Establishing standardized evaluation protocols for peptide-target interaction prediction: the PTI-TAPE consensus framework eDelphi

Abstract

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—Tasks 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 (>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.