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:
2013
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Repository URL:
https://works.bepress.com/joseph_audie/2; https://digitalcommons.sacredheart.edu/chem_fac/6
PMID:
23066895
DOI:
10.1111/cbdd.12076
Author(s):
Audie, Joseph; Swanson, Jon
Publisher(s):
Wiley-Blackwell
Tags:
Biochemistry, Genetics and Molecular Biology; Protein binding; Drug development; Molecules; Molecular recognition; Molecular modeling; Drugs; Design; Prediction theory; Analytical Chemistry; Biological and Chemical Physics
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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.