@article{a1ac40181f3842569cf5746e940a5873,
title = "Crius: A novel fragment-based algorithm of de novo substrate prediction for enzymes",
abstract = "The study of enzyme substrate specificity is vital for developing potential applications of enzymes. However, the routine experimental procedures require lot of resources in the discovery of novel substrates. This article reports an in silico structure-based algorithm called Crius, which predicts substrates for enzyme. The results of this fragment-based algorithm show good agreements between the simulated and experimental substrate specificities, using a lipase from Candida antarctica (CALB), a nitrilase from Cyanobacterium syechocystis sp. PCC6803 (Nit6803), and an aldo-keto reductase from Gluconobacter oxydans (Gox0644). This opens new prospects of developing computer algorithms that can effectively predict substrates for an enzyme.",
keywords = "enzyme selectivity, fragment-based algorithm, substrate prediction, substrate specificity",
author = "Zhiqiang Yao and Shuiqin Jiang and Lujia Zhang and Bei Gao and Xiao He and Zhang, {John Z.H.} and Dongzhi Wei",
note = "Funding Information: Grant sponsor: National Key R&D Program of China; Grant number: 2016YFA0501701; Grant sponsor: National Natural Science Foundation of China; Grant numbers: 31571786 and 31772007; Grant sponsor: Natural Science Foundation of Shanghai; Grant number: 16ZR1449500; Grant sponsor: Innovation Program of Shanghai Municipal Education Commission; Grant number: 201701070005E00020; Grant sponsor: Open Funding Project of the State Key Laboratory of Bioreactor Engineering and the Special Program for Applied Research on Super Computation of the NSFC-Guangdong Joint Fund (the second phase; Grant number: U1501501. Funding Information: The authors thank professor Romas Kazlauskas for helpful discussions and insightful suggestions. This work was supported by National Natural Science Foundation of China [No. 31772007 and No. 31571786], National Basic Research Program of China (973) [No. 2012CB721003], Natural Science Foundation of Shanghai [No. 16ZR1449500], Open Funding Project of the State Key Laboratory of Bioreactor Engineering and Special Program for Applied Research on Super Computation of the NSFC-Guangdong.",
year = "2018",
month = aug,
doi = "10.1002/pro.3437",
language = "English (US)",
volume = "27",
pages = "1526--1534",
journal = "Protein Science",
issn = "0961-8368",
publisher = "Cold Spring Harbor Laboratory Press",
number = "8",
}