Accelerating crystal structure determination with iterative AlphaFold prediction.

Journal: Acta crystallographica. Section D, Structural biology
Published Date: Feb 27, 2023

Abstract

Experimental structure determination can be accelerated with artificial intelligence (AI)-based structure-prediction methods such as AlphaFold. Here, an automatic procedure requiring only sequence information and crystallographic data is presented that uses AlphaFold predictions to produce an electron-density map and a structural model. Iterating through cycles of structure prediction is a key element of this procedure: a predicted model rebuilt in one cycle is used as a template for prediction in the next cycle. This procedure was applied to X-ray data for 215 structures released by the Protein Data Bank in a recent six-month period. In 87% of cases our procedure yielded a model with at least 50% of C atoms matching those in the deposited models within 2 Å. Predictions from the iterative template-guided prediction procedure were more accurate than those obtained without templates. It is concluded that AlphaFold predictions obtained based on sequence information alone are usually accurate enough to solve the crystallographic phase problem with molecular replacement, and a general strategy for macromolecular structure determination that includes AI-based prediction both as a starting point and as a method of model optimization is suggested.

Authors

  • Thomas C Terwilliger
    New Mexico Consortium, Los Alamos, NM 87544, USA.
  • Pavel V Afonine
    Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, 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.
  • Airlie J McCoy
    Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Hills Road, Cambridge CB2 0XY, United Kingdom.
  • Robert D Oeffner
    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.
  • Billy K Poon
    Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.
  • 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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