{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,9]],"date-time":"2026-10-09T05:51:41Z","timestamp":1791525101449,"version":"4.3.4"},"reference-count":80,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,10,9]],"date-time":"2026-10-09T00:00:00Z","timestamp":1791504000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Bioinform."],"abstract":"<jats:p>Computational peptide-target interaction (PTI) prediction has advanced rapidly as a tool for drug discovery, yet the field lacks agreed evaluation standards. Discrepancies in metrics, negative sampling strategies, and dataset construction across publications currently render cross-study comparisons methodologically intractable, ultimately impeding the clinical translation of therapeutic peptides. To resolve this, we present PTI-TAPE (Peptide-Target Interaction\u2014Tasks Assessing Peptide Engagement), a standardised benchmarking framework developed via a structured three-round eDelphi consensus study with 15 international experts spanning computational biology, machine learning, and regulatory science. Operating under a robust consensus threshold (&amp;gt;80% agreement), the panel established 26 definitive standards across eight domains, governed by the new STRIDE (Standardisation, Transparency, Representativeness, Integration, Discovery, Evidence) framework. Key outcomes include mandating specific primary metrics for affinity and structure, enforcing a tiered negative sampling hierarchy that prioritizes experimental non-binders, and requiring mandatory temporal dataset splits. By providing a unified reporting checklist, benchmark specifications, and a biennial governance structure, PTI-TAPE ensures reproducible evaluation and fair method comparison, bridging the gap between computational PTI predictions and genuine therapeutic benefit.<\/jats:p>","DOI":"10.3389\/fbinf.2026.1894725","type":"journal-article","created":{"date-parts":[[2026,10,9]],"date-time":"2026-10-09T05:30:12Z","timestamp":1791523812000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Establishing standardized evaluation protocols for peptide-target interaction prediction: the PTI-TAPE consensus framework eDelphi"],"prefix":"10.3389","volume":"6","author":[{"given":"William J.","family":"Waldock","sequence":"first","affiliation":[{"name":"Imperial College London, Institute of Global Health Innovation","place":["London, United Kingdom"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guangshun","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Pathology, Microbiology, and Immunology, College of Medicine, University of Nebraska Medical Center","place":["Omaha, NE, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ara","family":"Darzi","sequence":"additional","affiliation":[{"name":"Imperial College London, Institute of Global Health Innovation","place":["London, United Kingdom"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cesar","family":"de la Fuente-Nunez","sequence":"additional","affiliation":[{"name":"Machine Biology Group, Departments of Psychiatry and Microbiology, Perelman School of Medicine, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, University of Pennsylvania","place":["Philadelphia, PA, United States"]},{"name":"Departments of Bioengineering and Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania","place":["Philadelphia, PA, United States"]},{"name":"Department of Chemistry, School of Arts and Sciences, University of Pennsylvania","place":["Philadelphia, PA, United States"]},{"name":"Penn Institute for Computational Science, University of Pennsylvania","place":["Philadelphia, PA, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hutan","family":"Ashrafian","sequence":"additional","affiliation":[{"name":"Imperial College London, Institute of Global Health Innovation","place":["London, United Kingdom"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"name":"the PTI-TAPE Consortium Committee","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,10,9]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"493","DOI":"10.1038\/s41586-024-07487-w","article-title":"Accurate structure prediction of biomolecular interactions with AlphaFold 3","volume":"630","author":"Abramson","year":"2024","journal-title":"Nature"},{"key":"B2","doi-asserted-by":"publisher","first-page":"bbaa153","DOI":"10.1093\/bib\/bbaa153","article-title":"AntiCP 2.0: an updated model for predicting anticancer peptides","volume":"22","author":"Agrawal","year":"2021","journal-title":"Brief. 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