Literature DB >> 23253129

The future of virtual compound screening.

Kathrin Heikamp1, Jürgen Bajorath.   

Abstract

We provide a future perspective of the virtual screening field. A number of challenges will be highlighted that virtual screening will likely face when compound data will further grow at or beyond current rates and when much more target information will become available. These challenges go beyond computational efficiency issues (that will of course also play a critical role). For example, for structure-based approaches, the accuracy of scoring functions and energy calculations will need to be improved. For ligand-based approaches, the compound class-dependence of similarity methods needs to be further explored and relationships between molecular similarity and activity similarity need to be established. We also comment on the current and future value of virtual screening. Opportunities for further development in a postgenome era are also discussed. It is hoped that some of the views and hypotheses we articulate might stimulate further discussion about the virtual screening field going forward.
© 2012 John Wiley & Sons A/S.

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Year:  2013        PMID: 23253129     DOI: 10.1111/cbdd.12054

Source DB:  PubMed          Journal:  Chem Biol Drug Des        ISSN: 1747-0277            Impact factor:   2.817


  16 in total

1.  Combining in silico and in cerebro approaches for virtual screening and pose prediction in SAMPL4.

Authors:  Arnout R D Voet; Ashutosh Kumar; Francois Berenger; Kam Y J Zhang
Journal:  J Comput Aided Mol Des       Date:  2014-01-21       Impact factor: 3.686

2.  Binding mode similarity measures for ranking of docking poses: a case study on the adenosine A2A receptor.

Authors:  Andrew Anighoro; Jürgen Bajorath
Journal:  J Comput Aided Mol Des       Date:  2016-06-22       Impact factor: 3.686

3.  Comparison of affinity ranking using AutoDock-GPU and MM-GBSA scores for BACE-1 inhibitors in the D3R Grand Challenge 4.

Authors:  Léa El Khoury; Diogo Santos-Martins; Sukanya Sasmal; Jérôme Eberhardt; Giulia Bianco; Francesca Alessandra Ambrosio; Leonardo Solis-Vasquez; Andreas Koch; Stefano Forli; David L Mobley
Journal:  J Comput Aided Mol Des       Date:  2019-11-06       Impact factor: 3.686

4.  Choosing the Optimal Rigid Receptor for Docking and Scoring in the CSAR 2013/2014 Experiment.

Authors:  Matthew P Baumgartner; Carlos J Camacho
Journal:  J Chem Inf Model       Date:  2015-08-07       Impact factor: 4.956

Review 5.  The future of crystallography in drug discovery.

Authors:  Heping Zheng; Jing Hou; Matthew D Zimmerman; Alexander Wlodawer; Wladek Minor
Journal:  Expert Opin Drug Discov       Date:  2013-12-28       Impact factor: 6.098

Review 6.  G-quadruplex virtual drug screening: A review.

Authors:  Robert C Monsen; John O Trent
Journal:  Biochimie       Date:  2018-06-30       Impact factor: 4.079

7.  Discover binding pathways using the sliding binding-box docking approach: application to binding pathways of oseltamivir to avian influenza H5N1 neuraminidase.

Authors:  Diem-Trang T Tran; Ly T Le; Thanh N Truong
Journal:  J Comput Aided Mol Des       Date:  2013-08-24       Impact factor: 3.686

8.  Accurate and efficient target prediction using a potency-sensitive influence-relevance voter.

Authors:  Alessandro Lusci; Michael Browning; David Fooshee; Joshua Swamidass; Pierre Baldi
Journal:  J Cheminform       Date:  2015-12-29       Impact factor: 5.514

Review 9.  Drug-Like Protein-Protein Interaction Modulators: Challenges and Opportunities for Drug Discovery and Chemical Biology.

Authors:  Bruno O Villoutreix; Melaine A Kuenemann; Jean-Luc Poyet; Heriberto Bruzzoni-Giovanelli; Céline Labbé; David Lagorce; Olivier Sperandio; Maria A Miteva
Journal:  Mol Inform       Date:  2014-06-02       Impact factor: 3.353

10.  Rational design of small-molecule stabilizers of spermine synthase dimer by virtual screening and free energy-based approach.

Authors:  Zhe Zhang; Virginie Martiny; David Lagorce; Yoshihiko Ikeguchi; Emil Alexov; Maria A Miteva
Journal:  PLoS One       Date:  2014-10-23       Impact factor: 3.240

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