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Phys Chem Chem Phys. 2015 Feb 14;17(6):4210-9. doi: 10.1039/c4cp04580g.

Toward structure prediction of cyclic peptides.

Author information

1
Department of Chemistry, Tufts University, Medford, Massachusetts 02155, USA. yu-shan.lin@tufts.edu.

Abstract

Cyclic peptides are a promising class of molecules that can be used to target specific protein-protein interactions. A computational method to accurately predict their structures would substantially advance the development of cyclic peptides as modulators of protein-protein interactions. Here, we develop a computational method that integrates bias-exchange metadynamics simulations, a Boltzmann reweighting scheme, dihedral principal component analysis and a modified density peak-based cluster analysis to provide a converged structural description for cyclic peptides. Using this method, we evaluate the performance of a number of popular protein force fields on a model cyclic peptide. All the tested force fields seem to over-stabilize the α-helix and PPII/β regions in the Ramachandran plot, commonly populated by linear peptides and proteins. Our findings suggest that re-parameterization of a force field that well describes the full Ramachandran plot is necessary to accurately model cyclic peptides.

PMID:
25566700
DOI:
10.1039/c4cp04580g
[Indexed for MEDLINE]

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