Evaluating the similarity of biochemical reactions and its uses for mapping novel reactions to protein sequences

A key challenge in metabolic engineering is to design novel or to improve existing biosynthetic pathways that lead to the cellular production of a given industrial or pharmaceutical compound. In many cases, the required enzymatic reactions for the biosynthesis of the target molecule need to be designed from scratch. BNICE.ch is a method that enables the design of de novo synthetic pathways through the postulation of novel biotransformations. However, finding enzymes that can potentially catalyze the proposed reactions remains a challenge. In this work, we propose a novel method, named BridgIT, to link novel reactions with well characterized enzymatic reactions and their associated genes. BridgIT compares every predicted novel reaction to all known enzymatic reactions for which a protein sequence is available. Novel and known reactions are compared based on the similarity of the reactive site of the substrates and the breakage and formation of atomic bonds during the conversion of the substrate to the product. As a result, BridgIT reports a similarity score for each comparison of known reactions to novel reactions, thus giving an estimate of the likelihood that a given enzyme can catalyze a novel reaction. The candidate proposed enzymes for de novo reactions by BridgIT, are either capable of catalyzing these reactions or they can serve as good initial sequences for the enzyme engineering. BridgIT online tool is freely available on the web (http://lcsb-databases.epfl.ch/) for academia upon subscription

Design of novel enzyme-catalyzed reactions linked to protein sequences for finding enzyme engineering targets

Noushin Hadadi, Jasmin Maria Hafner, Vassily Hatzimanikatis, Homa Mohammadi Peyhani

A key challenge in metabolic engineering is to find and to improve biosynthetic pathways that lead to the cellular production of a given industrial, pharmaceutical or specialty chemical compound. In many cases, the enzymatic reactions required for bio-production have not been observed in nature and need to be designed from scratch. Computational approaches are essential to predict possible novel biotransformation and to find enzymes that can potentially catalyze the proposed reactions. In this work, we present two computational tools, BNICE.ch and BridgIT, and we demonstrate their concerted action to (i) predict hypothetical biotransformations and (ii) to link these novel reactions with well characterized enzymatic reactions and their associated genes. BNICE.ch reconstructs known reactions and generates novel reactions by applying its integrated, expert curated, generalized enzyme reaction rules on known metabolites. In order to find enzymes that potentially catalyze the biotransformation of these novel reactions, we assume that molecules with a similar reactive site and a similar atomic structure around the reactive site may be recognized and transformed by the same enzyme. Hence, BridgIT compares every predicted novel reaction to all known enzymatic reactions for which a protein sequence is available. Novel and known reactions are compared based on the reactive site of the substrates, the atoms surrounding the reactive site, and the breakage and formation of atomic bonds during the conversion of the substrate to the product. As a result, BridgIT reports a similarity score for each comparison of known reactions to novel reactions, thus giving an estimate of how possible it is that a given enzyme can catalyze a novel reaction. The results are organized in a database of known and hypothetical reactions called the “ATLAS of Biochemistry”1, where every hypothetical reaction is associated with its structurally most similar known enzymatic reactions, thus suggesting a plausible Gene-Protein-Reaction (GPR) association that can be used as a starting point for enzyme engineering. Our database currently spans more than 130’000 biochemically possible reactions between known metabolites from the Kyoto Encyclopedia of Genes and Genomes (KEGG). The ATLAS database and the BridgIT online tool are available on the web (http://lcsb-databases.epfl.ch/) and they can be used to extract potential reactions and pathways and to identify enzyme targets for metabolic and enzymatic engineering purposes. 1Hadadi, N., Hafner, J., Shajkofci, A., Zisaki, A., & Hatzimanikatis, V. (2016). ATLAS of Biochemistry: A repository of all possible biochemical reactions for synthetic biology and metabolic engineering studies. ACS Synthetic Biology, 2016.

2017

ATLAS of Biochemistry: A Repository of All Possible Biochemical Reactions for Synthetic Biology and Metabolic Engineering Studies

Noushin Hadadi, Jasmin Maria Hafner, Vassily Hatzimanikatis, Adrian Shajkofci, Aikaterini Zisaki

Because the complexity of metabolism cannot be intuitively understood or analyzed, computational methods are indispensable for studying biochemistry and deepening our understanding of cellular metabolism to promote new discoveries. We used the computational framework BNICE.ch along with cheminformatic tools to assemble the whole theoretical reactome from the known metabolome through expansion of the known biochemistry presented in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. We constructed the ATLAS of Biochemistry, a database of all theoretical biochemical reactions based on known biochemical principles and compounds. ATLAS includes more than 130 000 hypothetical enzymatic reactions that KEGG connect two or more KEGG metabolites through novel enzymatic reactions that have never been reported to occur in living organisms. Moreover, ATLAS reactions integrate 42% of KEGG metabolites that are not currently present in any KEGG reaction into one or more novel enzymatic reactions. The generated repository of information is organized in a Web-based database (http://lcsb-databases.epfl.ch/atlas/) that allows the user to search for all possible routes from any substrate compound to any product. The resulting pathways involve known and novel enzymatic steps that may indicate unidentified enzymatic activities and provide potential targets for protein engineering. Our approach of introducing novel biochemistry into pathway design and associated databases will be important for synthetic biology and metabolic engineering.

Amer Chemical Soc2016

Enzyme annotation for orphan and novel reactions using knowledge of substrate reactive sites

Noushin Hadadi, Vassily Hatzimanikatis, Ljubisa Miskovic, Marianne Seijo

Thousands of biochemical reactions with characterized activities are “orphan,” meaning they cannot be assigned to a specific enzyme, leaving gaps in metabolic pathways. Novel reactions predicted by pathway-generation tools also lack associated sequences, limiting protein engineering applications. Associating orphan and novel reactions with known biochemistry and suggesting enzymes to catalyze them is a daunting problem. We propose the method BridgIT to identify candidate genes and catalyzing proteins for these reactions. This method introduces information about the enzyme binding pocket into reaction-similarity comparisons. BridgIT assesses the similarity of two reactions, one orphan and one well-characterized nonorphan reaction, using their substrate reactive sites, their surrounding structures, and the structures of the generated products to suggest enzymes that catalyze the most-similar nonorphan reactions as candidates for also catalyzing the orphan ones. We performed two large-scale validation studies to test BridgIT predictions against experimental biochemical evidence. For the 234 orphan reactions from the Kyoto Encyclopedia of Genes and Genomes (KEGG) 2011 (a comprehensive enzymatic-reaction database) that became nonorphan in KEGG 2018, BridgIT predicted the exact or a highly related enzyme for 211 of them. Moreover, for 334 of 379 novel reactions in 2014 that were later cataloged in KEGG 2018, BridgIT predicted the exact or highly similar enzymes. BridgIT requires knowledge about only four connecting bonds around the atoms of the reactive sites to correctly annotate proteins for 93% of analyzed enzymatic reactions. Increasing to seven connecting bonds allowed for the accurate identification of a sequence for nearly all known enzymatic reactions.

PNAS2019

Design of novel enzyme-catalyzed reactions linked to protein sequences for finding enzyme engineering targets

Noushin Hadadi, Jasmin Maria Hafner, Vassily Hatzimanikatis, Homa Mohammadi Peyhani

2017