AlphaFold predictions are valuable hypotheses and accelerate but do not replace experimental structure determination

Thomas C. Terwilliger, Dorothee Claudia Liebschner, Tristan Ian Croll, Christopher J. Williams, Airlie J. McCoy, Billy K. Poon, Pavel V. Afonine, Robert D. Oeffner, Jane S. Richardson, Randy J. Read, Paul D. Adams

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Abstract

Abstract AI-based methods such as AlphaFold have revolutionized structural biology, often making it possible to predict protein structures with high accuracy. The accuracies of these predictions vary, however, and they do not include ligands, covalent modifications or other environmental factors. Here we focus on very-high-confidence parts of AlphaFold predictions, evaluating how well they can be expected to describe the structure of a protein in a particular environment. We compare predictions with experimental crystallographic maps of the same proteins for 102 crystal structures. In many cases, those parts of AlphaFold predictions that were predicted with very high confidence matched experimental maps remarkably closely. In other cases, these predictions differed from experimental maps on a global scale through distortion and domain orientation, and on a local scale in backbone and side-chain conformation. Overall, C α atoms in very-high-confidence parts of AlphaFold predictions differed from corresponding crystal structures by a median of 0.6 Å, and about 10% of these differed by more than 2 Å, each about twice the values found for pairs of crystal structures containing the same components but determined in different space groups. We suggest considering AlphaFold predictions as exceptionally useful hypotheses. We further suggest that it is important to consider the confidence in prediction when interpreting AlphaFold predictions and to carry out experimental structure determination to verify structural details, particularly those that involve interactions not included in the prediction.

Abstract of "AlphaFold predictions are valuable hypotheses and accelerate but do not replace experimental structure determination" by Thomas C. Terwilliger, Dorothee Claudia Liebschner, Tristan Ian Croll et al., https://doi.org/10.1038/s41592-023-02087-4, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified.

Record

Archive ID
doi:10.1038/s41592-023-02087-4
Published
Nov 30, 2023
Venue
Nature Methods
DOI
10.1038/s41592-023-02087-4
PubMed
38036854
PMC
PMC10776388
Categories
Protein Structure and Dynamics
License
cc-by
Provenance
openalex+europepmc

Topics