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PDBsum entry 1lqd
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Contents |
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* Residue conservation analysis
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Enzyme class:
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Chains A, B:
E.C.3.4.21.6
- coagulation factor Xa.
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Reaction:
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Preferential cleavage: Arg-|-Thr and then Arg-|-Ile bonds in prothrombin to form thrombin.
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DOI no:
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J Med Chem
45:2749-2769
(2002)
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PubMed id:
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Design and quantitative structure-activity relationship of 3-amidinobenzyl-1H-indole-2-carboxamides as potent, nonchiral, and selective inhibitors of blood coagulation factor Xa.
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H.Matter,
E.Defossa,
U.Heinelt,
P.M.Blohm,
D.Schneider,
A.Müller,
S.Herok,
H.Schreuder,
A.Liesum,
V.Brachvogel,
P.Lönze,
A.Walser,
F.Al-Obeidi,
P.Wildgoose.
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ABSTRACT
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A series of 138 nonchiral 3-amidinobenzyl-1H-indole-2-carboxamides and analogues
as inhibitors of the blood coagulation enzyme factor Xa (fXa) were designed,
synthesized, and investigated by X-ray structure analysis and 3D quantitative
structure-activity relationship (QSAR) studies (CoMFA, CoMSIA) in order to
identify important protein-ligand interactions responsible for biological
affinity and selectivity. Several compounds from this series are highly potent
and selective inhibitors of this important enzyme linking extrinsic and
intrinsic coagulation pathways. To rationalize biological affinity and to
provide guidelines for further design, all compounds were docked into the factor
Xa binding site. Those docking studies were based on X-ray structures of factor
Xa in complex with literature-known inhibitors. It was possible to validate
those binding modes by four X-ray crystal structures of representative ligands
in factor Xa, while one ligand was additionally crystallized in trypsin to
rationalize requirements for selective factor Xa inhibition. The 3D-QSAR models
based on a superposition rule derived from these docking studies were validated
using conventional and cross-validated r(2) values using the leave-one-out
method and repeated analyses using two randomly chosen cross-validation groups
plus randomization of biological activities. This led to consistent and highly
predictive 3D-QSAR models with good correlation coefficients for both CoMFA and
CoMSIA, which were found to correspond to experimentally determined factor Xa
binding site topology in terms of steric, electrostatic, and hydrophobic
complementarity. Subsets selected as smaller training sets using 2D fingerprints
and maximum dissimilarity methods resulted in 3D-QSAR models with remarkable
correlation coefficients and a high predictive power. The final quantitative SAR
information agrees with all experimental data for the binding topology and thus
provides reasonable activity predictions for novel factor Xa inhibitors.
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Literature references that cite this PDB file's key reference
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PubMed id
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Reference
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S.Genheden,
and
U.Ryde
(2011).
A comparison of different initialization protocols to obtain statistically independent molecular dynamics simulations.
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J Comput Chem,
32,
187-195.
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J.Kongsted,
P.Söderhjelm,
and
U.Ryde
(2009).
How accurate are continuum solvation models for drug-like molecules?
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J Comput Aided Mol Des,
23,
395-409.
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J.Kongsted,
and
U.Ryde
(2009).
An improved method to predict the entropy term with the MM/PBSA approach.
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J Comput Aided Mol Des,
23,
63-71.
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N.Singh,
and
J.M.Briggs
(2008).
Molecular dynamics simulations of Factor Xa: insight into conformational transition of its binding subsites.
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Biopolymers,
89,
1104-1113.
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R.Abel,
T.Young,
R.Farid,
B.J.Berne,
and
R.A.Friesner
(2008).
Role of the active-site solvent in the thermodynamics of factor Xa ligand binding.
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J Am Chem Soc,
130,
2817-2831.
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S.Y.Huang,
and
X.Zou
(2006).
An iterative knowledge-based scoring function to predict protein-ligand interactions: II. Validation of the scoring function.
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J Comput Chem,
27,
1876-1882.
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K.Schärer,
M.Morgenthaler,
R.Paulini,
U.Obst-Sander,
D.W.Banner,
D.Schlatter,
J.Benz,
M.Stihle,
and
F.Diederich
(2005).
Quantification of cation-pi interactions in protein-ligand complexes: crystal-structure analysis of Factor Xa bound to a quaternary ammonium ion ligand.
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Angew Chem Int Ed Engl,
44,
4400-4404.
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PDB code:
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P.W.Swaan,
and
S.Ekins
(2005).
Reengineering the pharmaceutical industry by crash-testing molecules.
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Drug Discov Today,
10,
1191-1200.
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C.A.Kontogiorgis,
and
D.Hadjipavlou-Litina
(2004).
Current trends in quantitative structure activity relationships on FXa inhibitors: evaluation and comparative analysis.
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Med Res Rev,
24,
687-747.
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D.B.Kitchen,
H.Decornez,
J.R.Furr,
and
J.Bajorath
(2004).
Docking and scoring in virtual screening for drug discovery: methods and applications.
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Nat Rev Drug Discov,
3,
935-949.
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C.Oostenbrink,
and
W.F.van Gunsteren
(2003).
Single-step perturbations to calculate free energy differences from unphysical reference states: limits on size, flexibility, and character.
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J Comput Chem,
24,
1730-1739.
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The most recent references are shown first.
Citation data come partly from CiteXplore and partly
from an automated harvesting procedure. Note that this is likely to be
only a partial list as not all journals are covered by
either method. However, we are continually building up the citation data
so more and more references will be included with time.
Where a reference describes a PDB structure, the PDB
code is
shown on the right.
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Links
