Literature DB >> 23340112

The holistic integration of virtual screening in drug discovery.

Yusuf Tanrikulu1, Björn Krüger, Ewgenij Proschak.   

Abstract

During the past decade, virtual screening (VS) has come of age. In this review, we document the evolution and maturation of VS from a rather exotic, stand-alone method toward a versatile hit and lead identification technology. VS campaigns have become fully integrated into drug discovery campaigns, evenly matched and complementary to high-throughput screening (HTS) methods. Here, we propose a novel classification of VS applications to help to monitor the advances in VS and to support future improvement of computational hit and lead identification methods. Several relevant VS studies from recent publications, in both academic and industrial settings, were selected to demonstrate the progress in this area. Furthermore, we identify challenges that lie ahead for the development of integrated VS campaigns.
Copyright © 2013 Elsevier Ltd. All rights reserved.

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Year:  2013        PMID: 23340112     DOI: 10.1016/j.drudis.2013.01.007

Source DB:  PubMed          Journal:  Drug Discov Today        ISSN: 1359-6446            Impact factor:   7.851


  40 in total

1.  A virtual screen discovers novel, fragment-sized inhibitors of Mycobacterium tuberculosis InhA.

Authors:  Alexander L Perryman; Weixuan Yu; Xin Wang; Sean Ekins; Stefano Forli; Shao-Gang Li; Joel S Freundlich; Peter J Tonge; Arthur J Olson
Journal:  J Chem Inf Model       Date:  2015-02-17       Impact factor: 4.956

2.  Prospective evaluation of shape similarity based pose prediction method in D3R Grand Challenge 2015.

Authors:  Ashutosh Kumar; Kam Y J Zhang
Journal:  J Comput Aided Mol Des       Date:  2016-08-02       Impact factor: 3.686

3.  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

4.  Identification of potential ACAT-2 selective inhibitors using pharmacophore, SVM and SVR from Chinese herbs.

Authors:  Lian-Sheng Qiao; Xian-Bao Zhang; Lu-di Jiang; Yan-Ling Zhang; Gong-Yu Li
Journal:  Mol Divers       Date:  2016-06-21       Impact factor: 2.943

5.  Performance of multiple docking and refinement methods in the pose prediction D3R prospective Grand Challenge 2016.

Authors:  Xavier Fradera; Andreas Verras; Yuan Hu; Deping Wang; Hongwu Wang; James I Fells; Kira A Armacost; Alejandro Crespo; Brad Sherborne; Huijun Wang; Zhengwei Peng; Ying-Duo Gao
Journal:  J Comput Aided Mol Des       Date:  2017-09-14       Impact factor: 3.686

6.  Congestion game scheduling for virtual drug screening optimization.

Authors:  Natalia Nikitina; Evgeny Ivashko; Andrei Tchernykh
Journal:  J Comput Aided Mol Des       Date:  2017-12-20       Impact factor: 3.686

7.  Comparison of Deep Learning With Multiple Machine Learning Methods and Metrics Using Diverse Drug Discovery Data Sets.

Authors:  Alexandru Korotcov; Valery Tkachenko; Daniel P Russo; Sean Ekins
Journal:  Mol Pharm       Date:  2017-11-13       Impact factor: 4.939

8.  Discovery of Staphylococcus aureus sortase A inhibitors using virtual screening and the relaxed complex scheme.

Authors:  Albert H Chan; Jeff Wereszczynski; Brendan R Amer; Sung Wook Yi; Michael E Jung; J Andrew McCammon; Robert T Clubb
Journal:  Chem Biol Drug Des       Date:  2013-10       Impact factor: 2.817

Review 9.  The essential roles of chemistry in high-throughput screening triage.

Authors:  Jayme L Dahlin; Michael A Walters
Journal:  Future Med Chem       Date:  2014-07       Impact factor: 3.808

Review 10.  Systematic Targeting of Protein-Protein Interactions.

Authors:  Ashley E Modell; Sarah L Blosser; Paramjit S Arora
Journal:  Trends Pharmacol Sci       Date:  2016-06-04       Impact factor: 14.819

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