# Evaluating AlphaFold Tools and Related Scoring Functions for Protein-peptide Complex Prediction

Article · Manshour N, Ren JZ, Esmaili F, Bergstrom E, Xu 许东 D

- Archive id: doi:10.1093/gpbjnl/qzag026
- Published: 2026-10-01
- Venue: Genomics, proteomics & bioinformatics
- DOI: https://doi.org/10.1093/gpbjnl/qzag026
- PMID: 41885376
- PMCID: PMC13653374
- Citations: 1
- Source URL: https://doi.org/10.1093/gpbjnl/qzag026
- PDF: https://europepmc.org/articles/PMC13653374/pdf
- Provenance: europepmc

## 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 reproduced under CC-BY (article license as recorded by Europe PMC; abstract reproduced unmodified apart from markup removal)._

Topics: [AI Protein Design & Structure Prediction](https://space-kitty.com/topics/protein-design)

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