Exploring Chemical Biosynthetic Design Space with Transform-MinER
Author(s) -
Jonathan D. Tyzack,
António J. M. Ribeiro,
Neera Borkakoti,
Janet M. Thornton
Publication year - 2019
Publication title -
acs synthetic biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.156
H-Index - 66
ISSN - 2161-5063
DOI - 10.1021/acssynbio.9b00105
Subject(s) - chemical space , computer science , set (abstract data type) , space (punctuation) , path (computing) , substrate (aquarium) , theoretical computer science , combinatorial chemistry , data mining , chemistry , drug discovery , bioinformatics , biology , programming language , operating system , ecology
Transform-MinER (Transforming Molecules in Enzyme Reactions) is a web application facilitating the exploration of chemical biosynthetic space, guiding the user toward promising start points for enzyme design projects or directed evolution experiments. Two types of search are possible: Molecule Search allows a user to submit a source substrate enabling Transform-MinER to search for enzyme reactions acting on similar substrates, whereas Path Search additionally allows a user to submit a target molecule enabling Transform-MinER to search for a path of enzyme reactions acting on similar substrates to link source and target. Transform-MinER searches for potential reaction centers in the source substrate and uses chemoinformatic fingerprints to identify those that are situated in molecular environments similar to native counterparts, prioritizing steps that move closer to the target using reactions most similar to native in its exploration of search space. The ligand-based methodology behind Transform-MinER is presented, and its performance is validated yielding 90% success rates: first, on a data set of native pathways from the KEGG database, and second, on a data set of de novo enzyme reactions.
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