Inferring Stabilizing Mutations from Protein Phylogenies: Application to Influenza Hemagglutinin

Bloom, Jesse D.; Glassman, Matthew

doi:10.1371/journal.pcbi.1000349

Cited by 64 publications

(78 citation statements)

References 123 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The general consensus is that amino acid frequencies follow a Boltzmann distribution. The individual frequencies at sites can be calculated either from stability effects [DDG values (Dokholyan and Shakhnovich 2001;Dokholyan et al 2002;GodoyRuiz et al 2004;Bloom and Glassman 2009;Schmidt am Busch et al 2010] or from the protein's connectivity matrix (Porto et al 2004;Bastolla et al 2005;Pokarowski et al 2005;Wolff et al 2008;Bastolla et al 2008). In particular, Porto et al (2004) showed that the frequency of amino acid a is proportional to e 2bh(a) , where b measures properties of the site under consideration and h(a) measures properties of the amino acid.…”

Section: Resultsmentioning

confidence: 99%

The Relationship Between Relative Solvent Accessibility and Evolutionary Rate in Protein Evolution

Ramsey

Scherrer

Zhou³

et al. 2011

Genetics

127

139

View full text Add to dashboard Cite

Recent work with Saccharomyces cerevisiae shows a linear relationship between the evolutionary rate of sites and the relative solvent accessibility (RSA) of the corresponding residues in the folded protein. Here, we aim to develop a mathematical model that can reproduce this linear relationship. We first demonstrate that two models that both seem reasonable choices (a simple model in which selection strength correlates with RSA and a more complex model based on RSA-dependent amino acid distributions) fail to reproduce the observed relationship. We then develop a model on the basis of observed site-specific amino acid distributions and show that this model behaves appropriately. We conclude that evolutionary rates are directly linked to the distribution of amino acids at individual sites. Because of this link, any future insight into the biophysical mechanisms that determine amino acid distributions will improve our understanding of evolutionary rates.T HE requirement for successful and efficient protein folding imposes significant biophysical constraints on coding sequences. These constraints shape how sequences evolve. Mutations that interfere with correct folding will generally be removed by purifying selection. Likewise, mutations that do not interfere with folding are often neutral, or nearly so, and accumulate over time. As a consequence of this interaction between protein biophysics and molecular evolution, signatures of protein structure can be found in the divergence

show abstract

Section: Resultsmentioning

confidence: 99%

The Relationship Between Relative Solvent Accessibility and Evolutionary Rate in Protein Evolution

Ramsey

Scherrer

Zhou³

et al. 2011

Genetics

127

139

View full text Add to dashboard Cite

show abstract

“…Computational methods generally rely on physicochemical models to estimate the thermodynamic impact of mutations (28,29). Stabilizing mutations can also be identified by analyzing evolutionary conservation or proteins from hyperthermophilic organisms (30,31). Rational design draws on protein structure as well as the knowledge of the experimenter to predict stabilizing mutations (32).…”

Section: Discussionmentioning

confidence: 99%

A fundamental protein property, thermodynamic stability, revealed solely from large-scale measurements of protein function

Araya¹,

Fowler

Chen³

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

240

264

View full text Add to dashboard Cite

The ability of a protein to carry out a given function results from fundamental physicochemical properties that include the protein's structure, mechanism of action, and thermodynamic stability. Traditional approaches to study these properties have typically required the direct measurement of the property of interest, oftentimes a laborious undertaking. Although protein properties can be probed by mutagenesis, this approach has been limited by its low throughput. Recent technological developments have enabled the rapid quantification of a protein's function, such as binding to a ligand, for numerous variants of that protein. Here, we measure the ability of 47,000 variants of a WW domain to bind to a peptide ligand and use these functional measurements to identify stabilizing mutations without directly assaying stability. Our approach is rooted in the well-established concept that protein function is closely related to stability. Protein function is generally reduced by destabilizing mutations, but this decrease can be rescued by stabilizing mutations. Based on this observation, we introduce partner potentiation, a metric that uses this rescue ability to identify stabilizing mutations, and identify 15 candidate stabilizing mutations in the WW domain. We tested six candidates by thermal denaturation and found two highly stabilizing mutations, one more stabilizing than any previously known mutation. Thus, physicochemical properties such as stability are latent within these large-scale protein functional data and can be revealed by systematic analysis. This approach should allow other protein properties to be discovered.deep mutational scanning | epistasis | high-throughput DNA sequencing

show abstract

“…Whereas such epistasis between counterbalancing mutations can cause transient fluctuations in the rate of substitution (44), it does not drive systematic shifts in substitution patterns. 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)(41)(42) and why a mutation's effect on stability is correlated with its rate of fixation (45).…”

Section: Discussionmentioning

confidence: 99%

Mutational effects on stability are largely conserved during protein evolution

Ashenberg

Gong

Bloom

2013

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

136

154

View full text Add to dashboard Cite

Protein stability and folding are the result of cooperative interactions among many residues, yet phylogenetic approaches assume that sites are independent. This discrepancy has engendered concerns about large evolutionary shifts in mutational effects that might confound phylogenetic approaches. Here we experimentally investigate this issue by introducing the same mutations into a set of diverged homologs of the influenza nucleoprotein and measuring the effects on stability. We find that mutational effects on stability are largely conserved across the homologs. We reach qualitatively similar conclusions when we simulate protein evolution with molecular-mechanics force fields. Our results do not mean that proteins evolve without epistasis, which can still arise even when mutational stability effects are conserved. However, our findings indicate that large evolutionary shifts in mutational effects on stability are rare, at least among homologs with similar structures and functions. We suggest that properly describing the clearly observable and highly conserved amino acid preferences at individual sites is likely to be far more important for phylogenetic analyses than accounting for rare shifts in amino acid propensities due to site covariation.heterotachy | consensus design | substitution models M ost biological proteins stably fold to a well-defined native structure (1). Stable folding to the native structure is typically essential for a protein to perform its evolutionarily selected function. Stability and folding are the result of highly cooperative interactions among a protein's constituent amino acids (1). Therefore, evolutionary selection at a site in a protein acts on properties that in principle are determined by interactions of that site with every other position in the sequence.However, phylogenetic approaches assume that protein sites evolve independently. This assumption has historically been justified primarily by pragmatic considerations. If substitution models are site independent, then the evolution of each site is mathematically described by a 20 × 20 matrix, with entries corresponding to all amino acid interchanges at that site. On the other hand, if each site depends upon all other sites, then the evolution of a protein of length L is mathematically described by a 20 L × 20 L matrix, with entries corresponding to all interchanges among the 20 L sequences. Even for a small protein of length L = 100, the number of entries in such a matrix vastly exceeds the number of atoms in the universe, which poses severe computational challenges.The fact that sites are not actually independent at the physicochemical level has provoked concern about the use of siteindependent substitution models (2-5). Pollock et al. (2) have used computer simulations to suggest that there are widespread evolutionary shifts in mutational effects, where for instance a mutation is destabilizing in one homolog but stabilizing in another homolog due to interactions with other covarying sites. They have argued that such evolutionary...

show abstract

Inferring Stabilizing Mutations from Protein Phylogenies: Application to Influenza Hemagglutinin

Cited by 64 publications

References 123 publications

The Relationship Between Relative Solvent Accessibility and Evolutionary Rate in Protein Evolution

The Relationship Between Relative Solvent Accessibility and Evolutionary Rate in Protein Evolution

A fundamental protein property, thermodynamic stability, revealed solely from large-scale measurements of protein function

Mutational effects on stability are largely conserved during protein evolution

Contact Info

Product

Resources

About