Co-evolutionary distance predictions contain flexibility information.

Journal: Bioinformatics (Oxford, England)
Published Date:

Abstract

MOTIVATION: Co-evolution analysis can be used to accurately predict residue-residue contacts from multiple sequence alignments. The introduction of machine-learning techniques has enabled substantial improvements in precision and a shift from predicting binary contacts to predict distances between pairs of residues. These developments have significantly improved the accuracy of de novo prediction of static protein structures. With AlphaFold2 lifting the accuracy of some predicted protein models close to experimental levels, structure prediction research will move on to other challenges. One of those areas is the prediction of more than one conformation of a protein. Here, we examine the potential of residue-residue distance predictions to be informative of protein flexibility rather than simply static structure.

Authors

  • Dominik Schwarz
    Department of Statistics, University of Oxford, Oxford OX1 3LB, UK.
  • Guy Georges
    a Roche Pharmaceutical Research and Early Development, Large Molecule Research, Roche Innovation Center Penzberg , Nonnenwald 2, Penzberg , Germany.
  • Sebastian Kelm
    Department of Informatics, UCB Pharma, Slough, UK.
  • Jiye Shi
    UCB Pharma, Slough, Berkshire SL1 3WE, U.K.
  • Anna Vangone
    Bijvoet Center for Biomolecular Research, Faculty of Science - Chemistry, Utrecht University, Utrecht, The Netherlands.
  • Charlotte M Deane
    Oxford Protein Informatics Group, Department of Statistics, University of Oxford, Oxford, United Kingdom.