| 초록 |
We propose a method, called RiSLnet (Rapid identification of Smart mutant Library using residue network), to identify neutral mutations by combining network analysis for protein residue interactions, identification of conserved residues, and evaluation of relative solvent accessibility. To validate its performance, the method was applied to four proteins, i.e. T4 lysozyme, ribonuclease H, barnase, and cold shock protein B. Our method predicted beneficial mutations in thermal stability with ca. 62% average accuracy. RiSLnet identified mutations increasing the thermal stability of lysine decarboxylase with the accuracy of ca. 60% and significantly reduced the number of candidate residues (~99%) for mutation. Finally, combination of beneficial mutants yielded a thermally stable triple mutant with the half-life (T1/2) of 114.9 min at 58°C, which is approximately two-fold higher than that of the wild-type. |
