Evolutionary inferences from protein-coding genes

描述（由申请人提供）：蛋白质三级结构在进化过程中变化缓慢。如果核苷酸取代导致氨基酸取代破坏蛋白质结构，则核苷酸取代率预计会很低。氨基酸置换对三级结构的影响不仅取决于参与置换的残基，还取决于在空间上靠近置换位点的残基。蛋白质结构和蛋白质变化之间的这种关系导致了蛋白质编码基因位置之间的进化依赖。不幸的是，广泛使用的蛋白质编码基因进化模型忽略了这种依赖性。

DESCRIPTION (provided by applicant): Protein tertiary structure changes slowly during evolution. Nucleotide substitution rates are expected to be low if they result in an amino acid replacement that disrupts protein structure. The effect of an amino acid replacement on tertiary structure is determined not only by the residues involved in the replacement but also by the residues that are spatially nearby the site that experiences the replacement. This relationship between protein structure and protein change induces an evolutionary dependence among the positions in the protein-coding genes. Unfortunately, widely used models for the evolution of protein-coding genes ignore this dependence. The research in this project will build upon a newly developed statistical technique for making evolutionary inferences from sequence pairs. This new technique incorporates dependence among codons due to pain/vise amino acid interactions that are imposed by the protein tertiary structure. The initial focus will be to extend this model-based approach to the analysis of more than two phylogenetically-related sequences. The resulting method will be a powerful tool for characterizing the impact of protein structure on protein evolution. The Pandit database of aligned protein-coding DMA sequences will be mined to assess which protein families evolve under the most and least influence of tertiary structure. Evidence of positive selection in this database will be identified and the issue of whether the strength of the relationship between protein structure and protein evolution varies among taxonomic groups will be addressed. To complement the empirical studies and to further evaluate the new methodology, simulations will be performed. In addition, the possibility of allowing protein tertiary structure to change over time will be explored. Ancestral sequence inference that accounts for covarying positions and the potential for applying ancestral sequence inference to vaccine design is another topic of interest. Although the emphasis of this project is evolutionary dependence among codons due to protein structure, the statistical approach is quite general and could be applied to diverse cases of evolutionary dependence where surrogates for sequence fitness can be measured or modeled.