Statistical Potential for Modeling and Ranking of Protein–Ligand Interactions-Reference-Cited by-同舟云学术

Statistical Potential for Modeling and Ranking of Protein–Ligand Interactions

Published:2011-11-21 Issue:12 Volume:51 Page:3078-3092
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Fan Hao¹²,Schneidman-Duhovny Dina¹,Irwin John J.²,Dong Guangqiang¹,Shoichet Brian K.²,Sali Andrej¹

Affiliation:

1. Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, and California Institute for Quantitative Biosciences, University of California, San Francisco

2. Department of Pharmaceutical Chemistry and California Institute for Quantitative Biosciences, University of California, San Francisco

Publisher

American Chemical Society (ACS)

Subject

Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/ci200377u

Reference128 articles.

1. Molecular Recognition and Docking Algorithms

2. Prediction of Protein−Ligand Interactions. Docking and Scoring: Successes and Gaps

3. Virtual ligand screening: strategies, perspectives and limitations

4. Calculation of Protein-Ligand Binding Affinities

5. Scoring Functions for Protein-Ligand Docking

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