Geng, FengFengGengMa, Cheng-WeiCheng-WeiMaZeng, An-PingAn-PingZeng2019-08-302019-08-302017-02-09Biotechnology Letters 4 (39): 599-605 (2017-04-01)http://hdl.handle.net/11420/3232Objective: To re-engineer the active site of proteins for non-natural substrates using a position-based prediction method (PBPM). Results: The approach has been applied to re-engineer the E. coli glutamate dehydrogenase to alter its substrate from glutamate to homoserine for a de novo 1,3-propanediol biosynthetic pathway. After identification of key residues that determine the substrate specificity, residue K92 was selected as a candidate site for mutation. Among the three mutations (K92V, K92C, and K92M) suggested by PBPM, the specific activity of the best mutant (K92 V) was increased from 171 ± 35 to 1328 ± 71 μU mg−1. Conclusion: The PBPM approach has a high efficiency for re-engineering the substrate specificity of natural enzymes for new substrates.en1573-677620174599605Springer Science + Business Media B.VEnzyme designGlutamate dehydrogenaseHomoserinePosition-based prediction method1,3-PropanediolProtein engineeringSubstrate specificityBiowissenschaften, BiologieMedizinJournal Article10.1007/s10529-017-2297-2Other