{"id":"doi:10.1093/gpbjnl/qzag026","kind":"article","title":"Evaluating AlphaFold Tools and Related Scoring Functions for Protein-peptide Complex Prediction","authors":["Manshour N","Ren JZ","Esmaili F","Bergstrom E","Xu 许东 D"],"author_count":5,"year":2026,"published":"2026-10-01","venue":"Genomics, proteomics & bioinformatics","cited_by":1,"doi":"10.1093/gpbjnl/qzag026","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1093/gpbjnl/qzag026","archive_url":"https://space-kitty.com/papers/doi:10.1093/gpbjnl/qzag026","updated":null,"pmid":"41885376","pmcid":"PMC13653374","openalex_id":null,"pdf_url":"https://europepmc.org/articles/PMC13653374/pdf","abstract":"Determining the three-dimensional structures of protein-peptide complexes is crucial for elucidating biological processes and designing peptide-based drugs. Protein-peptide docking has become essential for predicting complex structures. AlphaFold-Multimer, ColabFold, and AlphaFold3 are groundbreaking tools that enhance protein-peptide docking accuracy. In this study, we evaluated these three tools for predicting protein-peptide complex structures in both template-based (TB) and template-free (TF) modes. AlphaFold-Multimer excels in TB predictions and performs moderately in TF scenarios in the prediction pool; however, TF outperforms TB in the first-ranked models. ColabFold demonstrates versatility in both TB and TF settings. AlphaFold3 generates high-quality structures for more proteins, but its medium-accuracy predictions are not as good as those of AlphaFold-Multimer using a large model pool. We also assessed the performance of various scoring functions in ranking predicted protein-peptide complex structures. While the scoring function built in AlphaFold demonstrates the best performance, some other scoring functions, e.g., FoldX-Stability and HADDOCK-mdscore, provide complementary information for model ranking. These findings suggest the potential for enhancing scoring functions targeting AlphaFold-based predictions by combining multiple scoring functions or using a consensus approach from many prediction models.","abstract_license":"CC-BY (article license as recorded by Europe PMC; abstract reproduced unmodified apart from markup removal)","license":"CC-BY","is_open_access":true,"retracted":false,"peer_reviewed":null,"categories":[],"details":null,"provenance":"europepmc","attribution":"Abstract of \"Evaluating AlphaFold Tools and Related Scoring Functions for Protein-peptide Complex Prediction\" by Manshour N, Ren JZ, Esmaili F et al., https://doi.org/10.1093/gpbjnl/qzag026, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified.","topics":[{"slug":"protein-design","name":"AI Protein Design & Structure Prediction","domain_slug":"biotech"}],"cited_in_dossiers":[]}