Advances in the prediction of protein-peptide binding affinities: implications for peptide-based drug discovery.

Citation data:

Chemical biology & drug design, ISSN: 1747-0285, Vol: 81, Issue: 1, Page: 50-60

Publication Year:
Usage 316
Abstract Views 280
Full Text Views 36
Captures 53
Readers 47
Exports-Saves 6
Social Media 1
Tweets 1
Citations 15
Citation Indexes 15
Repository URL:;
Audie, Joseph; Swanson, Jon
Biochemistry, Genetics and Molecular Biology; Protein binding; Drug development; Molecules; Molecular recognition; Molecular modeling; Drugs; Design; Prediction theory; Analytical Chemistry; Biological and Chemical Physics
Most Recent Tweet View All Tweets
review description
Peptides hold great promise as novel medicinal and biologic agents, and computational methods can help unlock that promise. In particular, structure-based peptide design can be used to identify and optimize peptide ligands. Successful structure-based design, in turn, requires accurate and fast methods for predicting protein-peptide binding affinities. Here, we review the development of such methods, emphasizing structure-based methods that assume rigid-body association and the single-structure approximation. We also briefly review recent applications of computational free energy prediction methods to enable and guide novel peptide drug and biomarker discovery. We close the review with a brief perspective on the future of computational, structure-based protein-peptide binding affinity prediction.