Literature DB >> 18217218

How to do an evaluation: pitfalls and traps.

Paul C D Hawkins1, Gregory L Warren, A Geoffrey Skillman, Anthony Nicholls.   

Abstract

The recent literature is replete with papers evaluating computational tools (often those operating on 3D structures) for their performance in a certain set of tasks. Most commonly these papers compare a number of docking tools for their performance in cognate re-docking (pose prediction) and/or virtual screening. Related papers have been published on ligand-based tools: pose prediction by conformer generators and virtual screening using a variety of ligand-based approaches. The reliability of these comparisons is critically affected by a number of factors usually ignored by the authors, including bias in the datasets used in virtual screening, the metrics used to assess performance in virtual screening and pose prediction and errors in crystal structures used.

Entities:  

Mesh:

Year:  2008        PMID: 18217218      PMCID: PMC2270916          DOI: 10.1007/s10822-007-9166-3

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


  40 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

Review 2.  Validation of protein crystal structures.

Authors:  G J Kleywegt
Journal:  Acta Crystallogr D Biol Crystallogr       Date:  2000-03

3.  Comparison of assay technologies for a tyrosine kinase assay generates different results in high throughput screening.

Authors:  Matthew A Sills; Donna Weiss; Quynhchi Pham; Robert Schweitzer; Xiang Wu; Jinzi J Wu
Journal:  J Biomol Screen       Date:  2002-06

4.  Assessing the performance of OMEGA with respect to retrieving bioactive conformations.

Authors:  Jonas Boström; Jeremy R Greenwood; Johan Gottfries
Journal:  J Mol Graph Model       Date:  2003-03       Impact factor: 2.518

5.  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

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.  Comparative study of several algorithms for flexible ligand docking.

Authors:  Badry D Bursulaya; Maxim Totrov; Ruben Abagyan; Charles L Brooks
Journal:  J Comput Aided Mol Des       Date:  2003-11       Impact factor: 3.686

Review 8.  Comparing protein-ligand docking programs is difficult.

Authors:  Jason C Cole; Christopher W Murray; J Willem M Nissink; Richard D Taylor; Robin Taylor
Journal:  Proteins       Date:  2005-08-15

9.  Comparative performance assessment of the conformational model generators omega and catalyst: a large-scale survey on the retrieval of protein-bound ligand conformations.

Authors:  Johannes Kirchmair; Gerhard Wolber; Christian Laggner; Thierry Langer
Journal:  J Chem Inf Model       Date:  2006 Jul-Aug       Impact factor: 4.956

10.  Comparison of shape-matching and docking as virtual screening tools.

Authors:  Paul C D Hawkins; A Geoffrey Skillman; Anthony Nicholls
Journal:  J Med Chem       Date:  2007-01-11       Impact factor: 7.446

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  37 in total

1.  SimiCon: a web tool for protein-ligand model comparison through calculation of equivalent atomic contacts.

Authors:  Manuel Rueda; Vsevolod Katritch; Eugene Raush; Ruben Abagyan
Journal:  Bioinformatics       Date:  2010-09-24       Impact factor: 6.937

2.  Models of protein-ligand crystal structures: trust, but verify.

Authors:  Marc C Deller; Bernhard Rupp
Journal:  J Comput Aided Mol Des       Date:  2015-02-10       Impact factor: 3.686

3.  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

4.  Computation of 3D queries for ROCS based virtual screens.

Authors:  Gregory J Tawa; J Christian Baber; Christine Humblet
Journal:  J Comput Aided Mol Des       Date:  2009-09-26       Impact factor: 3.686

5.  Comparative virtual screening and novelty detection for NMDA-GlycineB antagonists.

Authors:  Bjoern A Krueger; Tanja Weil; Gisbert Schneider
Journal:  J Comput Aided Mol Des       Date:  2009-11-05       Impact factor: 3.686

6.  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

7.  Evaluation of several two-step scoring functions based on linear interaction energy, effective ligand size, and empirical pair potentials for prediction of protein-ligand binding geometry and free energy.

Authors:  Obaidur Rahaman; Trilce P Estrada; Douglas J Doren; Michela Taufer; Charles L Brooks; Roger S Armen
Journal:  J Chem Inf Model       Date:  2011-06-06       Impact factor: 4.956

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.  Conformer generation with OMEGA: algorithm and validation using high quality structures from the Protein Databank and Cambridge Structural Database.

Authors:  Paul C D Hawkins; A Geoffrey Skillman; Gregory L Warren; Benjamin A Ellingson; Matthew T Stahl
Journal:  J Chem Inf Model       Date:  2010-04-26       Impact factor: 4.956

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