Literature DB >> 18273555

Community benchmarks for virtual screening.

John J Irwin1.   

Abstract

Ligand enrichment among top-ranking hits is a key metric of virtual screening. To avoid bias, decoys should resemble ligands physically, so that enrichment is not attributable to simple differences of gross features. We therefore created a directory of useful decoys (DUD) by selecting decoys that resembled annotated ligands physically but not topologically to benchmark docking performance. DUD has 2950 annotated ligands and 95,316 property-matched decoys for 40 targets. It is by far the largest and most comprehensive public data set for benchmarking virtual screening programs that I am aware of. This paper outlines several ways that DUD can be improved to provide better telemetry to investigators seeking to understand both the strengths and the weaknesses of current docking methods. I also highlight several pitfalls for the unwary: a risk of over-optimization, questions about chemical space, and the proper scope for using DUD. Careful attention to both the composition of benchmarks and how they are used is essential to avoid being misled by overfitting and bias.

Mesh:

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Year:  2008        PMID: 18273555     DOI: 10.1007/s10822-008-9189-4

Source DB:  PubMed          Journal:  J Comput Aided Mol Des        ISSN: 0920-654X            Impact factor:   3.686


  39 in total

1.  The Protein Data Bank.

Authors:  H M Berman; J Westbrook; Z Feng; G Gilliland; T N Bhat; H Weissig; I N Shindyalov; P E Bourne
Journal:  Nucleic Acids Res       Date:  2000-01-01       Impact factor: 16.971

2.  Virtual screening using protein-ligand docking: avoiding artificial enrichment.

Authors:  Marcel L Verdonk; Valerio Berdini; Michael J Hartshorn; Wijnand T M Mooij; Christopher W Murray; Richard D Taylor; Paul Watson
Journal:  J Chem Inf Comput Sci       Date:  2004 May-Jun

3.  Assessing scoring functions for protein-ligand interactions.

Authors:  Philippe Ferrara; Holger Gohlke; Daniel J Price; Gerhard Klebe; Charles L Brooks
Journal:  J Med Chem       Date:  2004-06-03       Impact factor: 7.446

4.  Comparative evaluation of eight docking tools for docking and virtual screening accuracy.

Authors:  Esther Kellenberger; Jordi Rodrigo; Pascal Muller; Didier Rognan
Journal:  Proteins       Date:  2004-11-01

5.  Glide: a new approach for rapid, accurate docking and scoring. 2. Enrichment factors in database screening.

Authors:  Thomas A Halgren; Robert B Murphy; Richard A Friesner; Hege S Beard; Leah L Frye; W Thomas Pollard; Jay L Banks
Journal:  J Med Chem       Date:  2004-03-25       Impact factor: 7.446

6.  Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy.

Authors:  Richard A Friesner; Jay L Banks; Robert B Murphy; Thomas A Halgren; Jasna J Klicic; Daniel T Mainz; Matthew P Repasky; Eric H Knoll; Mee Shelley; Jason K Perry; David E Shaw; Perry Francis; Peter S Shenkin
Journal:  J Med Chem       Date:  2004-03-25       Impact factor: 7.446

7.  Soft docking and multiple receptor conformations in virtual screening.

Authors:  Anna Maria Ferrari; Binqing Q Wei; Luca Costantino; Brian K Shoichet
Journal:  J Med Chem       Date:  2004-10-07       Impact factor: 7.446

Review 8.  How many drug targets are there?

Authors:  John P Overington; Bissan Al-Lazikani; Andrew L Hopkins
Journal:  Nat Rev Drug Discov       Date:  2006-12       Impact factor: 84.694

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.  Crystallographic study of the tetrabutylammonium block to the KcsA K+ channel.

Authors:  Sarah Yohannan; Yue Hu; Yufeng Zhou
Journal:  J Mol Biol       Date:  2006-12-02       Impact factor: 5.469

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  44 in total

1.  Conformational analysis of a polyconjugated protein-binding ligand by joint quantum chemistry and polarizable molecular mechanics. Addressing the issues of anisotropy, conjugation, polarization, and multipole transferability.

Authors:  Elodie Goldwaser; Benoit de Courcy; Luc Demange; Christiane Garbay; Françoise Raynaud; Reda Hadj-Slimane; Jean-Philip Piquemal; Nohad Gresh
Journal:  J Mol Model       Date:  2014-11-01       Impact factor: 1.810

Review 2.  Virtual screening: an endless staircase?

Authors:  Gisbert Schneider
Journal:  Nat Rev Drug Discov       Date:  2010-04       Impact factor: 84.694

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

5.  Docking validation resources: protein family and ligand flexibility experiments.

Authors:  Sudipto Mukherjee; Trent E Balius; Robert C Rizzo
Journal:  J Chem Inf Model       Date:  2010-10-29       Impact factor: 4.956

Review 6.  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

7.  VSDMIP 1.5: an automated structure- and ligand-based virtual screening platform with a PyMOL graphical user interface.

Authors:  Álvaro Cortés Cabrera; Rubén Gil-Redondo; Almudena Perona; Federico Gago; Antonio Morreale
Journal:  J Comput Aided Mol Des       Date:  2011-08-09       Impact factor: 3.686

8.  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

9.  Optimal assignment methods for ligand-based virtual screening.

Authors:  Andreas Jahn; Georg Hinselmann; Nikolas Fechner; Andreas Zell
Journal:  J Cheminform       Date:  2009-08-25       Impact factor: 5.514

10.  Automated docking screens: a feasibility study.

Authors:  John J Irwin; Brian K Shoichet; Michael M Mysinger; Niu Huang; Francesco Colizzi; Pascal Wassam; Yiqun Cao
Journal:  J Med Chem       Date:  2009-09-24       Impact factor: 7.446

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