Crius: A novel fragment‐based algorithm of de novo substrate prediction for enzymes
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 su...
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Online Access: | http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6153407/ http://www.ncbi.nlm.nih.gov/pubmed/29722450 https://doi.org/10.1002/pro.3437 |
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ftpubmed:oai:pubmedcentral.nih.gov:6153407 2023-05-15T13:59:25+02:00 Crius: A novel fragment‐based algorithm of de novo substrate prediction for enzymes Yao, Zhiqiang Jiang, Shuiqin Zhang, Lujia Gao, Bei He, Xiao Zhang, John Z. H. Wei, Dongzhi 2018-07-18 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6153407/ http://www.ncbi.nlm.nih.gov/pubmed/29722450 https://doi.org/10.1002/pro.3437 en eng John Wiley and Sons Inc. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6153407/ http://www.ncbi.nlm.nih.gov/pubmed/29722450 http://dx.doi.org/10.1002/pro.3437 © 2018 The Protein Society Tools for Protein Science Text 2018 ftpubmed https://doi.org/10.1002/pro.3437 2019-08-04T00:17:51Z 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. Text Antarc* Antarctica PubMed Central (PMC) Protein Science 27 8 1526 1534 |
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Tools for Protein Science |
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Tools for Protein Science Yao, Zhiqiang Jiang, Shuiqin Zhang, Lujia Gao, Bei He, Xiao Zhang, John Z. H. Wei, Dongzhi Crius: A novel fragment‐based algorithm of de novo substrate prediction for enzymes |
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Tools for Protein Science |
description |
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. |
format |
Text |
author |
Yao, Zhiqiang Jiang, Shuiqin Zhang, Lujia Gao, Bei He, Xiao Zhang, John Z. H. Wei, Dongzhi |
author_facet |
Yao, Zhiqiang Jiang, Shuiqin Zhang, Lujia Gao, Bei He, Xiao Zhang, John Z. H. Wei, Dongzhi |
author_sort |
Yao, Zhiqiang |
title |
Crius: A novel fragment‐based algorithm of de novo substrate prediction for enzymes |
title_short |
Crius: A novel fragment‐based algorithm of de novo substrate prediction for enzymes |
title_full |
Crius: A novel fragment‐based algorithm of de novo substrate prediction for enzymes |
title_fullStr |
Crius: A novel fragment‐based algorithm of de novo substrate prediction for enzymes |
title_full_unstemmed |
Crius: A novel fragment‐based algorithm of de novo substrate prediction for enzymes |
title_sort |
crius: a novel fragment‐based algorithm of de novo substrate prediction for enzymes |
publisher |
John Wiley and Sons Inc. |
publishDate |
2018 |
url |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6153407/ http://www.ncbi.nlm.nih.gov/pubmed/29722450 https://doi.org/10.1002/pro.3437 |
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Antarc* Antarctica |
genre_facet |
Antarc* Antarctica |
op_relation |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6153407/ http://www.ncbi.nlm.nih.gov/pubmed/29722450 http://dx.doi.org/10.1002/pro.3437 |
op_rights |
© 2018 The Protein Society |
op_doi |
https://doi.org/10.1002/pro.3437 |
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Protein Science |
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27 |
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8 |
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1526 |
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1534 |
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1766267962005651456 |