Inferring Stabilizing Mutations from Protein Phylogenies: Application to Influenza Hemagglutinin

By Jesse D. Bloom, Matthew J. Glassman. 2009

63 citations recorded by the source corpus.

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.

Subfields: Molecular Biology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Molecular Biology

Citations in the corpus

Coevolutionary Landscape Inference and the Context-Dependence of Mutations in Beta-Lactamase TEM-1 (2015, background): “Critically important residues tend to be conserved, while unfavorable residues are observed less frequently.”
A fundamental protein property, thermodynamic stability, revealed solely from large-scale measurements of protein function (2012, background): “Positions of previously known (superscript 1) and previously unknown (superscript 2) validated stabilizing mutations (20, 30, 34, 35) are highlighted.”
Mutational effects on stability are largely conserved during protein evolution (2013, background): “Rather, the underlying preferences of sites for specific stabilizing residues is well conserved, explaining why mutations to consensus amino acids tend to stabilize proteins (40–42) and why a mutation’s effect on stability is correlated with its rate of fixation (45).”
Consensus protein design (2016, methodology): “Bias reduction of natural sequences can be performed with relative ease using the sequence clustering software CD-HIT (Huang et al., 2010) or by using likelihood-based methods to account for phylogeny (Bloom and Glassman, 2009).”
Relationship between protein thermodynamic constraints and variation of evolutionary rates among sites (2014, methodology): “…steady-state distribution of Δ G extra values, p 0 (Δ G extra ), so that we can write the unconditional fixation probability as (7) For p 0 (Δ G extra ), Bloom & Glassman (2009) make the ansatz that it has an exponential probability-density function p 0 (Δ G extra ): (8) where α > 0 is a free…”