Literature DB >> 20176118

Troubleshooting computational methods in drug discovery.

Sandhya Kortagere1, Sean Ekins.   

Abstract

Computational approaches for drug discovery such as ligand-based and structure-based methods, are increasingly seen as an efficient approach for lead discovery as well as providing insights on absorption, distribution, metabolism, excretion and toxicity (ADME/Tox). What is perhaps less well known and widely described are the limitations of the different technologies. We have therefore presented a troubleshooting approach to QSAR, homology modeling, docking as well as hybrid methods. If such computational or cheminformatics methods are to become more widely used by non-experts it is critical that such limitations are brought to the user's attention and addressed during their workflows. This could improve the quality of the models and results that are obtained. Copyright 2010 Elsevier Inc. All rights reserved.

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Year:  2010        PMID: 20176118     DOI: 10.1016/j.vascn.2010.02.005

Source DB:  PubMed          Journal:  J Pharmacol Toxicol Methods        ISSN: 1056-8719            Impact factor:   1.950


  11 in total

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4.  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
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5.  Free energy landscape for the binding process of Huperzine A to acetylcholinesterase.

Authors:  Fang Bai; Yechun Xu; Jing Chen; Qiufeng Liu; Junfeng Gu; Xicheng Wang; Jianpeng Ma; Honglin Li; José N Onuchic; Hualiang Jiang
Journal:  Proc Natl Acad Sci U S A       Date:  2013-02-25       Impact factor: 11.205

6.  Human immunodeficiency virus protease inhibitors interact with ATP binding cassette transporter 4/multidrug resistance protein 4: a basis for unanticipated enhanced cytotoxicity.

Authors:  Yu Fukuda; Kazumasa Takenaka; Alex Sparreboom; Satish B Cheepala; Chung-Pu Wu; Sean Ekins; Suresh V Ambudkar; John D Schuetz
Journal:  Mol Pharmacol       Date:  2013-06-17       Impact factor: 4.436

7.  High-throughput respirometric assay identifies predictive toxicophore of mitochondrial injury.

Authors:  Lauren P Wills; Gyda C Beeson; Richard E Trager; Christopher C Lindsey; Craig C Beeson; Yuri K Peterson; Rick G Schnellmann
Journal:  Toxicol Appl Pharmacol       Date:  2013-06-26       Impact factor: 4.219

8.  Inhibitors of Helicobacter pylori protease HtrA found by 'virtual ligand' screening combat bacterial invasion of epithelia.

Authors:  Martin Löwer; Tim Geppert; Petra Schneider; Benjamin Hoy; Silja Wessler; Gisbert Schneider
Journal:  PLoS One       Date:  2011-03-31       Impact factor: 3.240

9.  An NMR-based scoring function improves the accuracy of binding pose predictions by docking by two orders of magnitude.

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Journal:  J Biomol NMR       Date:  2011-12-14       Impact factor: 2.835

10.  Open Source Bayesian Models. 3. Composite Models for Prediction of Binned Responses.

Authors:  Alex M Clark; Krishna Dole; Sean Ekins
Journal:  J Chem Inf Model       Date:  2016-01-19       Impact factor: 4.956

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