Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published April 17, 2009 | Published
Journal Article Open

Inferring stabilizing mutations from protein phylogenies : application to influenza hemagglutinin

Abstract

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.

Additional Information

Copyright: � 2009 Bloom, Glassman. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Received: November 19, 2008; Accepted: March 5, 2009; Published: April 17, 2009 We thank Dr. David Baltimore for his tremendous scientific guidance and advice, as well as his support in providing the infrastructure for the experimental work. The authors have declared that no competing interests exist. JDB was supported by a Beckman Institute Postdoctoral Fellowship and the Irvington Institute Fellowship Program of the Cancer Research Institute. MJG was supported by the Rose Hills Foundation and a Summer Undergraduate Research Fellowship from the California Institute of Technology. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Attached Files

Published - Bloom2009p4248Plos_Comput_Biol.pdf

Files

Bloom2009p4248Plos_Comput_Biol.pdf
Files (1.5 MB)
Name Size Download all
md5:47f2d7a79af22f582543464d1686d221
1.5 MB Preview Download

Additional details

Created:
August 20, 2023
Modified:
October 18, 2023