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

Journal: Nature methods
PMID: 38036854

Abstract

Artificial intelligence-based protein structure prediction methods such as AlphaFold have revolutionized structural biology. The accuracies of these predictions vary, however, and they do not take into account ligands, covalent modifications or other environmental factors. Here, we evaluate how well AlphaFold predictions can be expected to describe the structure of a protein by comparing predictions directly with experimental crystallographic maps. In many cases, AlphaFold predictions matched experimental maps remarkably closely. In other cases, even very high-confidence 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. 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.

Authors

  • Thomas C Terwilliger
    New Mexico Consortium, Los Alamos, NM 87544, USA.
  • Dorothee Liebschner
    Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.
  • Tristan I Croll
    Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Hills Road, Cambridge CB2 0XY, United Kingdom.
  • Christopher J Williams
    Department of Biochemistry, Duke University, Durham, NC 27710, USA.
  • Airlie J McCoy
    Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Hills Road, Cambridge CB2 0XY, United Kingdom.
  • Billy K Poon
    Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.
  • Pavel V Afonine
    Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.
  • Robert D Oeffner
    Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Hills Road, Cambridge CB2 0XY, United Kingdom.
  • Jane S Richardson
    Department of Biochemistry, Duke University, Durham, NC 27710, USA.
  • Randy J Read
    Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Cambridge, UK.
  • Paul D Adams
    Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.

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