PepCrawler: a fast RRT-based algorithm for high-resolution refinement and binding affinity estimation of peptide inhibitors

• Published in: Bioinformatics Vol. 27; no. 20; pp. 2836 - 2842
• Main Authors: Donsky, Elad, Wolfson, Haim J.
• Format: Journal Article
• Language: English
• Published: Oxford Oxford University Press 15.10.2011
• Subjects: Algorithms; Biological and medical sciences; Drug Design; Fundamental and applied biological sciences. Psychology; General aspects; Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects); Models, Molecular; Multiprotein Complexes - chemistry; Multiprotein Complexes - metabolism; Peptides - chemistry; Peptides - metabolism; Protein Conformation; Protein Interaction Mapping - methods; Affinity; High resolution; Inhibitor; Peptides; Fast algorithm; Estimation
• ISSN: 1367-4803; 1367-4811; 1460-2059; 1367-4811
• DOI: 10.1093/bioinformatics/btr498

Motivation: Design of protein-protein interaction (PPI) inhibitors is a key challenge in structural bioinformatics and computer-aided drug design. Peptides, which partially mimic the interface area of one of the interacting proteins, are natural candidates to form protein-peptide complexes competing with the original PPI. The prediction of such complexes is especially challenging due to the high flexibility of peptide conformations. Results: In this article, we present PepCrawler, a new tool for deriving binding peptides from protein-protein complexes and prediction of peptide-protein complexes, by performing high-resolution docking refinement and estimation of binding affinity. By using a fast path planning approach, PepCrawler rapidly generates large amounts of flexible peptide conformations, allowing backbone and side chain flexibility. A newly introduced binding energy funnel 'steepness score' was applied for the evaluation of the protein-peptide complexes binding affinity. PepCrawler simulations predicted high binding affinity for native protein-peptide complexes benchmark and low affinity for low-energy decoy complexes. In three cases, where wet lab data are available, the PepCrawler predictions were consistent with the data. Comparing to other state of the art flexible peptide-protein structure prediction algorithms, our algorithm is very fast, and takes only minutes to run on a single PC. Availability: http://bioinfo3d.cs.tau.ac.il/PepCrawler/ Contact: eladdons@tau.ac.il; wolfson@tau.ac.il