Epik: p<i>K</i><sub>a</sub> and Protonation State Prediction through Machine Learning-Reference-Cited by-同舟云学术

Epik: pK_a and Protonation State Prediction through Machine Learning

Published:2023-04-06 Issue:8 Volume:19 Page:2380-2388
ISSN:1549-9618
Container-title:Journal of Chemical Theory and Computation
language:en
Short-container-title:J. Chem. Theory Comput.

Author:

Johnston Ryne C.¹^ORCID,Yao Kun²,Kaplan Zachary²,Chelliah Monica²,Leswing Karl²,Seekins Sean¹,Watts Shawn¹,Calkins David¹,Chief Elk Jackson¹,Jerome Steven V.³^ORCID,Repasky Matthew P.¹^ORCID,Shelley John C.¹^ORCID

Affiliation:

1. Schrödinger, Inc., 101 SW Main Street, Suite 1300, Portland, Oregon 97204, United States

2. Schrödinger, Inc., 1540 Broadway Street, 24th Floor, New York, New York 10036, United States

3. Schrödinger, Inc., 9171 Towne Centre Drive, San Diego, California 92122, United States

Publisher

American Chemical Society (ACS)

Subject

Physical and Theoretical Chemistry,Computer Science Applications

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.3c00044

Reference50 articles.

1. Rigorous Free Energy Perturbation Approach to Estimating Relative Binding Affinities between Ligands with Multiple Protonation and Tautomeric States

2. Towards the comprehensive, rapid, and accurate prediction of the favorable tautomeric states of drug-like molecules in aqueous solution

3. Tautomerism in drug discovery

4. Tautomerism in Computer‐Aided Drug Design

5. pK a Prediction for Organic Acids and Bases

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