Rational design of glycosaminoglycan binding cyclic peptides using cPEPmatch

Abstract

Cyclic peptides present a robust platform for drug design, offering high specificity and stability due to their conformationally constrained structures. In this study, we introduce an updated version of the Cyclic Peptide Matching program (cPEPmatch) tailored for the identification of cyclic peptides capable of mimicking protein-glycosaminoglycan (GAG) binding sites. We focused on engineering cyclic peptides to replicate the GAG-binding affinity of antithrombin III (ATIII), a protein that plays a crucial role in modulating anticoagulation through interaction with the GAG heparin. By integrating computational and experimental methods, we successfully identified a cyclic peptide binder with promising potential for future optimization. MD simulations and MM-GBSA calculations were used to assess binding efficacy, supplemented by umbrella sampling to approximate free energy landscapes. The binding specificity was further validated through NMR and ITC experiments. Our findings demonstrate that the computationally designed cyclic peptides effectively target GAGs, suggesting their potential as novel therapeutic agents. This study advances our understanding of peptide-GAG interactions and lays the groundwork for future development of cyclic peptide-based therapeutics.