Abstract
In this chapter, you will learn about ways for modeling the chemical diversity found in metabolic pathways in nature. Organisms have evolved enzymes, i.e., specialized proteins to carry out chemical transformations that produce the compounds required for life. We have nowadays a good understanding about the mechanisms of natural evolution that allowed the creation of new enzymes and new activities. We are going to model and simulate such behavior by encoding reactions in the same way as we encode a language using words. This will allow us to understand the grammar behind the generation of new reactions. Even more interestingly, we will see how the grammar can be potentially used to enumerate any possible reaction and any possible compound that can be produced in nature. At the end of this chapter, we should have gained a good understanding of the biochemical space that exists in nature.
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Notes
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I invite the reader to learn in detail the rules about SMARTS to understand the big possibilities of using this common representation for chemical transformations.
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References
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Further Reading
A good introduction to biocatalysis:
Grunwald, P.: Biocatalysis. Biochemical Fundamentals and Applications. Imperial College Press (2009)
An interesting discussion on enzyme promiscuity and evolution:
Khersonsky, O., Tawfik, D.S.: Enzyme promiscuity: a mechanistic and evolutionary perspective. Ann. Rev. Biochem. 79(1), 471–505 (2010)
Useful introductions to chemoinformatics and associated algorithms can be found in:
Judson, P.: Knowledge-Based Expert Systems in Chemistry. Theoretical and Computational Chemistry Series. Royal Society of Chemistry, Cambridge (2009)
Gasteiger, J., Engel, T. (eds.): Chemoinformatics. Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim, FRG (2003)
Faulon, J.L., Bender, A.: Handbook of Chemoinformatics Algorithms. Chapman & Hall/CRC (2010)
More details about the implementation of chemoinformatics algorithms are available at the sites for the software packages:
The RDKit Python library: http://rdkit.org
The CDK [9] Java library: https://cdk.github.io/
An insightful discussion about chemical space enumeration:
Reymond, J.L., Ruddigkeit, L., Blum, L., van Deursen, R.: The enumeration of chemical space. Wiley Interdiscip. Rev.: Comput. Mol. Sci. 2(5), 717–733 (2012)
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Carbonell, P. (2019). Modeling Chemical Diversity. In: Metabolic Pathway Design. Learning Materials in Biosciences. Springer, Cham. https://doi.org/10.1007/978-3-030-29865-4_4
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DOI: https://doi.org/10.1007/978-3-030-29865-4_4
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