Journal of Chemical Information and ModelingBioinformaticsPeer-reviewed journal article
Exhaustive exploration of the conformational landscape of small cyclic peptides using a robotics approach
Maud JusotiD, Dirk StratmanniD, Marc Vaisset, Jacques ChomilieriD, Juan CortésiD
Abstract
Small cyclic peptides represent a promising class of therapeutic molecules with unique chemical properties. However, the poor knowledge of their structural characteristics makes their computational design and structure prediction a real challenge. In order to better describe their conformational space, we developed a method, named EGSCyP, for the exhaustive exploration of the energy landscape of small head-to-tail cyclic peptides. The method can be summarized by (i) a global exploration of the conformational space based on a mechanistic representation of the peptide and the use of robotics-based algorithms to deal with the closure constraint, (ii) an all-atom refinement of the obtained conformations. EGSCyP can handle D-form residues and N-methylations. Two strategies for the side-chains placement were implemented and compared. To validate our approach, we applied it to a set of three variants of cyclic RGDFV pentapeptides, including the drug candidate Cilengitide. A comparative analysis was made with respect to replica exchange molecular dynamics simulations in implicit solvent. It results that the EGSCyP method provides a very complete characterization of the conformational space of small cyclic pentapeptides.\n\nO_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY\n\nThe paper presents a new method for the exhaustive exploration of the conformational energy landscape of small head-to-tail cyclic peptides. The approach is based on a multilevel representation of the peptide and the use of robotics-inspired algorithms.
- Citations
- 20
- FWCI
- 0.98
- Field percentile
- top 27%
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Heuristic energy-based cyclic peptide design
Qiyao Zhu, Vikram Khipple Mulligan, Dennis E. Shasha·PLoS Computational BiologyPeer-reviewed·Apr 30, 2025
- Robust conformational space exploration of cyclic peptides by combining different MD protocols and force fields
Samuel Murail, Jaysen Sawmynaden, … Dirk Stratmann·Journal of Chemical Theory and ComputationPeer-reviewed·Sep 26, 2025
- Accelerated ensemble generation for cyclic peptides using a Reservoir-REMD implementation in GROMACS
S. C. C. Hsueh, A. Aina, S. S. Plotkin·bioRxiv·Sep 7, 2022
- A Cyclisation and Docking Protocol for Cyclic Peptide-Protein Modelling using HADDOCK2.4
Vicky Charitou, Siri Camee van Keulen, Alexandre M. J. J. Bonvin·bioRxiv·Jan 21, 2022
- CyclicCAE: A Conformational Autoencoder for Efficient Heterochiral Macrocyclic Conformational Sampling
Andrew C. Powers, P. Douglas Renfrew, … Vikram Khipple Mulligan·bioRxiv·Feb 21, 2025
- Cyclic peptide structure prediction and design using AlphaFold
S. A. Rettie, K. V. Campbell, … G. Bhardwaj·bioRxiv·Feb 25, 2023