Literature DB >> 15529328

The MPSim-Dock hierarchical docking algorithm: application to the eight trypsin inhibitor cocrystals.

Art E Cho1, John A Wendel, Nagarajan Vaidehi, Peter M Kekenes-Huskey, Wely B Floriano, Prabal K Maiti, William A Goddard.   

Abstract

To help improve the accuracy of protein-ligand docking as a useful tool for drug discovery, we developed MPSim-Dock, which ensures a comprehensive sampling of diverse families of ligand conformations in the binding region followed by an enrichment of the good energy scoring families so that the energy scores of the sampled conformations can be reliably used to select the best conformation of the ligand. This combines elements of DOCK4.0 with molecular dynamics (MD) methods available in the software, MPSim. We test here the efficacy of MPSim-Dock to predict the 64 protein-ligand combinations formed by starting with eight trypsin cocrystals, and crossdocking the other seven ligands to each protein conformation. We consider this as a model for how well the method would work for one given target protein structure. Using as a criterion that the structures within 2 kcal/mol of the top scoring include a conformation within a coordinate root mean square (CRMS) of 1 A of the crystal structure, we find that 100% of the 64 cases are predicted correctly. This indicates that MPSim-Dock can be used reliably to identify strongly binding ligands, making it useful for virtual ligand screening.

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Year:  2005        PMID: 15529328     DOI: 10.1002/jcc.20118

Source DB:  PubMed          Journal:  J Comput Chem        ISSN: 0192-8651            Impact factor:   3.376


  15 in total

1.  Importance of accurate charges in molecular docking: quantum mechanical/molecular mechanical (QM/MM) approach.

Authors:  Art E Cho; Victor Guallar; Bruce J Berne; Richard Friesner
Journal:  J Comput Chem       Date:  2005-07-15       Impact factor: 3.376

2.  Unexpected acetylcholinesterase activity of cocaine esterases.

Authors:  Claude J Rogers; Lisa M Eubanks; Tobin J Dickerson; Kim D Janda
Journal:  J Am Chem Soc       Date:  2006-12-06       Impact factor: 15.419

3.  Prediction of the 3D structure and dynamics of human DP G-protein coupled receptor bound to an agonist and an antagonist.

Authors:  Youyong Li; Fangqiang Zhu; Nagarajan Vaidehi; William A Goddard; Felix Sheinerman; Stephan Reiling; Isabelle Morize; Lan Mu; Keith Harris; Ali Ardati; Abdelazize Laoui
Journal:  J Am Chem Soc       Date:  2007-08-11       Impact factor: 15.419

4.  Predicted structures of agonist and antagonist bound complexes of adenosine A3 receptor.

Authors:  Soo-Kyung Kim; Lindsay Riley; Ravinder Abrol; Kenneth A Jacobson; William A Goddard
Journal:  Proteins       Date:  2011-04-12

5.  Prediction of the three-dimensional structure for the rat urotensin II receptor, and comparison of the antagonist binding sites and binding selectivity between human and rat receptors from atomistic simulations.

Authors:  Soo-Kyung Kim; Youyong Li; Changmoon Park; Ravinder Abrol; William A Goddard
Journal:  ChemMedChem       Date:  2010-09-03       Impact factor: 3.466

6.  Structure-based prediction of subtype selectivity of histamine H3 receptor selective antagonists in clinical trials.

Authors:  Soo-Kyung Kim; Peter Fristrup; Ravinder Abrol; William A Goddard
Journal:  J Chem Inf Model       Date:  2011-11-16       Impact factor: 4.956

7.  Predicting glycosaminoglycan surface protein interactions and implications for studying axonal growth.

Authors:  Adam R Griffith; Claude J Rogers; Gregory M Miller; Ravinder Abrol; Linda C Hsieh-Wilson; William A Goddard
Journal:  Proc Natl Acad Sci U S A       Date:  2017-12-11       Impact factor: 11.205

8.  Characterizing and predicting the functional and conformational diversity of seven-transmembrane proteins.

Authors:  Ravinder Abrol; Soo-Kyung Kim; Jenelle K Bray; Adam R Griffith; William A Goddard
Journal:  Methods       Date:  2011-12-17       Impact factor: 3.608

9.  Prediction of the 3-D structure of rat MrgA G protein-coupled receptor and identification of its binding site.

Authors:  Jiyoung Heo; Nagarajan Vaidehi; John Wendel; William A Goddard
Journal:  J Mol Graph Model       Date:  2007-07-14       Impact factor: 2.518

10.  High-performance drug discovery: computational screening by combining docking and molecular dynamics simulations.

Authors:  Noriaki Okimoto; Noriyuki Futatsugi; Hideyoshi Fuji; Atsushi Suenaga; Gentaro Morimoto; Ryoko Yanai; Yousuke Ohno; Tetsu Narumi; Makoto Taiji
Journal:  PLoS Comput Biol       Date:  2009-10-09       Impact factor: 4.475

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