One selection pressure shaping sequence evolution is the requirement that a
protein fold with sufficient stability to perform its biological functions. We
present a conceptual framework that explains how this requirement causes the
probability that a particular amino acid mutation is fixed during evolution to
depend on its effect on protein stability. We mathematically formalize this
framework to develop a Bayesian approach for inferring the stability effects of
individual mutations from homologous protein sequences of known phylogeny. This
approach is able to predict published experimentally measured mutational
stability effects (ΔΔG values) with an accuracy
that exceeds both a state-of-the-art physicochemical modeling program and the
sequence-based consensus approach. As a further test, we use our phylogenetic
inference approach to predict stabilizing mutations to influenza hemagglutinin.
We introduce these mutations into a temperature-sensitive influenza virus with a
defect in its hemagglutinin gene and experimentally demonstrate that some of the
mutations allow the virus to grow at higher temperatures. Our work therefore
describes a powerful new approach for predicting stabilizing mutations that can
be successfully applied even to large, complex proteins such as hemagglutinin.
This approach also makes a mathematical link between phylogenetics and
experimentally measurable protein properties, potentially paving the way for
more accurate analyses of molecular evolution.