Enzyme modification using mutation site prediction method for enhancing the regioselectivity of substrate reaction sites

Abstract Enzymes with low regioselectivity of substrate reaction sites may produce multiple products from a single substrate. When a target product is produced industrially using these enzymes, the production of non-target products (byproducts) causes adverse effects such as increased processing cos...

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Autores principales:	Jinzen Ikebe, Munenori Suzuki, Aya Komori, Kaito Kobayashi, Tomoshi Kameda
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/3b5e11fddab54ea69e607d30ff4b5269
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spelling	oai:doaj.org-article:3b5e11fddab54ea69e607d30ff4b52692021-12-02T16:57:08ZEnzyme modification using mutation site prediction method for enhancing the regioselectivity of substrate reaction sites10.1038/s41598-021-98433-72045-2322https://doaj.org/article/3b5e11fddab54ea69e607d30ff4b52692021-10-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-98433-7https://doaj.org/toc/2045-2322Abstract Enzymes with low regioselectivity of substrate reaction sites may produce multiple products from a single substrate. When a target product is produced industrially using these enzymes, the production of non-target products (byproducts) causes adverse effects such as increased processing costs for purification and the amount of raw material. Thus it is required the development of modified enzymes to reduce the amount of byproducts’ production. In this paper, we report a method called mutation site prediction for enhancing the regioselectivity of substrate reaction sites (MSPER). MSPER takes conformational data for docking poses of an enzyme and a substrate as input and automatically generates a ranked list of mutation sites to destabilize docking poses for byproducts while maintaining those for target products in silico. We applied MSPER to the enzyme cytochrome P450 CYP102A1 (BM3) and the two substrates to enhance the regioselectivity for four target products with different reaction sites. The 13 of the total 14 top-ranked mutation sites predicted by MSPER for the four target products succeeded in selectively enhancing the regioselectivity up to 6.4-fold. The results indicate that MSPER can distinguish differences of substrate structures and the reaction sites, and can accurately predict mutation sites to enhance regioselectivity without selection by directed evolution screening.Jinzen IkebeMunenori SuzukiAya KomoriKaito KobayashiTomoshi KamedaNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Jinzen Ikebe Munenori Suzuki Aya Komori Kaito Kobayashi Tomoshi Kameda Enzyme modification using mutation site prediction method for enhancing the regioselectivity of substrate reaction sites
description	Abstract Enzymes with low regioselectivity of substrate reaction sites may produce multiple products from a single substrate. When a target product is produced industrially using these enzymes, the production of non-target products (byproducts) causes adverse effects such as increased processing costs for purification and the amount of raw material. Thus it is required the development of modified enzymes to reduce the amount of byproducts’ production. In this paper, we report a method called mutation site prediction for enhancing the regioselectivity of substrate reaction sites (MSPER). MSPER takes conformational data for docking poses of an enzyme and a substrate as input and automatically generates a ranked list of mutation sites to destabilize docking poses for byproducts while maintaining those for target products in silico. We applied MSPER to the enzyme cytochrome P450 CYP102A1 (BM3) and the two substrates to enhance the regioselectivity for four target products with different reaction sites. The 13 of the total 14 top-ranked mutation sites predicted by MSPER for the four target products succeeded in selectively enhancing the regioselectivity up to 6.4-fold. The results indicate that MSPER can distinguish differences of substrate structures and the reaction sites, and can accurately predict mutation sites to enhance regioselectivity without selection by directed evolution screening.
format	article
author	Jinzen Ikebe Munenori Suzuki Aya Komori Kaito Kobayashi Tomoshi Kameda
author_facet	Jinzen Ikebe Munenori Suzuki Aya Komori Kaito Kobayashi Tomoshi Kameda
author_sort	Jinzen Ikebe
title	Enzyme modification using mutation site prediction method for enhancing the regioselectivity of substrate reaction sites
title_short	Enzyme modification using mutation site prediction method for enhancing the regioselectivity of substrate reaction sites
title_full	Enzyme modification using mutation site prediction method for enhancing the regioselectivity of substrate reaction sites
title_fullStr	Enzyme modification using mutation site prediction method for enhancing the regioselectivity of substrate reaction sites
title_full_unstemmed	Enzyme modification using mutation site prediction method for enhancing the regioselectivity of substrate reaction sites
title_sort	enzyme modification using mutation site prediction method for enhancing the regioselectivity of substrate reaction sites
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/3b5e11fddab54ea69e607d30ff4b5269
work_keys_str_mv	AT jinzenikebe enzymemodificationusingmutationsitepredictionmethodforenhancingtheregioselectivityofsubstratereactionsites AT munenorisuzuki enzymemodificationusingmutationsitepredictionmethodforenhancingtheregioselectivityofsubstratereactionsites AT ayakomori enzymemodificationusingmutationsitepredictionmethodforenhancingtheregioselectivityofsubstratereactionsites AT kaitokobayashi enzymemodificationusingmutationsitepredictionmethodforenhancingtheregioselectivityofsubstratereactionsites AT tomoshikameda enzymemodificationusingmutationsitepredictionmethodforenhancingtheregioselectivityofsubstratereactionsites
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Enzyme modification using mutation site prediction method for enhancing the regioselectivity of substrate reaction sites

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