Work

Accuracy of AlphaFold models: Comparison with short N O contacts in atomic resolution protein crystal structures

Year: 2024

Type: article

Abstract: Artificial intelligence (AI) has revolutionized structural biology by predicting protein 3D structures with near-experimental accuracy. Here, short backbone N-O distances in high-resolution crystal structures were compared to those in three-dimensional models based on AI AlphaFold/ColabFold, specifically considering their estimated standard errors. Experimental and computationally modeled distances very often differ significantly, showing that these models' precision is inadequate to reproduce experimental results at high resolution. T-tests and normal probability plots showed that these computational methods predict atomic position standard errors 3.5-6 times bigger than experimental errors. SYNOPSIS: Positional standard errors in AI-based protein 3D models are 3.5-6 times larger than in atomic resolution crystal structures.

Source: Computational Biology and Chemistry

DOI: 10.1016/j.compbiolchem.2024.108069

Author: Oliviero Carugo

Institutions: University of Vienna, University of Pavia, Max Perutz Labs

Language: English

Topic: Protein Structure and Dynamics

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: hybrid

Estimated APC paid: $3,080

Funders: Ministero dell’Istruzione, dell’Università e della Ricerca, Università degli Studi di Pavia