Literature DB >> 17929799

Fast and efficient in silico 3D screening: toward maximum computational efficiency of pharmacophore-based and shape-based approaches.

Johannes Kirchmair1, Stojanka Ristic, Kathrin Eder, Patrick Markt, Gerhard Wolber, Christian Laggner, Thierry Langer.   

Abstract

In continuation of our recent studies on the quality of conformational models generated with CATALYST and OMEGA we present a large-scale survey focusing on the impact of conformational model quality and several screening parameters on pharmacophore-based and shape-based virtual high throughput screening (vHTS). Therefore, we collected known active compounds of CDK2, p38 MAPK, PPAR-gamma, and factor Xa and built a set of druglike decoys using ilib:diverse. Subsequently, we generated 3D structures using CORINA and also calculated conformational models for all compounds using CAESAR, CATALYST FAST, and OMEGA. A widespread set of 103 structure-based pharmacophore models was developed with LigandScout for virtual screening with CATALYST. The performance of both database search modes (FAST and BEST flexible database search) as well as the fit value calculation procedures (FAST and BEST fit) available in CATALYST were analyzed in terms of their ability to discriminate between active and inactive compounds and in terms of efficiency. Moreover, these results are put in direct comparison to the performance of the shape-based virtual screening platform ROCS. Our results prove that high enrichment rates are not necessarily in conflict with efficient vHTS settings: In most of the experiments, we obtained the highest yield of actives in the hit list when parameter sets for the fastest search algorithm were used.

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Year:  2007        PMID: 17929799     DOI: 10.1021/ci700024q

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


  15 in total

Review 1.  Evaluation of the performance of 3D virtual screening protocols: RMSD comparisons, enrichment assessments, and decoy selection--what can we learn from earlier mistakes?

Authors:  Johannes Kirchmair; Patrick Markt; Simona Distinto; Gerhard Wolber; Thierry Langer
Journal:  J Comput Aided Mol Des       Date:  2008-01-15       Impact factor: 3.686

2.  Application of shape-based and pharmacophore-based in silico screens for identification of Type II protein kinase inhibitors.

Authors:  Daniel Mucs; Richard A Bryce; Pascal Bonnet
Journal:  J Comput Aided Mol Des       Date:  2011-06-17       Impact factor: 3.686

3.  Exploring conformational search protocols for ligand-based virtual screening and 3-D QSAR modeling.

Authors:  Daniel Cappel; Steven L Dixon; Woody Sherman; Jianxin Duan
Journal:  J Comput Aided Mol Des       Date:  2014-11-19       Impact factor: 3.686

4.  Pharmacophore and molecular dynamics based activity profiling of natural products for kinases involved in lung cancer.

Authors:  Pankaj Kumar Singh; Om Silakari
Journal:  J Mol Model       Date:  2018-10-20       Impact factor: 1.810

5.  An integrated approach to knowledge-driven structure-based virtual screening.

Authors:  Angela M Henzler; Sascha Urbaczek; Matthias Hilbig; Matthias Rarey
Journal:  J Comput Aided Mol Des       Date:  2014-07-04       Impact factor: 3.686

6.  In search of the representative pharmacophore hypotheses of the enzymatic proteome of Plasmodium falciparum: a multicomplex-based approach.

Authors:  Anu Manhas; Mohsin Y Lone; Prakash C Jha
Journal:  Mol Divers       Date:  2018-10-12       Impact factor: 2.943

7.  Structure-based and shape-complemented pharmacophore modeling for the discovery of novel checkpoint kinase 1 inhibitors.

Authors:  Xiu-Mei Chen; Tao Lu; Shuai Lu; Hui-Fang Li; Hao-Liang Yuan; Ting Ran; Hai-Chun Liu; Ya-Dong Chen
Journal:  J Mol Model       Date:  2009-12-18       Impact factor: 1.810

Review 8.  The importance of discerning shape in molecular pharmacology.

Authors:  Sandhya Kortagere; Matthew D Krasowski; Sean Ekins
Journal:  Trends Pharmacol Sci       Date:  2009-01-31       Impact factor: 14.819

9.  Application of 3D Zernike descriptors to shape-based ligand similarity searching.

Authors:  Vishwesh Venkatraman; Padmasini Ramji Chakravarthy; Daisuke Kihara
Journal:  J Cheminform       Date:  2009-12-17       Impact factor: 5.514

Review 10.  Computational prediction of metabolism: sites, products, SAR, P450 enzyme dynamics, and mechanisms.

Authors:  Johannes Kirchmair; Mark J Williamson; Jonathan D Tyzack; Lu Tan; Peter J Bond; Andreas Bender; Robert C Glen
Journal:  J Chem Inf Model       Date:  2012-02-17       Impact factor: 4.956

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