Literature DB >> 27543390

Ensemble-based docking: From hit discovery to metabolism and toxicity predictions.

Wilfredo Evangelista1, Rebecca L Weir1, Sally R Ellingson2, Jason B Harris3, Karan Kapoor3, Jeremy C Smith4, Jerome Baudry5.   

Abstract

This paper describes and illustrates the use of ensemble-based docking, i.e., using a collection of protein structures in docking calculations for hit discovery, the exploration of biochemical pathways and toxicity prediction of drug candidates. We describe the computational engineering work necessary to enable large ensemble docking campaigns on supercomputers. We show examples where ensemble-based docking has significantly increased the number and the diversity of validated drug candidates. Finally, we illustrate how ensemble-based docking can be extended beyond hit discovery and toward providing a structural basis for the prediction of metabolism and off-target binding relevant to pre-clinical and clinical trials.
Copyright © 2016 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Computational drug discovery; Docking; Drug discovery; Hit discovery; Lead discovery; Toxicity

Mesh:

Substances:

Year:  2016        PMID: 27543390      PMCID: PMC5073379          DOI: 10.1016/j.bmc.2016.07.064

Source DB:  PubMed          Journal:  Bioorg Med Chem        ISSN: 0968-0896            Impact factor:   3.641


  27 in total

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Review 2.  Towards the development of universal, fast and highly accurate docking/scoring methods: a long way to go.

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Review 9.  Efficient drug lead discovery and optimization.

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  17 in total

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Authors:  Hector A Velazquez; Demian Riccardi; Zhousheng Xiao; Leigh Darryl Quarles; Charless Ryan Yates; Jerome Baudry; Jeremy C Smith
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3.  Improving Structure-Based Virtual Screening with Ensemble Docking and Machine Learning.

Authors:  Joel Ricci-Lopez; Sergio A Aguila; Michael K Gilson; Carlos A Brizuela
Journal:  J Chem Inf Model       Date:  2021-10-15       Impact factor: 4.956

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5.  Energy penalties enhance flexible receptor docking in a model cavity.

Authors:  Anna S Kamenik; Isha Singh; Parnian Lak; Trent E Balius; Klaus R Liedl; Brian K Shoichet
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6.  Using Big Data Analytics to "Back Engineer" Protein Conformational Selection Mechanisms.

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7.  The quinic acid derivative KZ-41 prevents glucose-induced caspase-3 activation in retinal endothelial cells through an IGF-1 receptor dependent mechanism.

Authors:  Hui He; Rebecca L Weir; Jordan J Toutounchian; Jayaprakash Pagadala; Jena J Steinle; Jerome Baudry; Duane D Miller; Charles R Yates
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8.  Computationally identified novel agonists for GPRC6A.

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9.  Retrospective ensemble docking of allosteric modulators in an adenosine G-protein-coupled receptor.

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10.  Structure based virtual screening identifies small molecule effectors for the sialoglycan binding protein Hsa.

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