Literature DB >> 18075713

Bias, reporting, and sharing: computational evaluations of docking methods.

Ajay N Jain1.   

Abstract

Computational methods for docking ligands to protein binding sites have become ubiquitous in drug discovery. Despite the age of the field, no standards have been established with respect to methodological evaluation of docking accuracy, virtual screening utility, or scoring accuracy. There are critical issues relating to data sharing, data set design and preparation, and statistical reporting that have an impact on the degree to which a report will translate into real-world performance. These issues also have an impact on whether there is a transparent relationship between methodological changes and reported performance improvements. This paper presents detailed examples of pitfalls in each area and makes recommendations as to best practices.

Mesh:

Year:  2007        PMID: 18075713     DOI: 10.1007/s10822-007-9151-x

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


  27 in total

1.  Protocols for bridging the peptide to nonpeptide gap in topological similarity searches.

Authors:  R P Sheridan; S B Singh; E M Fluder; S K Kearsley
Journal:  J Chem Inf Comput Sci       Date:  2001 Sep-Oct

2.  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

3.  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

4.  ZINC--a free database of commercially available compounds for virtual screening.

Authors:  John J Irwin; Brian K Shoichet
Journal:  J Chem Inf Model       Date:  2005 Jan-Feb       Impact factor: 4.956

5.  Extra precision glide: docking and scoring incorporating a model of hydrophobic enclosure for protein-ligand complexes.

Authors:  Richard A Friesner; Robert B Murphy; Matthew P Repasky; Leah L Frye; Jeremy R Greenwood; Thomas A Halgren; Paul C Sanschagrin; Daniel T Mainz
Journal:  J Med Chem       Date:  2006-10-19       Impact factor: 7.446

Review 6.  Automated docking of flexible ligands: applications of AutoDock.

Authors:  D S Goodsell; G M Morris; A J Olson
Journal:  J Mol Recognit       Date:  1996 Jan-Feb       Impact factor: 2.137

7.  Empirical scoring functions: I. The development of a fast empirical scoring function to estimate the binding affinity of ligands in receptor complexes.

Authors:  M D Eldridge; C W Murray; T R Auton; G V Paolini; R P Mee
Journal:  J Comput Aided Mol Des       Date:  1997-09       Impact factor: 3.686

8.  Hammerhead: fast, fully automated docking of flexible ligands to protein binding sites.

Authors:  W Welch; J Ruppert; A N Jain
Journal:  Chem Biol       Date:  1996-06

9.  Development and validation of a genetic algorithm for flexible docking.

Authors:  G Jones; P Willett; R C Glen; A R Leach; R Taylor
Journal:  J Mol Biol       Date:  1997-04-04       Impact factor: 5.469

10.  The development of a simple empirical scoring function to estimate the binding constant for a protein-ligand complex of known three-dimensional structure.

Authors:  H J Böhm
Journal:  J Comput Aided Mol Des       Date:  1994-06       Impact factor: 3.686

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  41 in total

1.  FRED and HYBRID docking performance on standardized datasets.

Authors:  Mark McGann
Journal:  J Comput Aided Mol Des       Date:  2012-06-05       Impact factor: 3.686

2.  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

3.  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

4.  FDA approved drugs complexed to their targets: evaluating pose prediction accuracy of docking protocols.

Authors:  Mohammed H Bohari; G Narahari Sastry
Journal:  J Mol Model       Date:  2012-05-08       Impact factor: 1.810

5.  In-silico identification of the binding mode of synthesized adamantyl derivatives inside cholinesterase enzymes.

Authors:  Amal Al-Aboudi; Raed A Al-Qawasmeh; Alaa Shahwan; Uzma Mahmood; Asaad Khalid; Zaheer Ul-Haq
Journal:  Acta Pharmacol Sin       Date:  2015-05-04       Impact factor: 6.150

6.  Comparative evaluation of several docking tools for docking small molecule ligands to DC-SIGN.

Authors:  Gregor Jug; Marko Anderluh; Tihomir Tomašič
Journal:  J Mol Model       Date:  2015-06-04       Impact factor: 1.810

7.  Fragment-based drug discovery using a multidomain, parallel MD-MM/PBSA screening protocol.

Authors:  Tian Zhu; Hyun Lee; Hao Lei; Christopher Jones; Kavankumar Patel; Michael E Johnson; Kirk E Hevener
Journal:  J Chem Inf Model       Date:  2013-03-14       Impact factor: 4.956

8.  Progress towards automated Kepler scientific workflows for computer-aided drug discovery and molecular simulations.

Authors:  Pek U Ieong; Jesper Sørensen; Prasantha L Vemu; Celia W Wong; Özlem Demir; Nadya P Williams; Jianwu Wang; Daniel Crawl; Robert V Swift; Robert D Malmstrom; Ilkay Altintas; Rommie E Amaro
Journal:  Procedia Comput Sci       Date:  2014

9.  Recipes for the selection of experimental protein conformations for virtual screening.

Authors:  Manuel Rueda; Giovanni Bottegoni; Ruben Abagyan
Journal:  J Chem Inf Model       Date:  2010-01       Impact factor: 4.956

10.  A statistical framework to evaluate virtual screening.

Authors:  Wei Zhao; Kirk E Hevener; Stephen W White; Richard E Lee; James M Boyett
Journal:  BMC Bioinformatics       Date:  2009-07-20       Impact factor: 3.169

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