites. Ligand binding sites include, but are not
limited to, metal binding sites, co-factor binding sites, antigen
binding sites, substrate channels and tunnels, and substrate
binding domains (SBD). In an enzyme, a ligand binding site that is
a substrate binding domain may also be an active site. Functional
sites may also be composites of multiple functional sites, wherein
the absence of one or more sites comprising the composite results
in a loss of function. Identifying compounds that bind to a
functional site, such as a substrate binding domain, are discussed
below.
[0045] Accordingly, in one embodiment a method for identifying a
set of candidate structures includes a) obtaining a first amino
acid sequence derived from a query polypeptide; b) obtaining a
second amino acid sequence derived from a template polypeptide,
wherein the second sequence comprises: i) a predetermined
three-dimensional structure; and ii) at least 50% sequence homology
with the first sequence; c) performing a sequence alignment between
the first sequence and the second sequence, and identifying common
secondary structures; d) generating a plurality of candidate
topological structures by applying predetermined geometric
parameters to the secondary structures and transforming each
topological structure in to the amino acid residues associated with
the secondary structures; e) generating a first conformation set by
screening the plurality of candidate topological structures with
the predetermined geometric parameters and identifying the
structures that correspond to the parameters; f) generating a
second conformation set by applying energy minimization functions
to the first conformation set and identifying energetically-favored
conformations; and g) generating a final conformation set by
selecting those structures that exhibit an energy gradient having a
root mean square deviation (RMSD) of less than 0.001 kcal mol-1
.ANG.-1, wherein the final conformation set represents the set of
candidate structures of the query polypeptide.
[0046] Identifying a set of candidate structures is based, in part,
on computer generated structures derived, in part, from crystal
structures of homologous proteins (i.e., "homologs"). As used
herein, the term "homolog" refers to the polypeptide molecule, or a
functional domain from said polypeptide from a first source having
at least about 30%, 40% or 50% sequence identity, or at least about
60%, 70% or 75% sequence identity, or at least about 80% sequence
identity, or more preferably at least about 85% sequence identity,
or even more preferably at least about 90% sequence identity, and
most preferably at least about 95%, 97% or 99% amino acid sequence
identity with the polypeptide, or any functional domain thereof,
from a second source. The second source may be a version of the
molecule from the first source that has been genetically altered by
any available means to change the primary amino acid or may be from
the same or a different species than that of the first source.
[0047] As previously mentioned, a template polypeptide includes a
"predetermined three-dimensional structure." As used herein, a
"predetermined three-dimensional structure" includes crystalline
forms of a polypeptide provided as data in the form of structure
coordinates. As used herein, the term "atomic coordinates" or
"structure coordinates" refers to mathematical coordinates that
describe the positions of atoms in a crystal in a Protein Data Bank
(PDB) format, including X, Y, Z and B, for each atom. The
diffraction data obtained from the crystals are used to calculate
an electron density map of the repeating unit of the crystal. The
electron density maps may be used to establish the positions (i.e.,
coordinates X, Y and Z) of the individual atoms within the
crystal.
[0048] The computer-generated structure coordinates identified for
a query polypeptide, or sets or polypeptides, based upon the
coordinates available from a template polypeptide, or an active
site thereof, define a unique configuration of points in space.
Those of skill in the art understand that a set of structure
coordinates for a polypeptide, or a polypeptide complexed with a
chemical entity, or a portion thereof, define a relative set of
points that, in turn, define a configuration in three dimensions. A
similar or identical configuration can be defined by an entirely
different set of coordinates, provided the distances and angles
between coordinates remain essentially the same. Accordingly, the
coordinates provide a "scalable" configuration of points that can
be modified by increasing or decreasing the distances between
coordinates by a scalar factor while keeping the angles essentially
the same.
[0049] For example, in identifying sets of conformationally
suitable structures, it may be desirable to identify
"conformational" or "secondary" constraints. These terms refer to
the presence of a particular protein conformation, for example, an
alpha-helix, parallel and anti-parallel beta strands, leucine
zipper, zinc finger, etc. in which an amino acid residue, or group
of residues, is located. In addition, conformational or secondary
constraints can include amino acid sequence information without
additional structural information. As an example, "--C--X--X--C--"
is a conformational constraint indicating that two cysteine
residues must be separated by two other amino acid residues, the
identities of each of which are irrelevant in the context of this
particular constraint.
[0050] An "identity constraint" refers to a constraint that
indicates the identity of a particular amino acid residue at a
particular amino acid position in a protein. Typically, an amino
acid position is determined by counting from the amino-terminal
residue of the protein up to and including the residue in question.
As those in the art will appreciate, comparison between related
proteins may reveal that the identity of a particular amino acid
residue at a given amino acid position in a protein is not entirely
conserved, i.e., different amino acid residues may be present at a
particular amino acid position in related proteins, or even in
allelic or other variants of the same protein.
[0051] In another embodiment, methods of identifying a set of
candidate structures of a polypeptide further include modeling the
interaction of each member of a final conformation set with at
least one "substrate" or "cognate ligand." Such modeling can be in
the form of molecular docking using binding site searching and/or
interaction energy scoring. The amino acid residues associated with
the SBD, and that interacts with the substrate, can be
identified.
[0052] A "functional site" refers to any site in a protein that has
a function. Representative examples include active sites (i.e.,
those sites in catalytic proteins where catalysis occurs),
protein-protein interaction sites, sites for chemical modification
(e.g., glycosylation and phosphorylation sites), and substrate
binding sites. Substrate binding sites include, but are not limited
to, metal binding sites, co-factor binding sites, antigen binding
sites, substrate channels and tunnels, and ligand binding sites. In
an enzyme, a substrate binding site may also be an active site.
[0053] The methods provided herein include using a known ligand
that binds to both the query polypeptide and template polypeptide
in order to further refine the structure of the query polypeptide.
Accordingly, the structure of the substrate binding domain (SBD) of
an mPGES-1 molecule can be delineated using mPGES-1 cognate ligands
(e.g., PGH2 and GSH).
[0054] Active sites, such as substrate binding domains, are of
significant utility in the identification of compounds that
specifically interact with, and modulate the activity of, a
particular polypeptide. The association of natural ligands or
substrates with the active sites of their corresponding receptors
or enzymes is the basis of many biological mechanisms of action.
Similarly, many compounds exert their biological effects through
association with the active sites of receptors and enzymes. Such
associations may occur with all or any parts of the active site. An
understanding of such associations helps lead to the design of
compounds that modulate the activity of their target. Therefore,
this information is valuable in designing potential modifiers of
mPGES-1 activity, as discussed in more detail below.
[0055] In other embodiments, the methods further include
identifying at least one amino acid residue that interacts with the
substrate, modifying the residue, and determining the effect of the
modification on substrate binding to the modified polypeptide. In
general the modification is a substitution, such as a conservative
or non-conservative amino acid substitution. It may be desirable to
make mutations in the active site of a polypeptide, e.g., to
increase, reduce or completely eliminate synthase activity.
Mutations that will reduce or completely eliminate the activity of
mPGES-1 are provided in the examples below. Such mutations can be
introduced into a computer generated structural representation of a
molecule. Such "in silico" mutagenesis can be used to confirm or
augment the computer generated structural representation of, for
example, the mPGES-1 molecule. In vivo and in vitro mutagenesis can
be used to further confirm or augment the information generated in
silico. Such mutations are discussed further in the examples
provided below.
[0056] In yet another embodiment, the methods further include
producing the modified polypeptide in vivo or in vitro and assaying
the activity of the modified polypeptide in vivo or in vitro.
Methods of producing modified polypeptides in vivo or in vitro are
well known to the skilled artisan. Examples of such methods are
provided below.
[0057] In general amino acid modifications include substitutions of
one amino acid for another. Such substitutions, whether
manufactured in silico, in vitro, or in vivo, generally include
conservative and non-conservative amino acid substitutions.
[0058] As used herein, an "amino acid" is a molecule having the
structure wherein a central carbon atom (the alpha-carbon atom) is
linked to a hydrogen atom, a carboxylic acid group (the carbon atom
of which is referred to herein as a "carboxyl carbon atom"), an
amino group (the nitrogen atom of which is referred to herein as an
"amino nitrogen atom"), and a side chain group, R. When
incorporated into a peptide, polypeptide, or protein, an amino acid
loses one or more atoms of its amino and carboxylic groups in the
dehydration reaction that links one amino acid to another. As a
result, when incorporated into a protein, an amino acid is referred
to as an "amino acid residue." In the case of naturally occurring
proteins, an amino acid residue's R group differentiates the 20
amino acids from which proteins are synthesized, although one or
more amino acid residues in a protein may be derivatized or
modified following incorporation into protein in biological systems
(e.g., by glycosylation and/or by the formation of cysteine through
the oxidation of the thiol side chains of two non-adjacent cysteine
amino acid residues, resulting in a disulfide covalent bond that
frequently plays an important role in stabilizing the folded
conformation of a protein, etc.). As those in the art will
appreciate, non-naturally occurring amino acids can also be
incorporated into proteins, particularly those produced by
synthetic methods, including solid state and other automated
synthesis methods. Examples of such amino acids include, without
limitation, alpha-amino isobutyric acid, 4-amino butyric acid,
L-amino butyric acid, 6-amino hexanoic acid, 2-amino isobutyric
acid, 3-amino propionic acid, ornithine, norlensine, norvaline,
hydroxproline, sarcosine, citralline, cysteic acid, t-butylglyine,
t-butylalanine, phenylylycine, cyclohexylalanine, beta-alanine,
fluoro-amino acids, designer amino acids (e.g., beta-methyl amino
acids, alpha-methyl amino acids, alpha-methyl amino acids) and
amino acid analogs in general. In addition, when an alpha-carbon
atom has four different groups (as is the case with the 20 amino
acids used by biological systems to synthesize proteins, except for
glycine, which has two hydrogen atoms bonded to the carbon atom),
two different enantiomeric forms of each amino acid exist,
designated D and L. In mammals, only L-amino acids are incorporated
into naturally occurring polypeptides. Of course, the instant
invention envisions proteins incorporating one or more D- and
L-amino acids, as well as proteins comprised of just D- or L-amino
acid residues.
[0059] Conventional amino acid residue abbreviations are used
throughout this patent, and both the one and three letter codes are
reproduced here for convenience: alanine="A" or "Ala"; arginine="R"
or "Arg"; asparagine="N" or "Asn"; aspartic acid="D" or "Asp";
cysteine="C" or "Cys"; glutamic acid="E" or "Glu" glutamine="Q" or
"Gln"; glycine="G" or "Gly"; histidine="H" or "His"; isoleucine="I"
or "Ile"; leucine="L" or "Leu"; lysine "K" or "Lys"; methionine="M"
or "Met"; phenylalanine="F" of "Phe"; proline "P" or "Pro";
serine="S" or "Ser"; threonine="T" or "Thr"; tryptophan="W" or
"Trp"; tyrosine="Y" or "Tyr"; and valine="V" or "Val". Amino acid
sequences are written from amino to carboxy-terminus, unless
otherwise indicated. Conventional nucleic acid nomenclature is also
used, wherein "A" means adenine, "C" means cytosine, "G" means
guanine, "T" means thymine, and "U" means uracil. Nucleotide
sequences are written from 5' to 3', unless otherwise
indicated.
[0060] Conservative amino acid substitutions are well-known in the
art, and include substitutions made on the basis of a similarity in
polarity, charge, solubility, hydrophobicity and/or the
hydrophilicity of the amino acid residues involved. Typical
conservative substitutions are those in which the amino acid is
substituted with a different amino acid that is a member of the
same class or category, as those classes are defined herein. Thus,
typical conservative substitutions include aromatic to aromatic,
apolar to apolar, aliphatic to aliphatic, acidic to acidic, basic
to basic, polar to polar, etc. Other conservative amino acid
substitutions are well known in the art.
Structures
[0061] As those in the art are aware, protein structures can be of
different quality. Presently, the highest quality determination
methods are experimental structure prediction methods based on
x-ray crystallography and/or NMR spectroscopy. In x-ray
crystallography, "high resolution" structures are those wherein
atomic positions are determined at a resolution of about 2 .ANG. or
less, and enable the determination of the three-dimensional
positioning of each atom (or at least each non-hydrogen atom) of a
protein. "Medium resolution" structures are those wherein atomic
positioning is determined at about the 2-4 .ANG. level, while "low
resolution" structures are those wherein the atomic positioning is
determined in about the 4-8 .ANG. range. Herein, protein structures
that have been determined by x-ray crystallography or NMR may be
referred to as "template polypeptides" or "experimental
structures," as compared to those determined by computational
methods, i.e., derived from the application of one or more computer
algorithms to a primary amino acid sequence to predict protein
structure.
[0062] Accordingly, in another embodiment, a representation of a
three-dimensional structure of the mPGES-1 substrate binding domain
(SBD) is provided. The representation is characterized in that: a)
amino acid residues Q36, R110, T114, Y130, and Q134 of mPGES-1 are
associated with the PGH2-binding site of the SBD; b) amino acid
residue Y130 of mPGES-1 are associated with the peroxy head of
prostaglandin H2 (PGH2) when PGH2 occupies at least a portion of
the binding site; c) amino acid residue Y130 of mPGES-1 is
associated with the --SH group of glutathione (GSH) when GSH
occupies at least a portion of the binding site; d) amino acid
residues R110, T114, and Q36 of mPGES-1 are associated with the
carboxyl tail of PGH2; e) the calculated binding free energy (AG)
for an SBD-PGH2 complex is between -5.0 kcal/mol and -9.0 kcal/mol;
and f) the calculated binding free energy (AG) for an SBD-GSH
complex is between -4.0 kcal/mol and -8.0 kcal/mol.
[0063] In another embodiment, a representation of a
three-dimensional structure of an mPGES-1 trimer is provided. The
representation is characterized in that: a) each monomer of the
trimer comprises a representation of a three-dimensional structure
of the mPGES-1 substrate binding domain (SBD); b) the trimer
comprises C.sub.3-fold symmetry; and c) the representation of the
trimer comprises a homology model based on the crystallographic
structure of subunit 1 of cytochrome c oxidase.
[0064] As discussed throughout the specification, protein
structures can be determined entirely by computational methods,
including, but not limited to, homology modeling, threading, and ab
initio methods. Often, models produced by such computational
methods are "reduced" models. A "reduced model" refers to a
three-dimensional structural model of a protein wherein fewer than
all heavy atoms (e.g., carbon, oxygen, nitrogen, and sulfur atoms)
of the protein are represented. For example, a reduced model might
consist of just the alpha-carbon atoms of the protein, with each
amino acid connected to the subsequent amino acid by a virtual
bond. As will be appreciated by those in the art, more detailed
model structures of a protein can be assembled from a reduced
model. For example, a reduced model comprised only of amino acid
residue side chain centers of mass implicitly specifies the
location of the atoms comprising the side chain, as well the
position of the peptide backbone. Accordingly, whatever greater
level of atomic detail is required, if any, for the particular
application can be added to a reduced model, and it is understood
that once a protein structure based on a reduced model has been
generated, all or a portion of it may be further refined to include
additional predicted detail, up to including all atom
positions.
[0065] Computational methods usually produce lower quality
structures than experimental methods, and the models produced by
computational methods are often called "inexact models." In
contrast, the present methods provide a mechanism for generating
precise three-dimensional structure of an mPGES-1 synthase molecule
using various forms of information. In the present methods
structural motifs from a query polypeptide can be compared to
similar motifs in a homologous template polypeptide. The comparison
can be repeatedly refined until a final conformation set is
obtained. Throughout the refinement process, atomic positions of
atoms in the query polypeptide can be repeatedly compared to those
of the template polypeptide. The differences can be quantified via
a measure called "root mean square deviation" (RMSD). A query model
having an RMSD of about 2.0 .ANG. or less as compared to a
corresponding experimentally determined template structure is
considered "high quality". Frequently, predicted query models have
an RMSD of about 2.0 .ANG. to about 6.0 .ANG. when compared to one
or more experimentally determined template structures, and are
called "inexact models." As those in the art will appreciate, RMSDs
can also be determined for one or more atomic positions when two or
experimental structures have been generated for the same
protein.
[0066] The term "root mean square deviation" means the square root
of the arithmetic mean of the squares of the deviations. It is a
way to express the deviation or variation from a trend or object.
For purposes of this invention, the "root mean square deviation"
defines the variation in the backbone of a template polypeptide
from the backbone of a query polypeptide or an active site portion
thereof, as defined by the structure coordinates described herein.
"Having substantially the same three-dimensional structure" refers
to a polypeptide that is characterized by a set of atomic structure
coordinates that have a root mean square deviation (RMSD) of less
than or equal to about 1.5 .ANG. when superimposed onto the atomic
structure coordinates of a template polypeptide when at least about
50% to 100% of the C-alpha atoms of the coordinates are included in
the superposition.
[0067] Slight variations in structure coordinates can be generated
by mathematically manipulating the template polypeptide structure
coordinates. For example, the structure coordinates could be
manipulated by crystallographic permutations of the structure
coordinates, fractionalization of the structure coordinates,
integer additions or subtractions to sets of the structure
coordinates, inversion of the structure coordinates or any
combination of the above. Alternatively, modifications in the
crystal structure due to mutations, additions, substitutions,
and/or deletions of amino acids, or other changes in any of the
components that make up the crystal, could also yield variations in
structure coordinates. Such slight variations in the individual
coordinates will have little effect on overall shape. If such
variations are within an acceptable standard error as compared to
the original coordinates, the resulting three-dimensional model is
considered to be structurally equivalent.
[0068] As used herein, the term "model" refers to a representation
in a tangible medium of the three-dimensional structure of a
protein, polypeptide or peptide. For example, a model can be a
representation of the three dimensional structure in an electronic
file, on a computer screen, on a piece of paper (i.e., on a two
dimensional medium), and/or as a ball-and-stick figure. Physical
three-dimensional models are tangible and include, but are not
limited to, stick models and space-filling models. The phrase
"imaging the model on a computer screen" refers to the ability to
express (or represent) and manipulate the model on a computer
screen using appropriate computer hardware and software technology
known to those skilled in the art. Such technology is available
from a variety of sources including, for example, Evans and
Sutherland, Salt Lake City, Utah, and Biosym Technologies, San
Diego, Calif. The phrase "providing a picture of the model" refers
to the ability to generate a "hard copy" of the model. Hard copies
include both motion and still pictures. Computer screen images and
pictures of the model can be visualized in a number of formats
including space-filling representations, a carbon traces, ribbon
diagrams and electron density maps. A variety of such
representations of the structural models of the present invention
are shown, for example, in the figures. In practice, predicting the
three-dimensional structure of a protein can be attempted on
various levels, ranging from purely de novo, or "ab initio,"
approaches to those that incorporate constraints derived from
experimental data.
[0069] The primary structure of a polypeptide can be defined as the
sequence of amino acid residues that comprise the polypeptide. The
alpha carbon of each residue form the scaffold upon which the
structure of the polypeptide is built. In general, the single bond
between an alpha-carbon and its attached R-group provides limited
rotational freedom. Collectively, such structural flexibility
enables a number of possible conformations to be assumed at a given
region within a polypeptide. As discussed in greater detail below,
the particular conformation actually assumed depends on
thermodynamic considerations, with the lowest energy conformation
being preferred.
[0070] In addition to primary structure, proteins also have
secondary, tertiary, and, in multi-subunit proteins, quaternary
structure. "Secondary structure" refers to local conformation of
the polypeptide chain, with reference to the covalently linked
atoms of the peptide bonds and alpha-carbon linkages that string
the amino acid residues of the protein together. Side chain groups
are not typically included in such descriptions. Representative
examples of secondary structures include alpha-helices, parallel
and anti-parallel beta structures, and structural motifs such as
helix-turn-helix, the leucine zipper, the zinc finger, the
beta-barrel, and the immunoglobulin fold. Movement of such domains
relative to each other often relates to biological function and, in
proteins having more than one function, different binding or
effector sites can be located in different domains.
[0071] "Tertiary structure" concerns the overall three-dimensional
structure of a protein, including the spatial relationships of
amino acid residue side chains and the geometric relationship of
different regions of the protein. "Quaternary structure" relates to
the structure and non-covalent association of different polypeptide
subunits in a multisubunit protein, such as a trimer.
Modulators of mPGES-1 Activity
[0072] As described above, molecular modeling involves the use of
computational methods, preferably computer assisted methods, to
build realistic models of query polypeptides that are identifiably
related in sequence to a template polypeptide having a known
crystal structure. The present invention also includes the use of
molecular and computer modeling techniques to design and select
ligands, such as small molecule agonists or antagonists or other
compounds that interact with mPGES-1 molecules. The methods
utilized in ligand modeling range from molecular graphics (i.e.,
three-dimensional representations) to computational chemistry
(i.e., calculations of the physical and chemical properties) to
make predictions about the binding of ligands or activities of
ligands; to design new ligands; and to predict novel molecules,
including ligands such as compounds that inhibit the activity of a
synthase, such a mPGES-1.
[0073] According to the present invention, a "cognate ligand" of a
mPGES-1 protein is any protein that interacts with or more
particularly, binds to, a mPGES-1 protein in nature (e.g., under
any normal, natural, or physiological conditions in vitro or in
vivo). As such, the term "cognate" is intended to refer to the
relationship in nature between mPGES-1 and other ligands. The term
ligand is intended to generically or generally refer to any ligand,
binding partner, corepressor, substrate (such terms being capable
of use interchangeably) or other protein or compound with which the
SBD of mPGES-1 interacts. As such, the term implies any interaction
relationship between mPGES-1 and another compound.
[0074] The structures used to perform the above-described method
have been described in detail above and in the Examples section,
and include any structural homologues of proteins described herein.
According to the present invention, the phrase "models that define
the three dimensional structure" is defined as any means of
obtaining, providing, supplying, accessing, displaying, retrieving,
or otherwise making available the models defining any three
dimensional structures as described herein. For example, the step
of providing can include, but is not limited to, accessing the
structure from a database or other source; importing the structure
into a computer or other database; displaying the model of the
structure in any manner, such as on a computer, on paper, etc.; and
determining the three dimensional structure described by the
present invention de novo using the guidance provided herein.
[0075] Methods of structure based identification of compounds of
the present invention include identifying a candidate compound for
interacting with an SBD in mPGES-1, represented by the structure
model, by performing structure based drug design with the model of
the structure. According to the present invention, the step of
"identifying" can refer to any screening process, modeling process,
design process, or other process by which a compound can be
selected as useful for binding or inhibiting the activity of
protein or complex according to the present invention. Methods of
structure-based identification of compounds are described in detail
throughout the specification.
[0076] Structure based identification of compounds (e.g., structure
based drug design, structure based compound screening, or structure
based structure modeling) refers to the prediction or design of a
conformation of a peptide, polypeptide, protein, or to the
prediction or design of a conformational interaction between such
protein, peptide or polypeptide, and a candidate compound, by using
the three dimensional structure of the peptide, polypeptide or
protein. Typically, structure based identification of compounds is
performed with a computer (e.g., computer-assisted drug design,
screening or modeling). For example, generally, for a protein to
effectively interact with (e.g., bind to) a compound, it is
necessary that the three dimensional structure of the compound to
assume a compatible conformation that allows the compound to bind
to the protein in such a manner that a desired result is obtained
upon binding. Knowledge of the three dimensional structures of the
components of the complexes described herein in the conformation in
which they bind to one another enables a skilled artisan to design
a compound having such compatible conformation, or to select such a
compound from available libraries of compounds and/or structures
thereof. For example, knowledge of the three dimensional structure
of the substrate binding domain of mPGES-1 enables one of skill in
the art to design or select a compound structure that is predicted
to bind to the SBD of mPGES-1 at that site and result in, for
example, inhibition of the binding of mPGES-1 to its natural
ligand. Similarly, one can design or select (identify) a compound
that has the opposite, or stimulatory effect on the complex
components.
[0077] Suitable structures and models useful for structure based
drug design are disclosed herein. Preferred target structures, such
as the mPGES-1 substrate binding domain or mPGES-1 trimer, include
any representation of the structure produced by any modeling method
disclosed herein.
[0078] According to the present invention, the step of identifying,
selecting or designing a compound for testing in a method of
structure based identification of the present invention can include
creating a new chemical compound structure or searching databases
of libraries of known compounds (e.g., a compound listed in a
computational screening database containing three dimensional
structures of known compounds). Designing can also be performed by
simulating chemical compounds having substitute moieties at certain
structural features. The step of designing can include selecting a
chemical compound based on a known function of the compound.
Chemical compounds can generally include any peptide,
oligonucleotide, carbohydrate and/or synthetic organic molecule. A
preferred step of designing comprises computational screening of
one or more databases of compounds in which the three-dimensional
structure of the compound is known and is interacted (e.g., docked,
aligned, matched, interfaced) with the three dimensional of a
mPGES-1 molecule provided herein by computer (e.g. as described by
Humblet and Dunbar, Animal Reports in Medicinal Chemistry, vol. 28,
pp. 275-283, 1993, M Venuti, ed., Academic Press). The compound
itself, if identified as a suitable candidate by the method of the
invention, can be synthesized and tested directly with one or more
of the components of an mPGES-1 molecule, or a molecule-ligand
complex, for example, in a biological assay. Methods to synthesize
suitable chemical or protein-based compounds are known to those of
skill in the art and depend upon the structure of the chemical
being synthesized. Methods to evaluate the bioactivity of the
synthesized compound depend upon the bioactivity of the compound
(e.g., inhibitory or stimulatory) and are discussed herein.
[0079] In a molecular diversity strategy, large compound libraries
are synthesized, for example, from peptides, oligonucleotides,
carbohydrates and/or synthetic organic molecules, using biological,
enzymatic and/or chemical approaches. The critical parameters in
developing a molecular diversity strategy include subunit
diversity, molecular size, and library diversity. The general goal
of screening such libraries is to utilize sequential application of
combinatorial selection to obtain high-affinity ligands for a
desired target, and then to optimize the lead molecules by either
random or directed design strategies.
[0080] In the present method of structure based identification of
compounds, it is not necessary to align the structure of a
candidate chemical compound (i.e., a chemical compound being
analyzed in, for example, a computational screening method of the
present invention) to each residue in a target site (target sites
will be discussed in detail below). Suitable candidate chemical
compounds can align to a subset of residues described for a target
site. For example, a subset of residues can include amino acid
residues Q36, R110, T114, Y130, and Q134, positioned in the
PGH2-binding site of an mPGES-1 molecule. Preferably, a candidate
chemical compound comprises a conformation that promotes the
formation of covalent or non-covalent cross-linking between the
target site and the candidate chemical compound. In one aspect, a
candidate chemical compound binds to a surface adjacent to a target
site to provide an additional site of interaction in a complex.
When designing an antagonist (e.g., a chemical compound that
inhibits the biological activity of a mPGES-1 molecule), for
example, the antagonist should bind with sufficient affinity to the
target binding site or substantially prohibit a ligand (e.g., a
molecule that specifically binds to the substrate binding domain)
from binding to a target site. It will be appreciated by one of
skill in the art that it is not necessary that the complementarity
between a candidate chemical compound and a target site extend over
all residues specified here in order to inhibit or promote binding
of a ligand.
[0081] One embodiment of the present invention for structure based
drug design comprises identifying a compound (e.g., a chemical
compound) that complements the shape of a component of an mPGES-1
molecule-PGES-1 substrate complex, including a portion of mPGES-1
(including, but not limited to, an mPGES-1 trimer. Such method is
referred to herein as a "geometric approach". In a geometric
approach, the number of internal degrees of freedom (and the
corresponding local minima in the molecular conformation space) is
reduced by considering only the geometric (hard-sphere)
interactions of two rigid bodies, where one body (the active site)
contains "pockets" or "grooves" that form binding sites for the
second body (the complementing molecule, such as a ligand).
[0082] The geometric approach is described by Kuntz et al., J. Mol.
Biol., 1982, 161:269-288, which is incorporated by this reference
in its entirety. The algorithm for chemical compound design can be
implemented using the software program DOCK Package, Version 1.0
(available from the Regents of the University of California).
Pursuant to the Kuntz algorithm, the shape of the cavity or groove
on the surface of a structure at a binding site or interface is
defined as a series of overlapping spheres of different radii. One
or more extant databases of crystallographic data (e.g., the
Cambridge Structural Database System maintained by University
Chemical Laboratory, Cambridge University, Lensfield Road,
Cambridge CB2 1EW, U.K.) or the Protein Data Bank maintained by
Brookhaven National Laboratory, is then searched for chemical
compounds that approximate the shape thus defined. Chemical
compounds identified by the geometric approach can be modified to
satisfy criteria associated with chemical complementarity, such as
hydrogen bonding, ionic interactions or Van der Waals
interactions.
[0083] Another embodiment provides for structure based
identification of compounds comprises determining the interaction
of chemical groups ("probes") with an active site at sample
positions within and around a binding site or interface, resulting
in an array of energy values from which three dimensional contour
surfaces at selected energy levels can be generated. This method is
referred to herein as a "chemical-probe approach." The
chemical-probe approach to the design of a chemical compound of the
present invention is described by, for example, Goodford, J. Med.
Chem., 1985, 28:849-857, which is incorporated by this reference
herein in its entirety, and is implemented using an appropriate
software package, including for example, GRID (available from
Molecular Discovery Ltd., Oxford OX2 9LL, U.K.). The chemical
prerequisites for a site-complementing molecule can be identified
at the outset, by probing the substrate binding domain (SBD) of an
mPGES-1 molecule with different chemical probes, e.g., water, a
methyl group, amine nitrogen, carboxyl oxygen and/or a hydroxyl.
Preferred sites for interaction between an active site and a probe
are determined. Putative complementary chemical compounds can be
generated using the resulting three dimensional patterns of such
sites.
[0084] According to the present invention, suitable candidate
compounds to test using the method of the present invention include
proteins, peptides or other organic molecules, and inorganic
molecules. Suitable organic molecules include small organic
molecules. Peptides refer to small molecular weight compounds
yielding two or more amino acids upon hydrolysis. A polypeptide is
comprised of two or more peptides. As used herein, a protein is
comprised of one or more polypeptides. Preferred therapeutic
compounds to design include peptides composed of "L" and/or "D"
amino acids that are configured as normal or retroinverso peptides,
peptidomimetic compounds, small organic molecules, or homo- or
hetero-polymers thereof, in linear or branched configurations.
Suitable compounds for design or identification are described in
detail below.
[0085] A compound that is identified by the method of the present
invention can originate from a compound having chemical and/or
stereochemical complementarity with a site on one or more
components of a SBD of a mPGES-1 molecule as described herein. Such
complementarity is characteristic of a compound that matches the
surface of the protein(s) either in shape or in distribution of
chemical groups and binds to protein(s) to regulate (e.g., by
inhibition or stimulation/enhancement) binding of a mPGES-1
molecule to one or more of its cognate ligands, for example, or to
otherwise modulate the biological activity of mPGES-1.
[0086] The following general sites of amino acid residues Q36,
R110, T114, Y130, and Q134, positioned in the PGH2-binding site are
targets for structure based drug design or identification of
candidate compounds and lead compounds (also referred to herein as
target sites or active sites), although other sites may become
apparent to those of skill in the art based on the
three-dimensional structures provided herein. Although many of the
sites described below are illustrated with respect to the specific
amino acid sequence of a particular mPGES-1 molecule because the
tertiary structures are predicted to be highly similar in
homologous target sites on other highly related proteins and
complexes (e.g., the homologous protein in different mammalian
species; different mPGES-1 proteins that are structurally related)
it is to be understood that the description of the target sites is
intended to encompass all other such homologues of the exemplified
sequences and structures. One of skill in the art can readily
extrapolate the amino acid residues within a sequence described
herein to the corresponding amino acid residues in a highly related
sequence simply by aligning the related sequences. More
specifically, one of skill in the art can readily determine whether
a given sequence aligns with another sequence, as well as identify
conserved regions of sequence identity or homology within
sequences, by using any of a number of software programs that are
publicly available. For example, one can use BLOCKS (GIBBS) and
MAST (Henikoff et al., Gene, 1995, 163:17-26; Henikoff et al.,
Genomics 1994, 19:97-107), typically using standard manufacturer
defaults.
[0087] Exemplary target sites include, but are not limited to: (1)
amino acid residues Q36, R110, T114, Y130, and Q134, positioned in
the PGH2-binding site; (2) amino acid residue Y130 in proximity to
the peroxy head of PGH2 and the --SH group of GSH in the binding
site; around residue Y130 of mPGES-1, reflecting the distinct role
of Y130 residue; (3) the mPGES-1-catalyzed reaction of PGH2 can be
initialized by the electrophilic attack of the --SH group of GSH at
the peroxy oxygen of PGH2; and (4) amino acid residues R110, T114,
and Q36 contact the carboxyl tail of PGH2. These target sites are
described in detail in the Examples and the Figures. Combinations
of any of these general sites are also suitable target sites. These
sites are generally referenced with regard to the tertiary
structure of the sites. Even if some of such sites were generally
known or hypothesized to be important sites prior to the present
invention, the present invention actually defines the sites in
three dimensions and confirms or newly identifies residues that are
important targets that could not be confirmed or identified prior
to the present invention. The use of any of these target sites as a
three dimensional structure is novel and encompassed by the present
invention. Many of these target sites are further described below
and illustrated in the Figures and Examples of the invention.
[0088] The potential, predicted inhibitory agonist, inhibitory
antagonist, or binding effect of a ligand or other compound on
mPGES-1 molecules, such as the substrate binding site and/or
mPGES-1 trimers, may be analyzed prior to its actual synthesis and
testing by the use of computer modeling techniques. If the
theoretical structure of the given compound suggests insufficient
interaction and association between it and the mPGES-1 molecules,
synthesis and testing of the compound may be obviated. However, if
computer modeling indicates a strong interaction, the molecule may
then be synthesized and tested for its ability to interact with
mPGES-1 molecules. In this manner, synthesis of inoperative
compounds may be avoided. In some cases, inactive compounds are
synthesized predicted on modeling and then tested to develop a SAR
(structure-activity relationship) for compounds interacting with a
specific region of mPGES-1 molecules, such as the substrate binding
site, or a multimer of mPGES-1, such as an mPGES-1 trimer.
[0089] One skilled in the art may use one of several methods to
screen chemical entities fragments, compounds, or agents for their
ability to associate with mPGES-1 molecules. This process may begin
by visual inspection of, for example, the active site based on the
atomic coordinates of the polypeptide or the polypeptide complexed
with a ligand. Selected chemical entities, compounds, or agents may
then be positioned in a variety of orientations, or docked within
an individual binding pocket of mPGES-1 molecules. Docking may be
accomplished using software-such as Quanta and Sybyl, followed by
energy minimization and molecular dynamics with standard molecular
mechanics forcefields, such as CHARMM and AMBER.
[0090] The use of software such as GRID, a program that determines
probable interaction sites between probes with various functional
group characteristics and the macromolecular surface, is used to
analyze the surface sites to determine structures of similar
inhibiting proteins or compounds. The GRID calculations, with
suitable inhibiting groups on molecules (e.g., protonated primary
amines) as the probe, are used to identify potential hotspots
around accessible positions at suitable energy contour levels. The
program DOCK may be used to analyze an active site or ligand
binding site and suggest ligands with complementary steric
properties. See also, Kellenberger et al., Proteins, 2004,
54:671-80; Oldfield, 2003, Methods Enzymol. 374:271-300; Richardson
et al., 2003, Methods Enzymol. 374:385-412; Terwilliger, 2003, Acta
Crystallogr D Biol Crystallogr. 59:1174-82; Toerger and
Sacchettini, 2003, Methods Enzymol. 374:244-70; von Grotthuss et
al., 2004, Science 304:1597-9; Rajakiannan et al., 2004, J
Synchrotron Radiat. 11:358-62; Claude et al., 2004, Nucleic Acids
Res. 32:W606-9; Suhre and Sanejouand, 2004, Nucleic Acids Res.
32:W610-4.
[0091] Once a compound that associates with mPGES-1 molecules has
been optimally selected or designed, as described above,
substitutions may then be made in some of its atoms or side groups
in order to improve or modify its binding properties. Generally,
initial substitutions are conservative, i.e., the replacement group
will have approximately the same size, shape, hydrophobicity and
charge as the original group. It should, of course, be understood
that components known in the art to alter conformation may be
avoided. Such substituted chemical compounds may then be analyzed
for efficiency of fit to a mPGES-1 molecules by the same computer
methods described in detail above.
Data Storage and Retrieval
[0092] The invention encompasses machine-readable media embedded
with the three-dimensional structure of the model described herein,
or with portions thereof. As used herein, "machine-readable medium"
refers to any medium that can be read and accessed directly by a
computer or scanner. Such media include, but are not limited to:
magnetic storage media, such as floppy discs, hard disc storage
medium and magnetic tape; optical storage media such as optical
discs or CD-ROM; electrical storage media such as RAM or ROM; and
hybrids of these categories such as magnetic/optical storage media.
Such media further include paper on which is recorded a
representation of the atomic structure coordinates, e.g., Cartesian
coordinates, that can be read by a scanning device and converted
into a three-dimensional structure with an OCR.
[0093] A variety of data storage structures are available to a
skilled artisan for creating a computer readable medium having
recorded thereon the atomic structure coordinates of the invention
or portions thereof and/or X-ray diffraction data. The choice of
the data storage structure will generally be based on the means
chosen to access the stored information. In addition, a variety of
data processor programs and formats can be used to store the
sequence and X-ray data information on a computer readable medium.
Such formats include, but are not limited to, Protein Data Bank
("PDB") format (Research Collaboratory for Structural
Bioinformatics; Cambridge Crystallographic Data Centre format;
Structure-data ("SD") file format (MDL Information Systems, Inc.;
Dalby et al., J. Chem. Inf. Comp. Sci., 1992, 32:244-255), and
line-notation, e.g., as used in SMILES (Weininger, J. Chem. Inf.
Comp. Sci., 1988, 28:31-36). Methods of converting between various
formats read by different computer software will be readily
apparent to those of skill in the art, e.g., BABEL (v. 1.06,
Walters & Stahl, .COPYRGT.1992, 1993, 1994). All format
representations of the polypeptide coordinates described herein, or
portions thereof, are contemplated by the present invention. By
providing computer readable medium having stored thereon the atomic
coordinates of the invention, one of skill in the art can routinely
access the atomic coordinates of the invention, or portions
thereof, and related information for use in modeling and design
programs, described in detail below.
[0094] While Cartesian coordinates are important and convenient
representations of the three-dimensional structure of a
polypeptide, those of skill in the art will readily recognize that
other representations of the structure are also useful. Therefore,
the three-dimensional structure of a polypeptide, as discussed
herein, includes not only the Cartesian coordinate representation,
but also all alternative representations of the three-dimensional
distribution of atoms. For example, atomic coordinates may be
represented as a Z-matrix, wherein a first atom of the protein is
chosen, a second atom is placed at a defined distance from the
first atom, a third atom is placed at a defined distance from the
second atom so that it makes a defined angle with the first atom.
Each subsequent atom is placed at a defined distance from a
previously placed atom with a specified angle with respect to the
third atom, and at a specified torsion angle with respect to a
fourth atom. Atomic coordinates may also be represented as a
Patterson function, wherein all interatomic vectors are drawn and
are then placed with their tails at the origin. This representation
is particularly useful for locating heavy atoms in a unit cell. In
addition, atomic coordinates may be represented as a series of
vectors having magnitude and direction and drawn from a chosen
origin to each atom in the polypeptide structure. Furthermore, the
positions of atoms in a three-dimensional structure may be
represented as fractions of the unit cell (fractional coordinates),
or in spherical polar coordinates.
[0095] Additional information, such as thermal parameters, which
measure the motion of each atom in the structure, chain
identifiers, which identify the particular chain of a multi-chain
protein in which an atom is located, and connectivity information,
which indicates to which atoms a particular atom is bonded, is also
useful for representing a three-dimensional molecular
structure.
[0096] Accordingly, also provided herein is a machine-readable data
storage medium including a data storage material encoded with
machine readable data which, when using a machine programmed with
instructions for using the data, displays a graphical
three-dimensional representation of a mPGES-1 molecule.
[0097] Structure information, typically in the form of the atomic
structure coordinates, can be used in a variety of computational or
computer-based methods to, for example, design, screen for and/or
identify compounds that bind the crystallized polypeptide or a
portion or fragment thereof, or to intelligently design mutants
that have altered biological properties, and the like. Such
modeling includes, but is not limited to, drawing pictures of the
actual structures, building physical models of the actual
structures, and determining the structures of related subunits and
/ligand and subunit/ligand complexes using the coordinates. Such
molecular modeling can utilize known X-ray diffraction molecular
modeling algorithms or molecular modeling software to generate
atomic coordinates corresponding to the three-dimensional structure
of an mPGES-1 molecule.
[0098] The information can be included in an information storage,
manipulation and retrieval system, such as a computer system. Such
a system can include a representation of the three-dimensional
structure of an mPGES-1 molecule of the invention, such as a
monomer, substrate binding domain or trimer. Generally such a
system includes a user interface to view the representation.
[0099] Also provided herein are methods for conducting a
biotechnology business. The methods include identifying one or more
candidate compounds for regulation of interactions of mPGES-1 with
its cognate ligands by a method described herein. The business
method further includes generating a machine-readable medium, or
data signal embodied in a carrier wave, embedded with information
that corresponds to the three-dimensional structural representation
of the candidate compound and providing the medium or data signal
to an end user.
[0100] The following examples are provided to illustrate the
practice of preferred embodiments of the instant invention, and in
no way limit the scope of the invention.
EXAMPLES
[0101] In order to understand the molecular mechanism of the
substrate binding, an "ab initio" structure prediction approach has
been developed in the present study to build a three-dimensional
model of the substrate-binding domain (SBD) of mPGES-1 by making
use of the structural information available for both mPGES-1 and
MGST1 of the MAPEG superfamily. Based on the three-dimensional
model of the SBD, key residues that are crucial for the substrate
binding have been identified through further structural analysis
and molecular docking. Molecular docking is generally defined as
the relative positioning of two or more interacting bodies. Such a
positioning can be done by means of complex algorithms to match
physical properties of the multiple bodies or by a simple procedure
such as visual analysis. Accurate and intuitive docking, with easy
and accessible information of the docking process, is an important
process in the development of pharmaceuticals and novel materials
as well as in understanding the properties of existing systems.
[0102] Site-directed mutagenesis and catalytic activity assays have
been performed to validate the predicted three-dimensional SBD
model of the wild-type mPGES-1 and its mutants. The overall
agreement between the computational and experimental results
demonstrates some important structural features of the SBD of
mPGES-1 and it's binding with the substrates, providing a basis for
structure-based design of compounds that interact with the SBD.
[0103] "Ab initio" Structure Prediction: The sequence alignment
between MGST-1 and mPGES-1 (see FIG. 1) was generated by using
ClusterW with the Blosum scoring function. The best alignment was
selected according to not only the alignment score, but also the
reciprocal position of the conserved residues. These included the
conserved FANPED motif at amino acid positions #44 to #49, VERXXRAH
motif from position #65 to #72 and R110. There was a gap of four
residues from #55 to #58. The total homology is 73%, with the
sequence identity of 38.8%. The membrane-spanning regions were
defined based on the analysis of amino acids distribution and the
homology with MGST1. The locations of substrates PGH2 and GSH in
the SBD of mPGES-1 were thought to be similar to the corresponding
locations of the substrates in the SBD of MGST1 revealed by the
electron density map of MGST1 (Schmidt-Krey et al., EMBO J.,
19:6311-6316; Holm et al., Biochem. Biophys. Acta, 1594:276-285)
Considering the low-resolution quaternary structure of mPGES-1, the
"ab initio" rationale (see FIG. 10) began with the construction of
topological model in which each helix was represented by C-alpha
atoms, according to the structural parameters derived from the
reported two-dimensional and three-dimensional electron projection
maps of mPGES-121 and MGST1 and shown in Table 1 below:
TABLE-US-00001 Helix A B C D Helix center 11.0 .ANG., 9.0 .ANG.,
0.0 .ANG., 19.0 .ANG., (x, y plane) 16.0 .ANG. 2.0 .ANG. 0.0 .ANG.
10.0 .ANG. Tilt angle (.theta.) 27.0.degree.~37.0.degree.
12.0.degree.~20.0.degree. 12.0.degree.~22.0.degree.
18.0.degree.~18.0.degree. Helix-between A C: 19.4 .ANG. B C: 9.2
.ANG. D C: 21.5 .ANG. distance Helix arrangement Anti-clockwise
Membrane thickness 26.0 .ANG. Kink of helix C toward helix A 3.0
.ANG. Kink point to the C-terminal of helix C 11.0 .ANG. Motion
along the membrane normal (z axis) .+-.5.0 .ANG. Relative rotation
of each helix .+-.180.0.degree. Self-rotation of each helix
.+-.180.0.degree. Orientation of hydrophobic residues Toward
membrane
[0104] Here, the considered SBD is composed of alpha-helices A, C,
and D from one monomer and alpha-helix B from another neighboring
monomer. The orientation of each alpha-helix was explored along
three degrees of freedom, including the relative motion along the
normal to the membrane, relative rotation among helices, and the
helical self-rotation. A set of 144784 candidate topological
(C-alpha) structures were generated and subsequently transformed
into the corresponding residues of each helix. A set of criteria
(Table 1) were used to screen the candidate structures and only
1934 candidate structures were kept for further consideration. The
structures of these 1934 candidates were then fully optimized by
performing energy minimization using the Sander module of Amber7.0
program suite. Initially, the loop between alpha-helices C and D
was not considered. The energy minimization was carried out by
using a non-bonded cutoff of 10 .ANG. and conjugate gradient
method, first with fixed backbone for 500 steps and then with
constrained side chains for 300 steps. This was followed by energy
minimization on the whole molecule for 1000 steps. Further energy
minimization was performed after adding the loop between
alpha-helices C and D. The energy minimization was continued until
the root-mean square deviation (RMSD) of the energy gradient was
smaller than 0.001 kcal mol.sup.-1 .ANG..sup.-1. Additional
geometric screening was based on the structural compatibility among
all the helices, as well as the overall deviation of the C-alpha
atoms from the initial positions. This process eventually resulted
in a set of 27 candidate structures (conformations) with some
structural diversity and closely related low energies. These sets
of molecular structures were viewed as the most possible
conformations of the SBD of mPGES-1 and were used in further
molecular docking tests.
[0105] Molecular Docking and Mutational Calculation: The two native
substrates PGH2 and GSH were treated as ligands, and were
separately docked into the aforementioned 27 candidate structures
of the SBD of mPGES-1 by using the AutoDock 3.0.5 program. The
atomic charges used for these two ligands were the electrostatic
potential (ESP)-fitted charges determined by performing
first-principles electronic structure calculations using Gaussian03
program at the HF/6-31G* level. The similar ESP-fitting
calculations based on the first-principles electronic structure
method were used in previous computational studies of other
protein-ligand systems and led to satisfactory binding structures.
The molecular docking was performed with a large population of
randomly sampled ligand conformations and with random molecular
translations using the Lamarkian genetic algorithm (LGA). Through
three types of operations in the LGA method, namely selection,
mutation, and crossover, the substrate-enzyme matching quality was
monitored and improved. On each docking site, the ligand
conformation was searched by using the Solis and Wets local search
method in order to sample all the possible ligand conformations.
Among a series of docking parameters, the size of the grid, in
which both the enzyme and the ligand were embedded, was set to be
60 .ANG..times.60 .ANG..times.60 .ANG. along the x, y, and z
directions. This size of grid is large enough to cover all the
protein atoms near the docking site, and is also sufficient for
calculating the long-range electrostatic interactions between the
enzyme and ligand molecules. All the complex candidates were
evaluated and ranked in terms of the binding free energies by using
the standard energy score function implemented in the docking
program and the geometric matching quality. The best complex
candidate was selected from the docked structures according to the
best geometric matching and the low binding free energy (high
binding affinity). As the enzyme structure was kept rigid in the
above docking process, the structure of this selected complex
candidate was further refined through the energy minimization using
the aforementioned Amber7.0 program, leading to the construction of
the final complex structure.
[0106] Residue-based analysis was carried out for the obtained
complex structure. Critical atomic contacts between the substrates
and the enzyme were identified and the identified crucial residues
binding with PGH2 include Q36, R110, T114, Y130, and Q134. In order
to estimate individual contributions from these residues to the
binding affinity with PGH2 and to know their possible role in the
binding with the second substrate GSH, the substrate-bound SBD
structures of five mPGES-1 mutants was further examined: Q36E,
R110T, T114V, Y130I, and Q134E. The initial SBD structures of these
mutants were generated based on the finally refined SBD structure
of the wild-type by using the InsightII program (version 2002,
Accelrys, San Diego, Calif.). The initial SBD structures of the
substrate-bound mPGES-1 mutants were energy-minimized by using the
same method as used for the substrate-bound wild-type mPGES-1. The
substrate binding free energy (AG) with each mutant was calculated
in the same way as we did for the binding with the wild-type
enzyme. All the computations were performed on a supercomputer
(Superdome) at University of Kentucky Center for Computational
Sciences and on SGI Fuel workstations and a 34-processors IBM x335
Linux cluster.
[0107] Vector, Membrane, and Cloning of mPGES-1: PQE40 expression
vector, E. coli M15 and QIAprep Spin Plasmid miniprep Kit were from
QIAgene. Restriction endonucleases were from New England BioLabs.
The pfu polymerase was from Stratagene. Nickel-HRP was from
Kirkegaard & Perry Laboratories (Gaithersburg, Mass.),
polyvinylidene fluoride (PVDF) membrane was from Millipore Corp.
ECL western blotting detection system RPN 2132 was from Amersham
Life science. Oligonucleotide primers were synthesized by MWG
biotech. PGH2 and PGE2 were purchased from Cayman chemicals. Other
chemicals were from Sigma. The sequence of mPGES-1 was extracted
from Genebank (access No. AF27740). The specific oligonucleotide
primers to full length of mPGES-1 were synthesized to incorporate
restriction sites (BamHI and HindIII) into the 5' and 3' ends of
the products. PCR was performed with 2 units Taq polymerase, 1
.mu.l human placenta cDNA library. The PCR product was subcloned
into E. coli expression vector plasmid PQE40 at BamH I and Hind III
sites, which would express histidine X6 tagged mPGES-1. The ligated
plasmids were transformed into XLI-Blue competent cells with the
insertion confirmed by DNA sequencing.
[0108] Site-Directed Mutagenesis of mPGES-1: The internal primers
were designed to contain sense and antisense mutagenic factors with
mismatched codons in the wild-type sequence. All the mutations of
mPGES-1 cDNA were performed by quick change site-directed
mutagenesis method. The sequences of oligonucleotides used for
mutagenesis were:
Q36E:
TABLE-US-00002 [0109] (SEQ ID NO:1)
5'-GTGGCCATCATCACGGGCGAAGTGAGGCTGCGGAAGAAG, and (SEQ ID NO:2)
5'-CTTCTTCCGCAGCCTCACTTCGCCCGTGATGATGGCCAC; R110T: (SEQ ID NO:3)
5'-CTGGTCTTCCTCGTGGGCACTGTGGCACACACCGTGGCC, and (SEQ ID NO:4)
5'-GGCCACGGTGTGTGCCACAGTGCCCACGAGGAAGACCAG; T114V: (SEQ ID NO:5)
5'-GTGGGCCGTGTGGCACACGTCGTGGCCTACCTGGGGAAG, and (SEQ ID NO:6)
5'-CTTCCCCAGGTAGGCCACGACGTGTGCCACACGGCCCAC; Y130I: (SEQ ID NO:7)
5'-CCCATCCGCTCCGTGACCATCACCCTGGCCCAGCTCCCC, and (SEQ ID NO:8)
5'-GGGGAGCTGGGCCAGGGTGATGGTCACGGAGCGGATGGG; Q134E: (SEQ ID NO:9)
5'-GTGACCTACACCCTGGCCGAGCTCCCCTGCGCCTCCATG, and (SEQ ID NO:10)
5'-CATGGAGGCGCAGGGGAGCTCGGCCAGGGTGTAGGTCAC;
where the underlines indicate the bases that were changed. Pfu DNA
polymerase was used for PCR. The PCR products were treated with
DpnI endonuclease to digest the parental DNA template. All the
mutant plasmids were transformed into XLI-Blue cells to amplify
DNA. The DNA sequences of mutants were confirmed by sequencing.
[0110] Expression and Preparation for the Membrane Fraction of
mPGES-1 and its Mutants in E. coli: The wild-type mPGES-1 and its
mutant plasmids from XLI-Blue were transformed into M15 E. coli
cells. Cells were grown in 500 ml TB media containing 100 .mu.g/ml
ampicillin and 25 .mu.g/ml kanamycin at 37.degree. C. with shaking
at 270 rpm until OD reached 0.8. IPTG was added to a final
concentration of 2 mM and cells were allowed to grow for additional
3 hours at 37.degree. C. Cells were then harvested by
centrifugation at 5000 g for 15 min at 4.degree. C. The cell pellet
was re-suspended in 15 mM Tris-HCl pH 8.0 containing 0.25 M
sucrose, 0.1 mM EDTA and 1 mM reduced form glutathione. The cells
were broken by sonication, and then the cell lysate was cleared by
centrifugation at 12,500 g for 10 min. The supernatant then was
centrifugated at 250,000 g 4.degree. C. for 1 hour and the membrane
pellet were re-suspended in PPGEG buffer (10 mM potassium
phosphate, pH 7.0, 20% glycerol, 0.1 mM EDTA and 1 mM reduced form
glutathione). Total protein concentration of the membrane fraction
was determined by coomassie protein assay according to the
manufacture's instruction (Bio-Rad) with BSA as a standard.
[0111] SDS-PAGE and Western Blotting: The E. coli membranes (50
.mu.g) expressing the His-tagged wild-type and mutant mPGES-1 were
subjected to SDS-PAGE on 15% polyacrylamide gel. The proteins were
then electrophoretically transferred onto PVDF membranes. The
membrane was blocked with 5% nonfat milk in TBS (30 mM Tris HCl, pH
7.4 containing 120 mM NaCl) at room temperature for 1 hour. After
incubation 2 hours at room temperature with Nickel-HRP (1:500) in
5% nonfat milk in TBS, the membrane was washed 3 times with TBS
containing 0.1% Tween 20. The immunoreactive bands were detected
with ECL plus western blotting detection system.
[0112] Activity Assay for Wild-type mPGES-1 and Its Mutants: Assays
for mPGES-1 activity were performed on ice in 1.5 ml microfuge
tubes using PGH2 as substrate. The reaction mixture (100 .mu.l)
contained: 100 mM sodium phosphate, pH 7.2, 2.5 mM GSH and enzyme
preparation. The reaction was initiated by the addition of 15 .mu.M
PGH2 from 20-fold concentrated stock solution in dry ethanol. After
8 min of incubation on ice, the reaction was quenched by the
addition of 100 .mu.l (2 mg/ml) SnCl2 which rapidly reduced
un-reacted PGH2 to PGF2.alpha.. The non-enzymatic conversion of
PGH2 to PGE2 was performed using PPGEG buffer devoid of enzyme. The
reaction contents were 1:2500 diluted, from which 50 .mu.l aliquot
was used for quantification of PDE2 concentration by EIA assay. The
mPGES-1 activity was calculated using enzymatic conversion of PGH2
to PGE2 from total conversion subtracted by non-enzymatic
conversion. When the saturation kinetics for PGH2 was determined,
the activity was assayed with a fixed concentration of 2.5 mM GSH
and 1-500 .mu.M PGH2. The K.sub.M values of wild-type mPGES-1 and
its mutants were calculated by using the GraphPad Prism 4.01
program.
[0113] Results: Structural Models of the SBD of mPGES-1: The amino
acid sequence alignment of mPGES-1 with MGST1 (FIG. 1) shows that
four regions with high homology (>70%) can be assigned to four
alpha-helices. These are alpha-helix A from sequence position #11
to #38, alpha-helix B from #78 to #93, alpha-helix C from #96 to
#114, and alpha-helix D from #126 to #147. The longest loop between
alpha-helix A and alpha-helix B contains typically conserved
motifs. According to the geometric parameters used for the
alpha-helices (see Table 1, supra), the explored 144784
conformations derived from the initial topological model are
screened down to 1934 candidate conformations. After the energy
minimizations using the Sander module of Amber7.0 program, these
1934 candidates were clustered into four groups as shown in FIG. 2.
The 1232 candidates in the first group have positive energies,
indicating that these 1232 candidate conformations are
energetically unfavorable and should be excluded. The energies
calculated for the other groups of candidates are negative and
become lower and lower from group II to group IV (see FIG. 2),
showing the significant improvement of the positions of the side
chains. This funnel-like adaptation of the four alpha-helices
packing clearly shows both the energetic and geometric aspects
dominating the formation of the final reasonable conformations of
mPGES-1. Such folding-mimic process (see FIG. 10) also helps to
reduce the redundancy of the helix orientations. More strict
geometric checking and evaluation of the root-mean-square-deviation
(RMSD) of the C-alpha positions from those in the initial
topological model help us obtain eventual 27 best candidate
conformations selected from group IV (see FIG. 2). Although some of
the other candidate structures also had small RMSD values and lower
energies, those candidate structures were not selected because the
helix packing was not as good as the selected 27 ones. Further, the
helix packing was re-examined more strictly according to the
geometric criteria (see Table 1, supra) and was finely tuned for
the selected 27 candidates. Each of the finely tuned 27 candidate
structures was energy-minimized again by using the Sander module of
Amber7.0 program until the energy gradient criterion of 0.001 kcal
mol.sup.-1 .ANG..sup.-1 was achieved. The finally energy-minimized
27 candidate conformations with low energies and small RMSD values
(FIG. 3) can be considered as the most possible conformations of
the SBD of mPGES-1.
[0114] Complex Model for mPGES-1 Binding with PGH2 and GSH: The
first test on the 27 structural models of the SBD of mPGES-1 was
performed for their binding with substrates PGH2 and GSH, through
molecular docking using both the binding site searching and
interaction energy scoring. Each of the 27 structures was used to
perform molecular docking, with PGH2 and GSH separately. The
calculated binding free energies of PGH2 with the SBD of mPGES-1
range from -4.1 to -8.3 kcal/mol. The corresponding values of the
dissociation constant (K.sub.d) fall between 995 .mu.M to 0.768
.mu.M. The range of predicted K.sub.d values covers the reported
experimental values (.about.28, .about.14, and .about.160 .mu.M) of
the Michaelis-Menten constant (K.sub.M). We note that
K.sub.d.noteq.K.sub.M in theory. Nevertheless,
K.sub.d.apprxeq.K.sub.M under the widely used rapid-equilibration
assumption which assumes that the dissociation of the
enzyme-substrate complex is much faster than the corresponding
catalytic reaction. The catalytic reaction is characterized by the
catalytic rate constant (k.sub.cat). Based on the reported low
k.sub.cat values (1.8 to 50 S.sup.-1) for mPGES-1,
K.sub.d.apprxeq.K.sub.M in subsequent calculations and discussions.
The finally selected complex model of mPGES-1 binding with both
PGH2 and GSH substrates was the most satisfactory one with optimal
geometric matching (see FIG. 4A) compared to the other complex
candidates. The binding free energy (AG) calculated for the final
complex model is -7.8 kcal/mol for PGH2 and -6.0 kcal/mol for GSH,
respectively. Assuming K.sub.d.apprxeq.K.sub.M, the energetic
results calculated for the final complex model predict a K.sub.M
value of 2.1 .mu.M for PGH2 and a K.sub.M value of 41.3 .mu.M for
GSH.
[0115] Based on the predicted complex model shown in FIG. 4B,
substrate PGH2 stays in a pocket formed by alpha-helices A, C, and
D, with the two tails of PGH2 buried deeply. PGH2 has contacts with
both hydrophilic and hydrophobic residues of mPGES-1. The most
important interactions are around the carboxyl group on one tail of
PGH2, which is surrounded by the polar side chain of Q36,
positively charged side chain of R110, and side chain of T114 from
alpha-helix C. The binding of these residues with PGH2 is
associated with a network of electrostatic and hydrogen bonding
interactions. Such an interacting mode is consistent with the
reported experimental finding that R110S mutant of mPGES-1
completely lost the catalytic activity. The hydroxyl group on the
other tail of PGH2 interacts with side chain of Q134 through
possible hydrogen bonding, and this hydrophobic tail is surrounded
by side chains of V29, V30, I33, and V37, further strengthening the
binding affinity of PGH2 with mPGES-1. As seen in the complex
model, the two oxygen atoms forming the peroxy bridge of PGH2 also
interact with the --SH group of GSH through hydrogen bonding. The
head of the PGH2 molecule is close to the aromatic side chain of
Y130 and is covered by hydrophobic part of the side chain of
K120.
[0116] For the binding of GSH with the SBD of mPGES-1, as shown in
FIG. 4C, GSH is bound in a site nearby PGH2 under the loop between
alpha-helices C and D. Compared to the location of PGH2, GSH is
closer to surface of the protein. Based upon this model, another
alpha-helix C in a neighboring monomer could also be involved in
the binding with GSH. The molecular docking with GSH was also
guided by the insights obtained from the reported two-dimensional
and three-dimensional electro-density maps of mPGES-1 and MGST1.
Useful features of the GSH binding still can be derived from the
current model. As shown in FIG. 4C, GSH is surrounded by Y80, L118,
K120, L121, P124, R126, and Y130, and it is close to PGH2. Besides
the thiol (--SH) group of GSH interacts with PGH2, the carboxyl
group on the Gly-end of GSH interacts with positively charged side
chain of R126. Another carboxyl group on the gamma-Glu-end of GSH
points toward the backbone of K120 and L121. The packing of the
--SH group of GSH and the head of PGH2 with the aromatic side chain
of Y130 implies a possibly important role of Y130 in the catalytic
function of mPGES-1.
[0117] PGH2 Binding with mPGES-1 Mutants: Based on the modeled SBD
structure of mPGES-1 and the modeled binding structures with
substrates, five key residues (i.e. Q36, R110, T114, Y130, and
Q134) involved in the PGH2-binding site were selected for
mutational studies in order to further test the predicted SBD model
of mPGES-1. According to the three-dimensional model of the
substrate binding discussed above, the enzyme binding with
substrate PGH2 should be weakened by such mutations as Q36E, R110T,
T114V, Y130I, and Q134E. The binding affinities were estimated for
the mutants of mPGES-1 by using the same method as used for the
wild-type enzyme. The calculated results are summarized in Table 2
in comparison with available experimental data:
TABLE-US-00003 Calculated Experimental binding K.sub.M (.mu.M)
.DELTA.G This Previously Enzyme (kcal/mol) K.sub.d (.mu.M) work
reported Wild-type -7.8 2.1 (.sup.b) 130 14 to 160 (.sup.a) Q36E
-3.8 1600 ~1610 Q134E -4.7 359 ~734 The experimental K.sub.M values
reported previously by other groups (.sup.a) are 28 .mu.M), 14
.mu.M, and 160 .mu.M. The calculated k.sub.d value (.sup.b) is
close to the range of the experimental K.sub.M values (14 to 160
.mu.M).
[0118] Membrane Expression of mPGES-1 and Its Mutants: Based on the
information of the structure prediction and modeling on substrate
binding, five residues in the PGH2-binding site of mPGES-1 were
selected for further site-directed mutagenesis studies. The
substitutions for these five residues are Q36E, R110T, T114V,
Y130I, and Q134E. The wild-type mPGES-1 was cloned from human
placenta cDNA library by PCR techniques using specific sense and
anti-sense primers of mPGES-1. The wild-type and the five mutants
of mPGES-1 were expressed in M15 E. coli cells. As the membrane
proteins are very toxic to the host E. coli, a special strategy was
used to produce sufficient amount of expression in order to favor
the next activity assay. The best condition for expression was
selected as 3 hours at 37.degree. C. The membrane fractions were
further analyzed by western blotting using Ni-HRP as a detection
system, which is more sensitive and accurate than the traditional
analysis system of the primary and secondary antibody. The results
demonstrate that all the five mutants were expressed at a level
comparable with that of the wild-type enzyme (see FIG. 5).
[0119] Enzymatic Activity and Kinetic Data: The wild-type and the
mutants of mPGES-1 were assayed for the enzymatic activity in the
presence of PGH2 and GSH as substrates and the results are shown in
FIG. 6. The R110T mutation was designed to test mainly for its
electrostatic and hydrogen bonding interactions with the carboxyl
group of PGH2. This mutant retained only 17.8% catalytic activity
of the wild-type, not totally abrogated as reported by Murakami et
al. (J. Biol. Chem., 2000, 275:32783-32792). The T114V mutant
showed 21.3% activity of the wild-type mPGES-1, which is consistent
with the computational prediction that the hydroxyl group of T114
side chain is involved in hydrogen bonding with PGH2. The Y130I
mutant lost most of the enzymatic activity, indicating that this
residue cannot tolerate any amino acid change. This suggests that
the role of Y130 in the reaction of PGH2 catalyzed by mPGES-1 is
crucial. Q36E and Q134E mutants kept about 40%-50% catalytic
activity of the wild-type (FIG. 6), indicating that these two
residues (Q36 and Q134) are not as important as the other three
residues (R110, T114, and Y130) for the catalytic reaction.
[0120] The experimental results are listed in Table 2 and depicted
in FIGS. 6 and 7 for comparison with the computational predictions.
As seen in FIG. 6, each of the tested mPGES-1 mutants demonstrated
a lower catalytic activity compared to the wild-type, which is
qualitatively consistent with the predicted enzyme-substrate
binding model. Quantitatively, the experimental kinetic constant
K.sub.M was determined only for the wild-type mPGES-1 and the Q36E
and Q134E mutants, but the catalytic activity of the R110T, T114V,
and Y130I mutants is too low for the measurement of kinetic
constants. The correlation between the calculated K.sub.d and the
measured K.sub.M for these two mutants is represented in FIG. 8.
For the wild-type mPGES-1, the experimental K.sub.M value of 130
.mu.M is comparable to the K.sub.M values reported by Tanikawa et
al. (28 .mu.M) (Biochem. Biophys. Res. Com., 2002, 291:884-889),
Ouellet et al. (14 .mu.M) (Protein Expr. Puri., 2002, 26:489-495),
and Thoren et al. (160 .mu.M) (J. Biol. Chem., 2003,
278:22199-22209). The calculated K.sub.M value of 2.1 .mu.M is
acceptable, although it is slightly smaller than the experimental
range (14 to 160 .mu.M). The binding constant (K.sub.d) values
predicted for the Q36E and Q134E mutants are in agreement with the
experimental K.sub.M values, although the errors of the
experimental K.sub.M values determined for these two mutants are
expected to be very large because the concentrations of PGH2 used
in the experiments (.ltoreq.500 .mu.M) are not sufficiently high
due to the limitation of the solubility of PGH2. The overall
qualitative agreement of the calculated results with the
experimental data further supports the predicted three-dimensional
model of the substrate-enzyme binding as provided herein.
[0121] Structural determination of membrane-spanning proteins is
still exceedingly difficult by experimental methods such as X-ray
diffraction and NMR. As a stimulating drug target, detailed
information about the mPGES-1 structure and the relationship with
its functions are needed. In the present study, this need is
satisfied by performing computational three-dimensional structure
predictions of the SBD of mPGES-1 and it's binding with the
substrates PGH2 and GSH, followed by wet experimental tests on the
enzyme-substrate binding model predicted at atomic level. The
three-dimensional model reveals key amino acid residues, including
Q36, R110, T114, Y130, and Q134, involved in the PGH2-binding site.
This first three-dimensional model provides a mechanism for
designing agents that modulate the activity of mPGES-1 by
interacting with the SBD described herein.
[0122] The current results (see e.g., FIGS. 6 and 7 and Table 2)
obtained from the site-directed mutagenesis and enzymatic activity
assay have identified two remarkable features of the predicted
mPGES-1 binding with the substrates. One is the relative positions
of the peroxy head of PGH2 to the --SH group of GSH in the binding
site around residue Y130 of mPGES-1, reflecting the distinct role
of Y130 residue. Such a mode of the intermolecular interaction
clearly explains why the catalytic function of mPGES-1 is
GSH-dependent as observed in previous characterization studies on
this enzyme. The obtained binding mode also indicates that the
mPGES-1-catalyzed reaction of PGH2 can be initialized by the
electrophilic attack of the --SH group of GSH at the peroxy oxygen
of PGH2. Also provided herein are the contacts between the carboxyl
tail of PGH2 and residues R110, T114, and Q36 of mPGES-1.
Intermolecular interactions on this subsite reveal the role of
residues R110, T114, and Q36 in the binding of mPGSE-1 with PGH2.
R110 is conserved not only strictly for the MGST1 subfamily, but
also for the whole superfamily of MAPEG (Jakobsson, et al., Protein
Sci., 1999, 8:689-692; Jakobsson et al., Am. J. Respir. Crit. Care
Med., 1996, 161:S20-S24; Ekstrom et al., Biochem. Biophys. Acta,
2003, 1627:79-84) suggesting a similar binding/catalytic role of
this residue for all the members of this superfamily. The hydrogen
bonding between the substrate and the subfamily-conserved residue
T114 indicates a similar role of this residue for the members of
MGST1 subfamily in the binding with the substrate. The
indispensable role of the substitutable conserved Y130 demonstrates
why mPGES-1 is specific for the reaction of PGH2. Amino acid
residues #36 and #134 are not conserved even for the MGST1
subfamily, which is consistent with our observation that the
catalytic activity of mPGES-1 did not dramatically decrease when
these two residues were mutated.
[0123] Accordingly, in one embodiment, the present combined
computational modeling and wet experimental tests have led to
establishment of a three-dimensional model of the SBD of mPGES-1
and the identification of how mPGES-1 binds with various substrates
at the atomic level. Based on the three-dimensional model, further
computational modeling and binding free energy calculations were
performed to evaluate the substrate binding with Q36E, R110T,
T114V, Y130I, and Q134E mutants of mPGES-1, followed by the
site-directed mutagenesis and catalytic activity tests. The overall
agreement between the calculated and experimental results
demonstrates that the predicted three-dimensional model will be
valuable in future rational design of potent inhibitors of mPGES-1
for novel inflammation-related therapeutics.
[0124] In another embodiment, the present studies also provide
three-dimensional models of the mPGES-1 trimer. The computational
modeling of the mPGES-1 trimer models was based on the use of the
previously constructed three-dimensional model of the SBD (see data
provided supra) and the use of the X-ray crystal structure of
cytochrome c protein.
[0125] The principle behind homology modeling is the assumption
that structure is more highly conserved than sequence. This assumes
an evolutionary process called divergent evolution. Thus, the
deduced structure of the MGST-1 trimer observed in the
three-dimensional projection map (Schmidt-Krey et al., EMBO J.,
2000, 19:6311-6316) shows a striking similarity to subunit 1 of
both bacterial and bovine cytochrome c oxidase (Iwata et al.,
Nature, 1995, 376:660-669; Tsukihara et al., Science, 1996,
272:1136-1144), in spite of the fact that there is neither any
shared functional property nor any sequence similarity between
MGST1 and subunit 1 of cytochrome c oxidase. In addition, the
sequence of the mPGES-1 shares more than 73% of identity with MGST1
sequence confirming thus, that the topology of the mPGES-1 is
similar to MGST1 structure. Accordingly, in the present studies the
structural information previously deduced for cytochrome c oxidase
was used to extrapolate information required to build
three-dimensional models of the mPGES-1 trimer.
[0126] As previously noted, the present studies have provided a
three-dimensional model of the SBD of mPGST-1. This model was
superimposed to the subunit 1 of the template (the X-ray crystal
structure of cytochrome c oxidase, i.e. 1OCC.pdb). The same
three-dimensional model of the SBD of mPGST-1 was also superimposed
to the subunits 2 and 3 of the template. Thus, the constructed
mPGES-1 trimer model has three equivalent SBDs with an approximate
C3-fold symmetry. Depicted in FIG. 11 are different views of the
constructed three-dimensional model #1 (FIG. 11, panel (a), panel
(b) and panel (c)) of the mPGES-1 trimer complexed with GSH and
PGH2.
[0127] three-dimensional model #2 (see FIG. 13) is a pure homology
model modeled based on the template (the X-ray crystal structure of
cytochrome c oxidase, i.e. 1OCC.pdb). The homology model of the
mPGES-1 trimer was constructed using the Homology module of
InsightII program, based on the individual sequence/template
alignments (see FIG. 12). The alpha-helices are underlined in the
sequence alignment of mPGES-1 with the cytochrome c template shown
in FIG. 12. The refined final alignments based on the secondary
structure of each unit were used for constructing homology models
of human mPGES-1 using MODELER module of InsightII program. MODELER
is a well-known comparative modeling methodology, which generates a
refined three-dimensional homology model of a protein sequence
automatically and rapidly, based on a given sequence alignment to a
known three-dimensional protein structure.
[0128] The obtained initial three-dimensional models of the mPGES-1
trimer were refined further through carefully performing the
energy-minimizations and constrained molecular dynamics (MD)
simulations. FIG. 13 shows the obtained three-dimensional model #2
of the mPGES-1 trimer complexed with an inhibitor (i.e. MK-886
reported in literature) in each SBD.
[0129] The examples set forth above are provided to give those of
ordinary skill in the art a complete disclosure and description of
how to make and use the embodiments of the devices, systems and
methods of the invention, and are not intended to limit the scope
of what the inventors regard as their invention. Modifications of
the above-described modes for carrying out the invention that are
obvious to persons of skill in the art are intended to be within
the scope of the following claims. All patents and publications
mentioned in the specification are indicative of the levels of
skill of those skilled in the art to which the invention pertains.
All references cited in this disclosure are incorporated by
reference to the same extent as if each reference had been
incorporated by reference in its entirety individually.
[0130] In addition, it is understood that the terminology used
herein is for the purpose of describing particular embodiments
only, and is not intended to be limiting. As used in this
specification and the appended claims, the singular forms "a,"
"an," and "the" include plural referents unless the content clearly
dictates otherwise. Unless defined otherwise, all technical and
scientific terms used herein have the same meaning as commonly
understood by one of ordinary skill in the art to which the
invention pertains. Although any methods and materials similar or
equivalent to those described herein can be used in the practice
for testing of the invention(s), specific examples of appropriate
materials and methods are described herein.
[0131] A number of embodiments of the invention have been
described. Nevertheless, it will be understood that various
modifications may be made without departing from the spirit and
scope of the invention. Accordingly, other embodiments are within
the scope of the following claims.
Sequence CWU 1
1
13139DNAArtificial SequenceOligonucleotide primer sequence
1gtggccatca tcacgggcga agtgaggctg cggaagaag 39239DNAArtificial
SequenceOligonucleotide primer sequence 2cttcttccgc agcctcactt
cgcccgtgat gatggccac 39339DNAArtificial SequenceOligonucleotide
primer sequence 3ctggtcttcc tcgtgggcac tgtggcacac accgtggcc
39439DNAArtificial SequenceOligonucleotide primer sequence
4ggccacggtg tgtgccacag tgcccacgag gaagaccag 39539DNAArtificial
SequenceOligonucleotide primer sequence 5gtgggccgtg tggcacacgt
cgtggcctac ctggggaag 39639DNAArtificial SequenceOligonucleotide
primer sequence 6cttccccagg taggccacga cgtgtgccac acggcccac
39739DNAArtificial SequenceOligonucleotide primer sequence
7cccatccgct ccgtgaccat caccctggcc cagctcccc 39839DNAArtificial
SequenceOligonucleotide primer sequence 8ggggagctgg gccagggtga
tggtcacgga gcggatggg 39939DNAArtificial SequenceOligonucleotide
primer sequence 9gtgacctaca ccctggccga gctcccctgc gcctccatg
391039DNAArtificial SequenceOligonucleotide primer sequence
10catggaggcg caggggagct cggccagggt gtaggtcac 3911173PRTTarsius
bancanus 11Met Phe Ile Asn Arg Trp Leu Phe Ser Thr Asn His Lys Asp
Ile Gly1 5 10 15Thr Leu Tyr Leu Leu Phe Gly Ala Trp Ala Gly Met Val
Gly Thr Ala 20 25 30Leu Ser Leu Leu Ile Arg Ala Glu Leu Gly Gln Pro
Gly Thr Leu Leu 35 40 45Gly Asp Asp Gln Ile Tyr Asn Val Val Val Thr
Ala His Ala Phe Val 50 55 60Met Ile Phe Phe Met Val Met Pro Ile Met
Ile Gly Gly Phe Gly Asn65 70 75 80Trp Leu Val Pro Leu Met Ile Gly
Ala Pro Asp Met Ala Phe Pro Arg 85 90 95Met Asn Asn Met Ser Phe Trp
Leu Leu Pro Pro Ser Phe Leu Leu Leu 100 105 110Ala Ser Ser Met Val
Glu Ala Gly Ala Gly Thr Gly Trp Thr Val Tyr 115 120 125Pro Pro Leu
Ala Gly Asn Leu Ala His Ala Gly Ala Ser Val Asp Leu 130 135 140Thr
Ile Phe Ser Leu His Leu Ala Gly Val Ser Ser Ile Leu Gly Ala145 150
155 160Ile Asn Phe Ile Thr Thr Ile Ile Asn Met Lys Pro Pro 165
17012152PRTHomo Sapiens 12Met Pro Ala His Ser Leu Val Met Ser Ser
Pro Ala Leu Pro Ala Phe1 5 10 15Leu Leu Cys Ser Thr Leu Leu Val Ile
Lys Met Tyr Val Val Ala Ile 20 25 30Ile Thr Gly Gln Val Arg Leu Arg
Lys Lys Ala Phe Ala Asn Pro Glu 35 40 45Asp Ala Leu Arg His Gly Gly
Pro Gln Tyr Cys Arg Ser Asp Pro Asp 50 55 60Val Glu Arg Cys Leu Arg
Ala His Arg Asn Asp Met Glu Thr Ile Tyr65 70 75 80Pro Phe Leu Phe
Leu Gly Phe Val Tyr Ser Phe Leu Gly Pro Asn Pro 85 90 95Phe Val Ala
Trp Met His Phe Leu Val Phe Leu Val Gly Arg Val Ala 100 105 110His
Thr Val Ala Tyr Leu Gly Lys Leu Arg Ala Pro Ile Arg Ser Val 115 120
125Thr Tyr Thr Leu Ala Gln Leu Pro Cys Ala Ser Met Ala Leu Gln Ile
130 135 140Leu Trp Glu Ala Ala Arg His Leu145 15013155PRTHomo
Sapiens 13Met Val Asp Leu Thr Gln Val Met Asp Asp Glu Val Phe Met
Ala Phe1 5 10 15Ala Ser Tyr Ala Thr Ile Ile Leu Ser Lys Met Met Leu
Met Ser Thr 20 25 30Ala Thr Ala Phe Tyr Arg Leu Thr Arg Lys Val Phe
Ala Asn Pro Glu 35 40 45Asp Cys Val Ala Phe Gly Lys Gly Glu Asn Ala
Lys Lys Tyr Leu Arg 50 55 60Thr Asp Asp Arg Val Glu Arg Val Arg Lys
Ala His Leu Asn Asp Leu65 70 75 80Glu Asn Ile Ile Pro Phe Leu Gly
Ile Gly Leu Leu Tyr Ser Leu Ser 85 90 95Gly Pro Asp Pro Ser Thr Ala
Ile Leu His Phe Arg Leu Phe Val Gly 100 105 110Ala Arg Ile Tyr His
Thr Ile Ala Tyr Leu Thr Pro Leu Pro Gln Pro 115 120 125Asn Arg Ala
Leu Ser Phe Phe Val Gly Tyr Gly Val Thr Leu Ser Met 130 135 140Ala
Tyr Arg Leu Leu Lys Ser Lys Leu Tyr Leu145 150 155
* * * * *