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EHreact: Extended Hasse Diagrams for the Extraction and Scoring of Enzymatic Reaction Templates

[Image: see text] Data-driven computer-aided synthesis planning utilizing organic or biocatalyzed reactions from large databases has gained increasing interest in the last decade, sparking the development of numerous tools to extract, apply, and score general reaction templates. The generation of re...

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Autores principales: Heid, Esther, Goldman, Samuel, Sankaranarayanan, Karthik, Coley, Connor W., Flamm, Christoph, Green, William H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2021
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8549070/
https://www.ncbi.nlm.nih.gov/pubmed/34587449
http://dx.doi.org/10.1021/acs.jcim.1c00921
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author Heid, Esther
Goldman, Samuel
Sankaranarayanan, Karthik
Coley, Connor W.
Flamm, Christoph
Green, William H.
author_facet Heid, Esther
Goldman, Samuel
Sankaranarayanan, Karthik
Coley, Connor W.
Flamm, Christoph
Green, William H.
author_sort Heid, Esther
collection PubMed
description [Image: see text] Data-driven computer-aided synthesis planning utilizing organic or biocatalyzed reactions from large databases has gained increasing interest in the last decade, sparking the development of numerous tools to extract, apply, and score general reaction templates. The generation of reaction rules for enzymatic reactions is especially challenging since substrate promiscuity varies between enzymes, causing the optimal levels of rule specificity and optimal number of included atoms to differ between enzymes. This complicates an automated extraction from databases and has promoted the creation of manually curated reaction rule sets. Here, we present EHreact, a purely data-driven open-source software tool, to extract and score reaction rules from sets of reactions known to be catalyzed by an enzyme at appropriate levels of specificity without expert knowledge. EHreact extracts and groups reaction rules into tree-like structures, Hasse diagrams, based on common substructures in the imaginary transition structures. Each diagram can be utilized to output a single or a set of reaction rules, as well as calculate the probability of a new substrate to be processed by the given enzyme by inferring information about the reactive site of the enzyme from the known reactions and their grouping in the template tree. EHreact heuristically predicts the activity of a given enzyme on a new substrate, outperforming current approaches in accuracy and functionality.
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spelling pubmed-85490702021-10-27 EHreact: Extended Hasse Diagrams for the Extraction and Scoring of Enzymatic Reaction Templates Heid, Esther Goldman, Samuel Sankaranarayanan, Karthik Coley, Connor W. Flamm, Christoph Green, William H. J Chem Inf Model [Image: see text] Data-driven computer-aided synthesis planning utilizing organic or biocatalyzed reactions from large databases has gained increasing interest in the last decade, sparking the development of numerous tools to extract, apply, and score general reaction templates. The generation of reaction rules for enzymatic reactions is especially challenging since substrate promiscuity varies between enzymes, causing the optimal levels of rule specificity and optimal number of included atoms to differ between enzymes. This complicates an automated extraction from databases and has promoted the creation of manually curated reaction rule sets. Here, we present EHreact, a purely data-driven open-source software tool, to extract and score reaction rules from sets of reactions known to be catalyzed by an enzyme at appropriate levels of specificity without expert knowledge. EHreact extracts and groups reaction rules into tree-like structures, Hasse diagrams, based on common substructures in the imaginary transition structures. Each diagram can be utilized to output a single or a set of reaction rules, as well as calculate the probability of a new substrate to be processed by the given enzyme by inferring information about the reactive site of the enzyme from the known reactions and their grouping in the template tree. EHreact heuristically predicts the activity of a given enzyme on a new substrate, outperforming current approaches in accuracy and functionality. American Chemical Society 2021-09-29 2021-10-25 /pmc/articles/PMC8549070/ /pubmed/34587449 http://dx.doi.org/10.1021/acs.jcim.1c00921 Text en © 2021 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by/4.0/Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Heid, Esther
Goldman, Samuel
Sankaranarayanan, Karthik
Coley, Connor W.
Flamm, Christoph
Green, William H.
EHreact: Extended Hasse Diagrams for the Extraction and Scoring of Enzymatic Reaction Templates
title EHreact: Extended Hasse Diagrams for the Extraction and Scoring of Enzymatic Reaction Templates
title_full EHreact: Extended Hasse Diagrams for the Extraction and Scoring of Enzymatic Reaction Templates
title_fullStr EHreact: Extended Hasse Diagrams for the Extraction and Scoring of Enzymatic Reaction Templates
title_full_unstemmed EHreact: Extended Hasse Diagrams for the Extraction and Scoring of Enzymatic Reaction Templates
title_short EHreact: Extended Hasse Diagrams for the Extraction and Scoring of Enzymatic Reaction Templates
title_sort ehreact: extended hasse diagrams for the extraction and scoring of enzymatic reaction templates
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8549070/
https://www.ncbi.nlm.nih.gov/pubmed/34587449
http://dx.doi.org/10.1021/acs.jcim.1c00921
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