EHreact: Extended Hasse Diagrams for the Extraction and Scoring of Enzymatic Reaction Templates
Author(s)
Heid, Esther
Goldman, Samuel
Sankaranarayanan, Karthik
Coley, Connor Wilson
Flamm, Christoph
Green Jr, William H
Date Issued
September 2021
Journal
Journal of Chemical Information and Modeling
Publisher
American Chemical Society (ACS)
Citation
Heid, Esther et al. "EHreact: Extended Hasse Diagrams for the Extraction and Scoring of Enzymatic Reaction Templates." Journal of Chemical Information and Modeling 61, 10 (September 2021): 4949–4961. © 2021 The Authors
Version
Final published version
Abstract
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.
MIT Department
Massachusetts Institute of Technology. Department of Chemical Engineering
Massachusetts Institute of Technology. Computational and Systems Biology Program
Terms of Use
Creative Commons Attribution 4.0 International license
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1021/acs.jcim.1c00921
