Accuracy of AlphaFold models: Comparison with short N < sup > < sub > … < /sub > < /sup > O contacts in atomic resolution protein crystal structures

Comput Biol Chem. 2024 Apr 4;110:108069. doi: 10.1016/j.compbiolchem.2024.108069. Online ahead of print.ABSTRACTArtificial 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.PMID:38581839 | DOI:10.1016/j.compbiolchem.2024.108069
Source: Computational Biology and Chemistry - Category: Bioinformatics Authors: Source Type: research