Comparative evaluation of the prediction accuracy of AlphaFold and ESMFold for monomeric and dimeric proteins
Abstract
We have evaluated the prediction accuracy of three different tools, deep-learning-based AlphaFold2, AlphaFold3, and large language model-based ESMFold, utilizing the experimentally derived structures deposited in the Protein Data Bank between 2022 and 2024, excluding those entries with close homologs in the structures released prior to 2022. Based on the criteria of sequence identity lower than 40% and query coverage
Fields of Study & Subjects
Protein Structure and Dynamics
Machine Learning in Bioinformatics
Genomics and Rare Diseases
Publication details
- Journal / source
- NAR Genomics and Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Volume
- 8
- Issue
- 1
- Pages
- lqag002–lqag002
- Publication date
- 6 January 2026
- Language
- EN