Literature DB >> 21360606

Challenges and advances in computational docking: 2009 in review.

Elizabeth Yuriev1, Mark Agostino, Paul A Ramsland.   

Abstract

Docking is a computational technique that places a small molecule (ligand) in the binding site of its macromolecular target (receptor) and estimates its binding affinity. This review addresses methodological developments that have occurred in the docking field in 2009, with a particular focus on the more difficult, and sometimes controversial, aspects of this promising computational discipline. These developments aim to address the main challenges of docking: receptor representation (such aspects as structural waters, side chain protonation, and, most of all, flexibility (from side chain rotation to domain movement)), ligand representation (protonation, tautomerism and stereoisomerism, and the effect of input conformation), as well as accounting for solvation and entropy of binding. This review is strongly focused on docking advances in the context of drug design, specifically in virtual screening and fragment-based drug design.
Copyright © 2010 John Wiley & Sons, Ltd.

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Year:  2010        PMID: 21360606     DOI: 10.1002/jmr.1077

Source DB:  PubMed          Journal:  J Mol Recognit        ISSN: 0952-3499            Impact factor:   2.137


  58 in total

1.  Discrete molecular dynamics distinguishes nativelike binding poses from decoys in difficult targets.

Authors:  Elizabeth A Proctor; Shuangye Yin; Alexander Tropsha; Nikolay V Dokholyan
Journal:  Biophys J       Date:  2012-01-03       Impact factor: 4.033

Review 2.  From laptop to benchtop to bedside: structure-based drug design on protein targets.

Authors:  Lu Chen; John K Morrow; Hoang T Tran; Sharangdhar S Phatak; Lei Du-Cuny; Shuxing Zhang
Journal:  Curr Pharm Des       Date:  2012       Impact factor: 3.116

3.  Improving ligand 3D shape similarity-based pose prediction with a continuum solvent model.

Authors:  Ashutosh Kumar; Kam Y J Zhang
Journal:  J Comput Aided Mol Des       Date:  2019-08-28       Impact factor: 3.686

4.  Assessing protein-ligand binding modes with computational tools: the case of PDE4B.

Authors:  Gülşah Çifci; Viktorya Aviyente; E Demet Akten; Gerald Monard
Journal:  J Comput Aided Mol Des       Date:  2017-05-22       Impact factor: 3.686

5.  Application of binding free energy calculations to prediction of binding modes and affinities of MDM2 and MDMX inhibitors.

Authors:  Hui Sun Lee; Sunhwan Jo; Hyun-Suk Lim; Wonpil Im
Journal:  J Chem Inf Model       Date:  2012-07-06       Impact factor: 4.956

6.  Engineering the Pseudomonas aeruginosa II lectin: designing mutants with changed affinity and specificity.

Authors:  Zdeněk Kříž; Jan Adam; Jana Mrázková; Petros Zotos; Thomais Chatzipavlou; Michaela Wimmerová; Jaroslav Koča
Journal:  J Comput Aided Mol Des       Date:  2014-07-12       Impact factor: 3.686

7.  A pose prediction approach based on ligand 3D shape similarity.

Authors:  Ashutosh Kumar; Kam Y J Zhang
Journal:  J Comput Aided Mol Des       Date:  2016-07-05       Impact factor: 3.686

8.  Rigid Body Energy Minimization on Manifolds for Molecular Docking.

Authors:  Hanieh Mirzaei; Dmitri Beglov; Ioannis Ch Paschalidis; Sandor Vajda; Pirooz Vakili; Dima Kozakov
Journal:  J Chem Theory Comput       Date:  2012-08-21       Impact factor: 6.006

9.  The Search for Herbal Antibiotics: An In-Silico Investigation of Antibacterial Phytochemicals.

Authors:  Mary Snow Setzer; Javad Sharifi-Rad; William N Setzer
Journal:  Antibiotics (Basel)       Date:  2016-09-12

10.  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

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