Automatic Determination of Reaction Mappings and Reaction Center Information. 2. Validation on a Biochemical Reaction Database

Apostolakis, Joannis; Sacher, Oliver; Körner, Robert; Gasteiger, Johann

doi:10.1021/ci700433d

Cited by 30 publications

(32 citation statements)

References 22 publications

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“…This is in contrast to our method where multiple atom mappings were computed for 2.1% of 7501 reactions of MetaCyc. They do not report an error rate for KEGG, but a companion paper, Apostolakis et al, 6 gives the following results for the computed atom mappings applied to the BioPath database: (1) 13.5% of the reactions had multiple atom mappings (7.6% with two atom mappings, and 5.9% with more than two atom mappings) and (2) 1.6% of the reactions did not have the same atom mapping as the one in BioPath, with a true error rate of 0.9% once the discrepancies were analyzed manually. The 13.5% of reactions with multiple atom mappings make their result less accurate than ours because these contain, for each of these reactions, at least one atom mapping that does not match the one in the BioPath database, which occurs, for our approach, for 2.1% of 7501 reactions in MetaCyc.…”

Section: ■ Related Workmentioning

confidence: 99%

Accurate Atom-Mapping Computation for Biochemical Reactions

Latendresse

Malerich

Travers

et al. 2012

J. Chem. Inf. Model.

103

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The complete atom mapping of a chemical reaction is a bijection of the reactant atoms to the product atoms that specifies the terminus of each reactant atom. Atom mapping of biochemical reactions is useful for many applications of systems biology, in particular for metabolic engineering where synthesizing new biochemical pathways has to take into account for the number of carbon atoms from a source compound that are conserved in the synthesis of a target compound. Rapid, accurate computation of the atom mapping(s) of a biochemical reaction remains elusive despite significant work on this topic. In particular, past researchers did not validate the accuracy of mapping algorithms. We introduce a new method for computing atom mappings called the minimum weighted edit-distance (MWED) metric. The metric is based on bond propensity to react and computes biochemically valid atom mappings for a large percentage of biochemical reactions. MWED models can be formulated efficiently as Mixed-Integer Linear Programs (MILPs). We have demonstrated this approach on 7501 reactions of the MetaCyc database for which 87% of the models could be solved in less than 10 s. For 2.1% of the reactions, we found multiple optimal atom mappings. We show that the error rate is 0.9% (22 reactions) by comparing these atom mappings to 2446 atom mappings of the manually curated Kyoto Encyclopedia of Genes and Genomes (KEGG) RPAIR database. To our knowledge, our computational atom-mapping approach is the most accurate and among the fastest published to date. The atom-mapping data will be available in the MetaCyc database later in 2012; the atom-mapping software will be available within the Pathway Tools software later in 2012.

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Section: ■ Related Workmentioning

confidence: 99%

Accurate Atom-Mapping Computation for Biochemical Reactions

Latendresse

Malerich

Travers

et al. 2012

J. Chem. Inf. Model.

103

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“…The study of the biological mechanisms of isomerases provided fundamental insights into the electrostatic principles of enzyme catalysis (6) and helped to reveal the connection between host-parasite interactions and cancer (7). The challenges of automatically detecting stereoisomerization in reactions also make their chemistry technically interesting (8)(9)(10)(11).…”

Section: Ec Classificationmentioning

confidence: 99%

Exploring the chemistry and evolution of the isomerases

Cuesta

Rahman

Thornton

2016

Proc. Natl. Acad. Sci. U.S.A.

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Isomerization reactions are fundamental in biology, and isomers usually differ in their biological role and pharmacological effects. In this study, we have cataloged the isomerization reactions known to occur in biology using a combination of manual and computational approaches. This method provides a robust basis for comparison and clustering of the reactions into classes. Comparing our results with the Enzyme Commission (EC) classification, the standard approach to represent enzyme function on the basis of the overall chemistry of the catalyzed reaction, expands our understanding of the biochemistry of isomerization. The grouping of reactions involving stereoisomerism is straightforward with two distinct types (racemases/epimerases and cis-trans isomerases), but reactions entailing structural isomerism are diverse and challenging to classify using a hierarchical approach. This study provides an overview of which isomerases occur in nature, how we should describe and classify them, and their diversity.T he 3D structure and function of biomolecules are intimately linked. One of the most outstanding attributes of enzymes is their ability to recognize similar molecules, such as isomers, selectively. For example, glutamate racemase catalyzes the interconversion between the isomers L-glutamate and D-glutamate, with the first being one of the 20 amino acids used to build proteins, whereas the second is an essential component of bacterial cell walls (1). Isomers of the same drug are often distinguished; for example, the tragic story of thalidomide unveiled how subtle changes in the spatial arrangement of atoms can have drastic consequences in their biological effect (2).The isomerases, which catalyze these interconversions, are involved in the central metabolism of most living organisms and have important applications in organic synthesis, biotechnology, and drug discovery (3-5). In comparison to other classes, isomerases are a small class involving unimolecular reactions, which are easy to analyze manually. The study of the biological mechanisms of isomerases provided fundamental insights into the electrostatic principles of enzyme catalysis (6) and helped to reveal the connection between host-parasite interactions and cancer (7). The challenges of automatically detecting stereoisomerization in reactions also make their chemistry technically interesting (8-11).A standard description of the biological function of genes and proteins is essential to interpret and report the outcome of sequencing initiatives. Scientists have traditionally developed elaborate classification systems to group functions in a hierarchical manner. Among the existing approaches, enzyme function is probably the best described at the molecular level, due to the longstanding effort of a team of enzymologists from the Enzyme Commission (EC) of the Nomenclature Committee of the International Union of Biochemistry and Molecular Biology (NC-IUBMB) to classify enzyme function systematically. The EC classification is the most widely used system and uses...

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“…It may also be difficult to find mapping rules consistent with multiple reaction formulas [Akutsu 2004]. [2008] and Apostolakis et al [2008] the authors extend a branch and bound algorithm called RASCAL. The algorithms are based on the maximum common edge subgraph problem.…”

Section: Subgraph Isomorphism-based Algorithmsmentioning

confidence: 99%

Faster reaction mapping through improved naming techniques

Kouri

Mehta

2013

ACM J. Exp. Algorithmics

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Automated reaction mapping is an important tool in cheminformatics where it may be used to classify reactions or validate reaction mechanisms. The reaction mapping problem is known to be NP-Hard and may be formulated as an optimization problem. In this article, we present four algorithms that continue to obtain optimal solutions to this problem, but with significantly improved runtimes over the previous Constructive Count Vector (CCV) algorithm. Our algorithmic improvements include (i) the use of a fast (but not 100% accurate) canonical labeling algorithm, (ii) name reuse (i.e., storing intermediate results rather than recomputing), and (iii) an incremental approach to canonical name computation. The time to map the reactions from the Kegg/Ligand database previously took over 2 days using CCV, but now it takes fewer than 4 hours to complete. Experimental results on chemical reaction databases demonstrate our 2-CCV FDN MS algorithm usually performs over fifteen times faster than previous automated reaction mapping algorithms. ACM Reference Format:Kouri, T. M. and Mehta, D. P. 2013. Faster reaction mapping through improved naming techniques. ACM J.

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Automatic Determination of Reaction Mappings and Reaction Center Information. 2. Validation on a Biochemical Reaction Database

Cited by 30 publications

References 22 publications

Accurate Atom-Mapping Computation for Biochemical Reactions

Accurate Atom-Mapping Computation for Biochemical Reactions

Exploring the chemistry and evolution of the isomerases

Faster reaction mapping through improved naming techniques

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