Literature DB >> 18247505

Alternative global goodness metrics and sensitivity analysis: heuristics to check the robustness of conclusions from studies comparing virtual screening methods.

Robert P Sheridan1.   

Abstract

We introduce two ways of testing the robustness of conclusions from studies comparing virtual screening methods: alternative "global goodness" metrics and sensitivity analysis. While the robustness tests cannot eliminate all biases in virtual screening comparisons, they are useful as a "reality check" for any given study. To illustrate this, we apply them to a set of enrichments published in McGaughey et al. (J. Chem. Inf. Model. 2007, 47, 1504-1519) where 11 target protein/ligand combinations are tested on 2D and 3D similarity methods, plus docking. The major conclusions in that paper, for instance, that ligand-based methods are better than docking methods, hold up. However, some minor conclusions, such as Glide being the best docking method, do not.

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Year:  2008        PMID: 18247505     DOI: 10.1021/ci700380x

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


  6 in total

1.  Multiple protein structures and multiple ligands: effects on the apparent goodness of virtual screening results.

Authors:  Robert P Sheridan; Georgia B McGaughey; Wendy D Cornell
Journal:  J Comput Aided Mol Des       Date:  2008-02-14       Impact factor: 3.686

2.  A facile consensus ranking approach enhances virtual screening robustness and identifies a cell-active DYRK1α inhibitor.

Authors:  Maria E Mavrogeni; Filippos Pronios; Danae Zareifi; Sofia Vasilakaki; Olivier Lozach; Leonidas Alexopoulos; Laurent Meijer; Vassilios Myrianthopoulos; Emmanuel Mikros
Journal:  Future Med Chem       Date:  2018-10-16       Impact factor: 3.808

3.  A method to enhance the hit ratio by a combination of structure-based drug screening and ligand-based screening.

Authors:  Katsumi Omagari; Daisuke Mitomo; Satoru Kubota; Haruki Nakamura; Yoshifumi Fukunishi
Journal:  Adv Appl Bioinform Chem       Date:  2008-08-12

4.  Comparing structural fingerprints using a literature-based similarity benchmark.

Authors:  Noel M O'Boyle; Roger A Sayle
Journal:  J Cheminform       Date:  2016-07-05       Impact factor: 5.514

5.  Virtual screening of specific insulin-like growth factor 1 receptor (IGF1R) inhibitors from the National Cancer Institute (NCI) molecular database.

Authors:  Cong Fan; Yan-Xin Huang; Yong-Li Bao; Lu-Guo Sun; Yin Wu; Chun-Lei Yu; Yu Zhang; Zhen-Bo Song; Li-Hua Zheng; Ying Sun; Guan-Nan Wang; Yu-Xin Li
Journal:  Int J Mol Sci       Date:  2012-12-14       Impact factor: 5.923

6.  Open-source platform to benchmark fingerprints for ligand-based virtual screening.

Authors:  Sereina Riniker; Gregory A Landrum
Journal:  J Cheminform       Date:  2013-05-30       Impact factor: 5.514

  6 in total

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