Assessing AlphaFold 3 for Per- and Polyfluoroalkyl Substances Docking in Protein Structures.

ABSTRACT: Per- and polyfluoroalkyl substances (PFAS) are persistent environmental pollutants that may pose health risks due to strong protein interactions. While AlphaFold 3 (AF3) was recently introduced for protein-ligand modeling with high claimed accuracy, its reliability for docking PFAS remains unclear. This study evaluates AF3's performance in predicting protein-PFAS interactions using a curated data set from the Protein Data Bank, divided into a "Before Set" (seen during AF3 training) and an "After Set" (unseen). AF3 accurately predicts protein structures and pockets but shows reduced performance in pocket-aligned ligand predictions, achieving ∼74.5% success in "Before Set" but only ∼55.8% in "After Set", indicative of possible overfitting. We further assess the effects of PFAS type on dockin

SUBMITTER: Gong X 

PROVIDER: S-EPMC12424161 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature