Literature DB >> 16426074

On evaluating molecular-docking methods for pose prediction and enrichment factors.

Hongming Chen1, Paul D Lyne, Fabrizio Giordanetto, Timothy Lovell, Jin Li.   

Abstract

Four of the most well-known, commercially available docking programs, FlexX, GOLD, GLIDE, and ICM, have been examined for their ligand-docking and virtual-screening capabilities. The relative performance of the programs in reproducing the native ligand conformation from starting SMILES strings for 164 high-resolution protein-ligand complexes is presented and compared. Applying only the native scoring functions, the latest versions of these four docking programs were also used to conduct virtual screening for 12 protein targets of therapeutic interest, involving both publicly available structures and AstraZeneca in-house structures. The capability of the four programs to correctly rank-order target-specific active compounds over alternative binders and nonbinders (decoys plus randomly selected compounds) and thereby enrich a small subset of a screening library is compared. Enrichments from the virtual-screening experiments are contrasted with those obtained with alternative 3D shape-matching and 2D similarity database-search methods.

Year:  2006        PMID: 16426074     DOI: 10.1021/ci0503255

Source DB:  PubMed          Journal:  J Chem Inf Model        ISSN: 1549-9596            Impact factor:   4.956


  61 in total

1.  Targeting the dimerization of epidermal growth factor receptors with small-molecule inhibitors.

Authors:  Robert Y C Yang; Katherine S Yang; Linda J Pike; Garland R Marshall
Journal:  Chem Biol Drug Des       Date:  2010-05-04       Impact factor: 2.817

2.  Biochemical and molecular analysis of carboxylesterase-mediated hydrolysis of cocaine and heroin.

Authors:  M J Hatfield; L Tsurkan; J L Hyatt; X Yu; C C Edwards; L D Hicks; R M Wadkins; P M Potter
Journal:  Br J Pharmacol       Date:  2010-08       Impact factor: 8.739

Review 3.  Structural systems biology and multiscale signaling models.

Authors:  Shannon E Telesco; Ravi Radhakrishnan
Journal:  Ann Biomed Eng       Date:  2012-04-27       Impact factor: 3.934

4.  Construction and test of ligand decoy sets using MDock: community structure-activity resource benchmarks for binding mode prediction.

Authors:  Sheng-You Huang; Xiaoqin Zou
Journal:  J Chem Inf Model       Date:  2011-08-03       Impact factor: 4.956

Review 5.  Towards the development of universal, fast and highly accurate docking/scoring methods: a long way to go.

Authors:  N Moitessier; P Englebienne; D Lee; J Lawandi; C R Corbeil
Journal:  Br J Pharmacol       Date:  2007-11-26       Impact factor: 8.739

6.  Differentiation of AmpC beta-lactamase binders vs. decoys using classification kNN QSAR modeling and application of the QSAR classifier to virtual screening.

Authors:  Jui-Hua Hsieh; Xiang S Wang; Denise Teotico; Alexander Golbraikh; Alexander Tropsha
Journal:  J Comput Aided Mol Des       Date:  2008-03-13       Impact factor: 3.686

7.  Evaluating docking programs: keeping the playing field level.

Authors:  John W Liebeschuetz
Journal:  J Comput Aided Mol Des       Date:  2008-01-15       Impact factor: 3.686

Review 8.  Evaluation of the performance of 3D virtual screening protocols: RMSD comparisons, enrichment assessments, and decoy selection--what can we learn from earlier mistakes?

Authors:  Johannes Kirchmair; Patrick Markt; Simona Distinto; Gerhard Wolber; Thierry Langer
Journal:  J Comput Aided Mol Des       Date:  2008-01-15       Impact factor: 3.686

9.  Optimization of CAMD techniques 3. Virtual screening enrichment studies: a help or hindrance in tool selection?

Authors:  Andrew C Good; Tudor I Oprea
Journal:  J Comput Aided Mol Des       Date:  2008-01-09       Impact factor: 3.686

10.  Virtual fragment screening: an exploration of various docking and scoring protocols for fragments using Glide.

Authors:  Sameer Kawatkar; Hongming Wang; Ryszard Czerminski; Diane Joseph-McCarthy
Journal:  J Comput Aided Mol Des       Date:  2009-06-03       Impact factor: 3.686

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