Literature DB >> 18203638

Is it possible to increase hit rates in structure-based virtual screening by pharmacophore filtering? An investigation of the advantages and pitfalls of post-filtering.

Daniel Muthas1, Yogesh A Sabnis, Magnus Lundborg, Anders Karlén.   

Abstract

We have investigated the influence of post-filtering virtual screening results, with pharmacophoric features generated from an X-ray structure, on enrichment rates. This was performed using three docking softwares, zdock+, Surflex and FRED, as virtual screening tools and pharmacophores generated in UNITY from co-crystallized complexes. Sets of known actives along with 9997 pharmaceutically relevant decoy compounds were docked against six chemically diverse protein targets namely CDK2, COX2, ERalpha, fXa, MMP3, and NA. To try to overcome the inherent limitations of the well-known docking problem, we generated multiple poses for each compound. The compounds were first ranked according to their scores alone and enrichment rates were calculated using only the top scoring pose of each compound. Subsequently, all poses for each compound were passed through the different pharmacophores generated from co-crystallized complexes and the enrichment factors were re-calculated based on the top-scoring passing pose of each compound. Post-filtering with a pharmacophore generated from only one X-ray complex was shown to increase enrichment rates in all investigated targets compared to docking alone. This indicates that this is a general method, which works for diverse targets and different docking softwares.

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Year:  2007        PMID: 18203638     DOI: 10.1016/j.jmgm.2007.11.005

Source DB:  PubMed          Journal:  J Mol Graph Model        ISSN: 1093-3263            Impact factor:   2.518


  16 in total

1.  Improving performance of docking-based virtual screening by structural filtration.

Authors:  Fedor N Novikov; Viktor S Stroylov; Oleg V Stroganov; Ghermes G Chilov
Journal:  J Mol Model       Date:  2009-12-30       Impact factor: 1.810

2.  Pharmacophore-based virtual screening versus docking-based virtual screening: a benchmark comparison against eight targets.

Authors:  Zhi Chen; Hong-lin Li; Qi-jun Zhang; Xiao-guang Bao; Kun-qian Yu; Xiao-min Luo; Wei-liang Zhu; Hua-liang Jiang
Journal:  Acta Pharmacol Sin       Date:  2009-11-23       Impact factor: 6.150

3.  Docking and 3D QSAR study of thiourea analogs as potent inhibitors of influenza virus neuraminidase.

Authors:  Jiaying Sun; Shaoxi Cai; Hu Mei; Jian Li; Ning Yan; Yuanqiang Wang
Journal:  J Mol Model       Date:  2010-03-07       Impact factor: 1.810

4.  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

5.  Docking and quantitative structure-activity relationship studies for 3-fluoro-4-(pyrrolo[2,1-f][1,2,4]triazin-4-yloxy)aniline, 3-fluoro-4-(1H-pyrrolo[2,3-b]pyridin-4-yloxy)aniline, and 4-(4-amino-2-fluorophenoxy)-2-pyridinylamine derivatives as c-Met kinase inhibitors.

Authors:  Julio Caballero; Miguel Quiliano; Jans H Alzate-Morales; Mirko Zimic; Eric Deharo
Journal:  J Comput Aided Mol Des       Date:  2011-04-13       Impact factor: 3.686

6.  The Development of Target-Specific Pose Filter Ensembles To Boost Ligand Enrichment for Structure-Based Virtual Screening.

Authors:  Jie Xia; Jui-Hua Hsieh; Huabin Hu; Song Wu; Xiang Simon Wang
Journal:  J Chem Inf Model       Date:  2017-06-01       Impact factor: 4.956

7.  Inhibition of Eimeria tenella CDK-related kinase 2: From target identification to lead compounds.

Authors:  Kristin Engels; Carsten Beyer; Maria L Suárez Fernández; Frank Bender; Michael Gassel; Gottfried Unden; Richard J Marhöfer; Jeremy C Mottram; Paul M Selzer
Journal:  ChemMedChem       Date:  2010-08-02       Impact factor: 3.466

8.  Cheminformatics meets molecular mechanics: a combined application of knowledge-based pose scoring and physical force field-based hit scoring functions improves the accuracy of structure-based virtual screening.

Authors:  Jui-Hua Hsieh; Shuangye Yin; Xiang S Wang; Shubin Liu; Nikolay V Dokholyan; Alexander Tropsha
Journal:  J Chem Inf Model       Date:  2011-12-14       Impact factor: 4.956

9.  Hybrid In Silico and TR-FRET-Guided Discovery of Novel BCL-2 Inhibitors.

Authors:  Kader Sahin; Muge Didem Orhan; Timucin Avsar; Serdar Durdagi
Journal:  ACS Pharmacol Transl Sci       Date:  2021-04-15

10.  IspE inhibitors identified by a combination of in silico and in vitro high-throughput screening.

Authors:  Naomi Tidten-Luksch; Raffaella Grimaldi; Leah S Torrie; Julie A Frearson; William N Hunter; Ruth Brenk
Journal:  PLoS One       Date:  2012-04-25       Impact factor: 3.240

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