Extrapolative prediction using physically-based QSAR-Reference-Cited by-同舟云学术

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Extrapolative prediction using physically-based QSAR

Published:2016-02 Issue:2 Volume:30 Page:127-152
ISSN:0920-654X
Container-title:Journal of Computer-Aided Molecular Design
language:en
Short-container-title:J Comput Aided Mol Des

Author:

Cleves Ann E.,Jain Ajay N.

Funder

National Institute of General Medical Sciences

Publisher

Springer Science and Business Media LLC

Subject

Physical and Theoretical Chemistry,Computer Science Applications,Drug Discovery

Link

http://link.springer.com/content/pdf/10.1007/s10822-016-9896-1.pdf

Reference50 articles.

1. Langham JJ, Cleves AE, Spitzer R, Kirshner D, Jain AN (2009) Physical binding pocket induction for affinity prediction. J Med Chem 52(19):6107–6125

2. Jain A, Dietterich TG, Lathrop RH, Chapman D, Critchlow REJ, Bauer BE, Webster TA, Lozano-Perez T (1994) A shape-based machine learning tool for drug design. J Comput-Aided Mol Des 8(6):635–652

3. Jain A, Koile K, Chapman D (1994) Compass: Predicting biological activities from molecular surface properties. performance comparisons on a steroid benchmark. J Med Chem 37(15):2315–2327

4. Jain AN (2010) QMOD: physically meaningful QSAR. J Comput-Aided Mol Des 24(10):865–878

5. Jain A, Cleves A (2012) Does your model weigh the same as a duck? J Comput-Aided Mol Des 26:57–67

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3. Synergy and Complementarity between Focused Machine Learning and Physics-Based Simulation in Affinity Prediction;Journal of Chemical Information and Modeling;2021-12-10

4. Quantitative surface field analysis: learning causal models to predict ligand binding affinity and pose;Journal of Computer-Aided Molecular Design;2018-06-22

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