Sequence optimization for native state stability determines the evolution and folding kinetics of a small protein.
Investigating the relative importance of protein stability, function, and folding kinetics in driving protein evolution has long been hindered by the fact that we can only compare modern natural proteins, the products of the very process we seek to understand, to each other, with no external references or baselines. Through a large-scale all-atom simulation of protein evolution, we have created a large diverse alignment of SH3 domain sequences which have been selected only for native state stability, with no other influencing factors. Although the average pairwise identity between computationally evolved and natural sequences is only 17%, the residue frequency distributions of the computationally evolved sequences are similar to natural SH3 sequences at 86% of the positions in the domain, suggesting that optimization for the native state structure has dominated the evolution of natural SH3 domains. Additionally, the positions which play a consistent role in the transition state of three well-characterized SH3 domains (by phi-value analysis) are structurally optimized for the native state, and vice versa. Indeed, we see a specific and significant correlation between sequence optimization for native state stability and conservation of transition state structure.
Larson
Stefan M
SM
Department of Chemistry and Biophysics Program, Stanford University, Stanford, CA 94305-5080, USA.
Pande
Vijay S
VS
D000595:Amino Acid Sequence; D030562:Databases, Protein; D019143:Evolution, Molecular; D017510:Protein Folding; D011506:Proteins / Q000737:chemistry*; D016415:Sequence Alignment; D018909:src Homology Domains
D011506:Proteins