{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,15]],"date-time":"2025-12-15T13:56:24Z","timestamp":1765806984552},"reference-count":44,"publisher":"Oxford University Press (OUP)","issue":"20","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2011,10,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: Design of protein\u2013protein 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\u2013peptide complexes competing with the original PPI. The prediction of such complexes is especially challenging due to the high flexibility of peptide conformations.<\/jats:p>\n               <jats:p>Results: In this article, we present PepCrawler, a new tool for deriving binding peptides from protein\u2013protein complexes and prediction of peptide\u2013protein 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 \u2018steepness score\u2019 was applied for the evaluation of the protein\u2013peptide complexes binding affinity. PepCrawler simulations predicted high binding affinity for native protein\u2013peptide 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\u2013protein structure prediction algorithms, our algorithm is very fast, and takes only minutes to run on a single PC.<\/jats:p>\n               <jats:p>Availability: \u00a0http:\/\/bioinfo3d.cs.tau.ac.il\/PepCrawler\/<\/jats:p>\n               <jats:p>Contact: \u00a0eladdons@tau.ac.il; wolfson@tau.ac.il<\/jats:p>","DOI":"10.1093\/bioinformatics\/btr498","type":"journal-article","created":{"date-parts":[[2011,9,1]],"date-time":"2011-09-01T11:03:12Z","timestamp":1314874992000},"page":"2836-2842","source":"Crossref","is-referenced-by-count":83,"title":["PepCrawler: a fast RRT-based algorithm for high-resolution refinement and binding affinity estimation of peptide inhibitors"],"prefix":"10.1093","volume":"27","author":[{"given":"Elad","family":"Donsky","sequence":"first","affiliation":[{"name":"Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel"}]},{"given":"Haim J.","family":"Wolfson","sequence":"additional","affiliation":[{"name":"Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel"}]}],"member":"286","published-online":{"date-parts":[[2011,8,31]]},"reference":[{"key":"2023012512012863500_B1","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1002\/prot.21495","article-title":"FireDock: fast interaction refinement in molecular docking","volume":"69","author":"Andrusier","year":"2007","journal-title":"Proteins"},{"key":"2023012512012863500_B2","doi-asserted-by":"crossref","first-page":"1084","DOI":"10.1002\/prot.22629","article-title":"DynaDock: a new molecular dynamics-based algorithm for protein\u2013peptide docking including receptor flexibility","volume":"78","author":"Antes","year":"2010","journal-title":"Proteins"},{"key":"2023012512012863500_B3","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1038\/nrd1343","article-title":"Small-molecule inhibitors of protein\u2013protein interactions: progressing towards the dream","volume":"3","author":"Arkin","year":"2004","journal-title":"Nat. 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