Graph transformation for enzymatic mechanisms

Author:

Andersen Jakob L1,Fagerberg Rolf1,Flamm Christoph2,Fontana Walter3,Kolčák Juraj1,Laurent Christophe V F P1,Merkle Daniel1,Nøjgaard Nikolai1

Affiliation:

1. Department of Mathematics and Computer Science, University of Southern Denmark, Odense, Denmark

2. Department of Theoretical Chemistry, University of Vienna, Vienna, Austria

3. Department of Systems Biology, Harvard Medical School, Boston, MA, USA

Abstract

Abstract Motivation The design of enzymes is as challenging as it is consequential for making chemical synthesis in medical and industrial applications more efficient, cost-effective and environmentally friendly. While several aspects of this complex problem are computationally assisted, the drafting of catalytic mechanisms, i.e. the specification of the chemical steps—and hence intermediate states—that the enzyme is meant to implement, is largely left to human expertise. The ability to capture specific chemistries of multistep catalysis in a fashion that enables its computational construction and design is therefore highly desirable and would equally impact the elucidation of existing enzymatic reactions whose mechanisms are unknown. Results We use the mathematical framework of graph transformation to express the distinction between rules and reactions in chemistry. We derive about 1000 rules for amino acid side chain chemistry from the M-CSA database, a curated repository of enzymatic mechanisms. Using graph transformation, we are able to propose hundreds of hypothetical catalytic mechanisms for a large number of unrelated reactions in the Rhea database. We analyze these mechanisms to find that they combine in chemically sound fashion individual steps from a variety of known multistep mechanisms, showing that plausible novel mechanisms for catalysis can be constructed computationally. Availability and implementation The source code of the initial prototype of our approach is available at https://github.com/Nojgaard/mechsearch Supplementary information Supplementary data are available at Bioinformatics online.

Funder

Novo Nordisk Foundation

Independent Research Fund Denmark

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

Reference21 articles.

1. Inferring chemical reaction patterns using rule composition in graph grammars;Andersen;J. Syst. Chem,2013

2. Generic strategies for chemical space exploration;Andersen;Int. J. Comput. Biol. Drug Des,2014

3. Computer-aided synthesis design: 40 years on;Cook;WIREs Comput. Mol. Sci,2012

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