Literature DB >> 17591764

Comparison of topological, shape, and docking methods in virtual screening.

Georgia B McGaughey1, Robert P Sheridan, Christopher I Bayly, J Chris Culberson, Constantine Kreatsoulas, Stacey Lindsley, Vladimir Maiorov, Jean-Francois Truchon, Wendy D Cornell.   

Abstract

Virtual screening benchmarking studies were carried out on 11 targets to evaluate the performance of three commonly used approaches: 2D ligand similarity (Daylight, TOPOSIM), 3D ligand similarity (SQW, ROCS), and protein structure-based docking (FLOG, FRED, Glide). Active and decoy compound sets were assembled from both the MDDR and the Merck compound databases. Averaged over multiple targets, ligand-based methods outperformed docking algorithms. This was true for 3D ligand-based methods only when chemical typing was included. Using mean enrichment factor as a performance metric, Glide appears to be the best docking method among the three with FRED a close second. Results for all virtual screening methods are database dependent and can vary greatly for particular targets.

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Year:  2007        PMID: 17591764     DOI: 10.1021/ci700052x

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


  105 in total

1.  Improving molecular docking through eHiTS' tunable scoring function.

Authors:  Orr Ravitz; Zsolt Zsoldos; Aniko Simon
Journal:  J Comput Aided Mol Des       Date:  2011-11-11       Impact factor: 3.686

2.  Correlation between biological activity and binding energy in systems of integrin with cyclic RGD-containing binders: a QM/MM molecular dynamics study.

Authors:  Mingli Xiang; Yuchun Lin; Gu He; Lijuan Chen; Mingli Yang; Shengyong Yang; Yirong Mo
Journal:  J Mol Model       Date:  2012-06-27       Impact factor: 1.810

3.  Biased retrieval of chemical series in receptor-based virtual screening.

Authors:  Natasja Brooijmans; Jason B Cross; Christine Humblet
Journal:  J Comput Aided Mol Des       Date:  2010-10-30       Impact factor: 3.686

4.  Ultrafast protein structure-based virtual screening with Panther.

Authors:  Sanna P Niinivehmas; Kari Salokas; Sakari Lätti; Hannu Raunio; Olli T Pentikäinen
Journal:  J Comput Aided Mol Des       Date:  2015-09-25       Impact factor: 3.686

Review 5.  Methods for Similarity-based Virtual Screening.

Authors:  Thomas G Kristensen; Jesper Nielsen; Christian N S Pedersen
Journal:  Comput Struct Biotechnol J       Date:  2013-03-03       Impact factor: 7.271

6.  The Development of Target-Specific Pose Filter Ensembles To Boost Ligand Enrichment for Structure-Based Virtual Screening.

Authors:  Jie Xia; Jui-Hua Hsieh; Huabin Hu; Song Wu; Xiang Simon Wang
Journal:  J Chem Inf Model       Date:  2017-06-01       Impact factor: 4.956

7.  Benchmarking methods and data sets for ligand enrichment assessment in virtual screening.

Authors:  Jie Xia; Ermias Lemma Tilahun; Terry-Elinor Reid; Liangren Zhang; Xiang Simon Wang
Journal:  Methods       Date:  2014-12-03       Impact factor: 3.608

8.  Modeling of peroxide activation in artemisinin derivatives by serial docking.

Authors:  Roy J Little; Alexis A Pestano; Zaida Parra
Journal:  J Mol Model       Date:  2009-01-14       Impact factor: 1.810

9.  BCL::MolAlign: Three-Dimensional Small Molecule Alignment for Pharmacophore Mapping.

Authors:  Benjamin P Brown; Jeffrey Mendenhall; Jens Meiler
Journal:  J Chem Inf Model       Date:  2019-02-12       Impact factor: 4.956

10.  Docking challenge: protein sampling and molecular docking performance.

Authors:  Khaled M Elokely; Robert J Doerksen
Journal:  J Chem Inf Model       Date:  2013-04-15       Impact factor: 4.956

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