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Mutation effects predicted from sequence co-variation

2017; Nature Portfolio; Volume: 35; Issue: 2 Linguagem: Inglês

10.1038/nbt.3769

1546-1696

Thomas A. Hopf, John Ingraham, Frank J. Poelwijk, Charlotta Schärfe, Michael Springer, Chris Sander, Debora S. Marks,

Protein Structure and Dynamics

Modern biomedicine is challenged to predict the effects of genetic variation. Systematic functional assays of point mutants of proteins have provided valuable empirical information, but vast regions of sequence space remain unexplored. Fortunately, the mutation-selection process of natural evolution has recorded rich information in the diversity of natural protein sequences. Here, building on probabilistic models for correlated amino-acid substitutions that have been successfully applied to determine the three-dimensional structures of proteins, we present a statistical approach for quantifying the contribution of residues and their interactions to protein function, using a statistical energy, the evolutionary Hamiltonian. We find that these probability models predict the experimental effects of mutations with reasonable accuracy for a number of proteins, especially where the selective pressure is similar to the evolutionary pressure on the protein, such as antibiotics.