Crius: A novel fragment-based algorithm of de novo substrate prediction for enzymes

Zhiqiang Yao, Shuiqin Jiang, Lujia Zhang, Bei Gao, Xiao He, John Z.H. Zhang, Dongzhi Wei

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)1526-1534
Number of pages9
JournalProtein Science
Issue number8
StatePublished - Aug 2018


  • enzyme selectivity
  • fragment-based algorithm
  • substrate prediction
  • substrate specificity

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology


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