b-Glucosidase is a class of hydrolytic enzymes that catalyzes the removal of the non-reducing b-D-glucosyl unit from various disaccharides and substituted b-D-glucosides. b-Glucosidase belongs to Glycoside Hydrolase (GH) families 1 and 3 and potentially has many biotechnological applications with thermostable enzymes are preferred over mesophilic homologs in different applications. In the present work, a comparative analysis of physicochemical properties and amino acids composition of 60 (20 mesophilic, 20 thermophilic and 20 hyperthermophilic) b-glucosidases were performed. Multiple sequence alignment and phylogenetic tree analysis were constructed. Analysis of Variance (ANOVA) showed that several physicochemical properties including molecular weight, isoelectric point, number of positively charged amino acids, and extinction coefficient are statistically different among b-glucosidases groups (P<0.05). The analysis also showed that content of amino acids Asp, Gln, Cys, His, and Thr is significantly higher in mesophilic enzymes whereas that of Glu, Lys, Tyr, and Trp is higher in thermo- and hyperthermostable homologs (P<0.05). Overall, nonpolar amino acids were the most abundant amino acids group in b-glucosidase with no significant difference among meso-, thermo-, and hyperthermophilic enzymes. Conversely, the content of polar amino acids is statistically higher (P<0.05) in mesophilic enzymes whereas that of charged and aromatic amino acids is significantly higher (P<0.05) in thermo- and hyperthermophilic counterparts. Finally, multiple regression analysis showed that both polar and aromatic amino acids contribute significantly (P<0.05) to the thermostability. Optimal temperature variation of 53% could be explained by these two groups of amino acids. In conclusion, several amino acids appear to contribute to the thermostability of b-glucosidases and the findings from this study should pave the road toward a better understanding of thermostability of b-glucosidases and protein engineering.
b-Glucosidase, thermostability, amino acid composition, physicochemical properties, ANOVA, Regression.
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