Abstract
The goal of our research is to increase our understanding of how biology works at the molecular level, with a particular focus on how enzymes evolve their functions through adaptations to generate new specificities and mechanisms. FunTree (Sillitoe and Furnham, Nucleic Acids Res 44:D317–D323, 2016) is a resource that brings together sequence, structure, phylogenetic, and chemical and mechanistic information for 2340 CATH superfamilies (Sillitoe et al., Nucleic Acids Res 43:D376–D381, 2015) (which all contain at least one enzyme) to allow evolution to be investigated within a structurally defined superfamily.
We will give an overview of FunTree’s use of sequence and structural alignments to cluster proteins within a superfamily into structurally similar groups (SSGs) and generate phylogenetic trees augmented by ancestral character estimations (ACE). This core information is supplemented with new measures of functional similarity (Rahman et al., Nat Methods 11:171–174, 2014) to compare enzyme reactions based on overall bond changes, reaction centers (the local environment atoms involved in the reaction), and the structural similarities of the metabolites involved in the reaction. These trees are also decorated with taxonomic and Enzyme Commission (EC) code and GO annotations, forming the basis of a comprehensive web interface that can be found at http://www.funtree.info. In this chapter, we will discuss the various analyses and supporting computational tools in more detail, describing the steps required to extract information.
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Tyzack, J.D., Furnham, N., Sillitoe, I., Orengo, C.M., Thornton, J.M. (2019). Exploring Enzyme Evolution from Changes in Sequence, Structure, and Function. In: Sikosek, T. (eds) Computational Methods in Protein Evolution. Methods in Molecular Biology, vol 1851. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-8736-8_14
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DOI: https://doi.org/10.1007/978-1-4939-8736-8_14
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