Computational methods to design cyclic peptides.
Cyclic peptides (CPs) are promising modulators of protein-protein interactions (PPIs), but their application remains challenging. It is currently difficult to predict the structures and bioavailability of CPs. The ability to design CPs using computer modeling would greatly facilitate the development of CPs as potent PPI modulators for fundamental studies and as potential therapeutics. Herein, we describe computational methods to generate CP libraries for virtual screening, as well as current efforts to accurately predict the conformations adopted by CPs. These advances are making it possible to envision robust computational design of active CPs. However, unique properties of CPs pose significant challenges associated with sampling CP conformational space and accurately describing CP energetics. These major obstacles to structure prediction likely must be solved before robust design of active CPs can be reliably achieved.
Department of Chemistry, Tufts University, Medford, MA 02155, United States.
Sean M
SM
McHugh
Department of Chemistry, Tufts University, Medford, MA 02155, United States.
Julia R
JR
Rogers
Department of Chemistry, Tufts University, Medford, MA 02155, United States.
Sarah A
SA
Solomon
Department of Chemistry, Tufts University, Medford, MA 02155, United States.
Hongtao
H
Yu
Department of Chemistry, Tufts University, Medford, MA 02155, United States. Electronic address: yu-shan.lin@tufts.edu.
Yu-Shan
YS
Lin
D000465:Algorithms; D056004:Molecular Dynamics Simulation; D010456:Peptides, Cyclic / Q000737:chemistry*; D011487:Protein Conformation
D010456:Peptides, Cyclic