ИСТИНА

Understanding how do changes in protein sequence affect biological function and structure has been a subject of discussion. Homologous enzymes evolved from a common ancestor to retain a general function but diverged in more specific features and can be divided into subfamilies with different functional properties such as specificity, enantioselectivity, stability, etc. Why do similar active sites in homologous enzymes perform different chemical transformations and how can we change enzyme function and create novel biocatalysts? Recent improvement of computational resources and expansion of protein databases due to rapid increase of sequencing and structure determination projects now offer a key to break this "nature code" by sequence and structural analysis of the mutations that survived evolution and how they correlate in protein superfamilies. New method of bioinformatic analysis has been developed [1, 2] to identify subfamily-specific positions (SSPs) – conserved only within protein subfamilies, but different between subfamilies – that seem to play important role in discrimination of substrate specificity, catalytic activity, stability, etc. The method was applied to study how lipase and amidase catalytic activities are implemented into the alpha-beta hydrolase fold. Subfamily-specific positions of α/β-hydrolases with lipase and protease activities were identified and used as hotspots to introduce amidase activity into Candida antarctica lipase B (CALB). Molecular modeling was used to evaluate influence of selected residues on binding and catalytic conversion of amide substrate by corresponding in silico library of mutants and to select reactive enzyme-substrate complexes that satisfy knowledge-based criteria of amidase catalytic activity. Selected CALB variants were produced and showed significant improvement of experimentally measured amidase activity [3, 4]. The developed method was also applied to study evolution of structure-functional relationship in other enzyme families: Ntn-hydrolases, penicillin-binding proteins, etc. It was shown, that patterns of SSPs can be effectively used to design enzyme mutants with improved functional properties. Based on these results, we suggest that bioinformatic analysis can be applied to explore structure-functional relationship in enzymes and to select highly significant subfamily-specific positions as hotspots for directed evolution or rational design experiments. [1] Suplatov, et.al. (2013) J Biomol Struct Dyn, doi:10.1080/07391102.2012.750249. [2] http://biokinet.belozersky.msu.ru/zebra [3] Suplatov, et.al. (2011) Acta Naturae, 3(1), 93-98. [4] Suplatov, et.al. (2012) Protein Eng Des Sel, 25(11), 689-697.