Exploring the conformational space of cyclic peptides by a stochastic search method

Anwar Rayan, Hanoch Senderowitz, Amiram Goldblum*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

37 Scopus citations


A stochastic search algorithm is applied in order to probe the conformations of cyclic peptides. The search is conducted in two stages. In the first stage, random conformations are generated and evaluated by a penalty function for ring closure ability, following a stepwise construction of each amino acid into the peptide by a random choice of one of its allowed conformations. The allowed conformational ranges of backbone dihedral angles for each amino acid have been extracted from a Data Bank of diverse proteins. Values of dihedral angles that do not contribute favorably to the scoring of ring closure are retained or discarded by a statistical test. Values are discarded up to a point from which all remaining combinations of angles are constructed, scored, sorted, and clustered. In the second stage, side chains have been added and fast optimization was applied to the set of diverse conformations in a "united atoms" approach, with the "Kollman forcefield" of Sybyl 6.8. This iterative stochastic elimination algorithm finds the global minimum and most of the best results, when compared to a full exhaustive search in appropriately sized problems. In larger problems, we compare the results to experimental structures. The root mean square deviation (RMSD) of our best results compared to crystal structures of cyclic peptides with sizes from 4 to 15 amino acids are mostly below 1.0Å up to 8mers and under 2.0Å for larger cyclic peptides.

Original languageAmerican English
Pages (from-to)319-333
Number of pages15
JournalJournal of Molecular Graphics and Modelling
Issue number5
StatePublished - May 2004

Bibliographical note

Funding Information:
This research was supported by the Israel Science Foundation grant no. 608/02. We thank the Alex Grass Center for Drug Design and Synthesis for supporting the purchase of a workstation for this research. We wish to thank professor G.V. Nikiforovich for sending us cyclic peptide coordinates that were helpful for comparing our results to experiments.


  • Complex combinatorial
  • Conformations
  • Cyclic peptides
  • Ensembles
  • Flexibility
  • Multidimensional space
  • Stochastic search algorithm
  • Structure prediction


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