Literature DB >> 20888294

Computer-aided drug-discovery techniques that account for receptor flexibility.

Jacob D Durrant1, J Andrew McCammon.   

Abstract

Protein flexibility plays a critical role in ligand binding to both orthosteric and allosteric sites. We here review some of the computer-aided drug-design techniques currently used to account for protein flexibility, ranging from methods that probe local receptor flexibility in the region of the protein immediately adjacent to the binding site, to those that account for general flexibility in all protein regions.
Copyright © 2010 Elsevier Ltd. All rights reserved.

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Year:  2010        PMID: 20888294      PMCID: PMC3026641          DOI: 10.1016/j.coph.2010.09.001

Source DB:  PubMed          Journal:  Curr Opin Pharmacol        ISSN: 1471-4892            Impact factor:   5.547


  50 in total

1.  Analysis of a data set of paired uncomplexed protein structures: new metrics for side-chain flexibility and model evaluation.

Authors:  S Zhao; D S Goodsell; A J Olson
Journal:  Proteins       Date:  2001-05-15

2.  A method for including protein flexibility in protein-ligand docking: improving tools for database mining and virtual screening.

Authors:  H B Broughton
Journal:  J Mol Graph Model       Date:  2000-06       Impact factor: 2.518

Review 3.  High-throughput docking for lead generation.

Authors:  R Abagyan; M Totrov
Journal:  Curr Opin Chem Biol       Date:  2001-08       Impact factor: 8.822

Review 4.  Implications of protein flexibility for drug discovery.

Authors:  Simon J Teague
Journal:  Nat Rev Drug Discov       Date:  2003-07       Impact factor: 84.694

5.  Protein flexibility in ligand docking and virtual screening to protein kinases.

Authors:  Claudio N Cavasotto; Ruben A Abagyan
Journal:  J Mol Biol       Date:  2004-03-12       Impact factor: 5.469

6.  Rapid protein-ligand docking using soft modes from molecular dynamics simulations to account for protein deformability: binding of FK506 to FKBP.

Authors:  Martin Zacharias
Journal:  Proteins       Date:  2004-03-01

7.  Optimization and computational evaluation of a series of potential active site inhibitors of the V82F/I84V drug-resistant mutant of HIV-1 protease: an application of the relaxed complex method of structure-based drug design.

Authors:  Alexander L Perryman; Jung-Hsin Lin; J Andrew McCammon
Journal:  Chem Biol Drug Des       Date:  2006-05       Impact factor: 2.817

8.  Ensemble docking of multiple protein structures: considering protein structural variations in molecular docking.

Authors:  Sheng-You Huang; Xiaoqin Zou
Journal:  Proteins       Date:  2007-02-01

9.  Ligand docking to proteins with discrete side-chain flexibility.

Authors:  A R Leach
Journal:  J Mol Biol       Date:  1994-01-07       Impact factor: 5.469

10.  Computer-aided identification of Trypanosoma brucei uridine diphosphate galactose 4'-epimerase inhibitors: toward the development of novel therapies for African sleeping sickness.

Authors:  Jacob D Durrant; Michael D Urbaniak; Michael A J Ferguson; J Andrew McCammon
Journal:  J Med Chem       Date:  2010-07-08       Impact factor: 7.446

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  25 in total

Review 1.  Identification of HIV inhibitors guided by free energy perturbation calculations.

Authors:  Orlando Acevedo; Zandrea Ambrose; Patrick T Flaherty; Hadega Aamer; Prashi Jain; Somisetti V Sambasivarao
Journal:  Curr Pharm Des       Date:  2012       Impact factor: 3.116

Review 2.  Computational methods in drug discovery.

Authors:  Gregory Sliwoski; Sandeepkumar Kothiwale; Jens Meiler; Edward W Lowe
Journal:  Pharmacol Rev       Date:  2013-12-31       Impact factor: 25.468

3.  Muscarinic receptors as model targets and antitargets for structure-based ligand discovery.

Authors:  Andrew C Kruse; Dahlia R Weiss; Mario Rossi; Jianxin Hu; Kelly Hu; Katrin Eitel; Peter Gmeiner; Jürgen Wess; Brian K Kobilka; Brian K Shoichet
Journal:  Mol Pharmacol       Date:  2013-07-25       Impact factor: 4.436

4.  Fragment Pose Prediction Using Non-equilibrium Candidate Monte Carlo and Molecular Dynamics Simulations.

Authors:  Nathan M Lim; Meghan Osato; Gregory L Warren; David L Mobley
Journal:  J Chem Theory Comput       Date:  2020-03-27       Impact factor: 6.006

5.  Flexible CDOCKER: Development and application of a pseudo-explicit structure-based docking method within CHARMM.

Authors:  Jessica K Gagnon; Sean M Law; Charles L Brooks
Journal:  J Comput Chem       Date:  2015-12-21       Impact factor: 3.376

Review 6.  Statistical mechanics and molecular dynamics in evaluating thermodynamic properties of biomolecular recognition.

Authors:  Jeff Wereszczynski; J Andrew McCammon
Journal:  Q Rev Biophys       Date:  2011-11-15       Impact factor: 5.318

Review 7.  Modelling three-dimensional protein structures for applications in drug design.

Authors:  Tobias Schmidt; Andreas Bergner; Torsten Schwede
Journal:  Drug Discov Today       Date:  2013-11-08       Impact factor: 7.851

8.  DOCK 6: Impact of new features and current docking performance.

Authors:  William J Allen; Trent E Balius; Sudipto Mukherjee; Scott R Brozell; Demetri T Moustakas; P Therese Lang; David A Case; Irwin D Kuntz; Robert C Rizzo
Journal:  J Comput Chem       Date:  2015-06-05       Impact factor: 3.376

9.  Neural-Network Scoring Functions Identify Structurally Novel Estrogen-Receptor Ligands.

Authors:  Jacob D Durrant; Kathryn E Carlson; Teresa A Martin; Tavina L Offutt; Christopher G Mayne; John A Katzenellenbogen; Rommie E Amaro
Journal:  J Chem Inf Model       Date:  2015-09-04       Impact factor: 4.956

10.  Discovery of Staphylococcus aureus sortase A inhibitors using virtual screening and the relaxed complex scheme.

Authors:  Albert H Chan; Jeff Wereszczynski; Brendan R Amer; Sung Wook Yi; Michael E Jung; J Andrew McCammon; Robert T Clubb
Journal:  Chem Biol Drug Des       Date:  2013-10       Impact factor: 2.817

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