Advances in the prediction of protein-peptide binding affinities: implications for peptide-based drug discovery.
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.
CMD Bioscience, LLC, 5 Science Park, New Haven, CT 06511, USA. joseph.audie@cmdbioscience.com
Joseph
J
Audie
Jon
J
Swanson
D019295:Computational Biology; D015195:Drug Design; D008958:Models, Molecular; D010455:Peptides / Q000737:chemistry / Q000378:metabolism*; D011485:Protein Binding; D011506:Proteins / Q000378:metabolism*; D013816:Thermodynamics
D010455:Peptides; D011506:Proteins