Abstract
A critical question in biology is the identification of functionally important amino acid sites in proteins. Because functionally important sites are under stronger purifying selection, site-specific substitution rates tend to be lower than usual at these sites. A large number of phylogenetic models have been developed to estimate site-specific substitution rates in proteins and the extraordinarily low substitution rates have been used as evidence of function. Most of the existing tools, e.g. Rate4Site, assume that site-specific substitution rates are independent across sites. However, site-specific substitution rates may be strongly correlated in the protein tertiary structure, since functionally important sites tend to be clustered together to form functional patches. We have developed a new model, GP4Rate, which incorporates the Gaussian process model with the standard phylogenetic model to identify slowly evolved regions in protein tertiary structures. GP4Rate uses the Gaussian process to define a nonparametric prior distribution of site-specific substitution rates, which naturally captures the spatial correlation of substitution rates. Simulations suggest that GP4Rate can potentially estimate site-specific substitution rates with a much higher accuracy than Rate4Site and tends to report slowly evolved regions rather than individual sites. In addition, GP4Rate can estimate the strength of the spatial correlation of substitution rates from the data. By applying GP4Rate to a set of mammalian B7-1 genes, we found a highly conserved region which coincides with experimental evidence. GP4Rate may be a useful tool for the in silico prediction of functionally important regions in the proteins with known structures.
Highlights
An important question in biology is the identification of functional residues in proteins
If we image each residue in a protein tertiary structure as a single point in the 3D space, the Gaussian process can be used to define a prior distribution of site-specific log substitution rates over these points
Rate4Site is used as a representative of the classic phylogenetic models which use the discrete Gamma distribution to describe the variation of substitution rates across sites [25] but do not consider the spatial correlation of site-specific substitution rates in the protein tertiary structure
Summary
An important question in biology is the identification of functional residues in proteins. A number of bioinformatics tools based on phylogenetics have been developed to infer functional sites by the simple idea that functionally important amino acid sites tend to be more conserved than unimportant ones [2,3,4,5,6,7,8,9,10,11]. Given the multiple sequence alignment and the phylogenetic tree of a protein family, these phylogenetic methods can infer the amino acid substitution rate at each site in the alignment and an unusually low substitution rate implies that the site is functionally important. It has been shown that the predicted conserved sites coincide with experimental evidence, which confirms that these bioinformatics tools are useful These existing methods are far from flawless. Several methods have been developed to incorporate the spatial correlation of evolutionary patterns, e.g. substitution rates at the protein level or dN/dS ratios at the codon level, to overcome the
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