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      Quantitative Comparison of Catalytic Mechanisms and Overall Reactions in Convergently Evolved Enzymes: Implications for Classification of Enzyme Function

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Functionally analogous enzymes are those that catalyze similar reactions on similar substrates but do not share common ancestry, providing a window on the different structural strategies nature has used to evolve required catalysts. Identification and use of this information to improve reaction classification and computational annotation of enzymes newly discovered in the genome projects would benefit from systematic determination of reaction similarities. Here, we quantified similarity in bond changes for overall reactions and catalytic mechanisms for 95 pairs of functionally analogous enzymes (non-homologous enzymes with identical first three numbers of their EC codes) from the MACiE database. Similarity of overall reactions was computed by comparing the sets of bond changes in the transformations from substrates to products. For similarity of mechanisms, sets of bond changes occurring in each mechanistic step were compared; these similarities were then used to guide global and local alignments of mechanistic steps. Using this metric, only 44% of pairs of functionally analogous enzymes in the dataset had significantly similar overall reactions. For these enzymes, convergence to the same mechanism occurred in 33% of cases, with most pairs having at least one identical mechanistic step. Using our metric, overall reaction similarity serves as an upper bound for mechanistic similarity in functional analogs. For example, the four carbon-oxygen lyases acting on phosphates (EC 4.2.3) show neither significant overall reaction similarity nor significant mechanistic similarity. By contrast, the three carboxylic-ester hydrolases (EC 3.1.1) catalyze overall reactions with identical bond changes and have converged to almost identical mechanisms. The large proportion of enzyme pairs that do not show significant overall reaction similarity (56%) suggests that at least for the functionally analogous enzymes studied here, more stringent criteria could be used to refine definitions of EC sub-subclasses for improved discrimination in their classification of enzyme reactions. The results also indicate that mechanistic convergence of reaction steps is widespread, suggesting that quantitative measurement of mechanistic similarity can inform approaches for functional annotation.

          Author Summary

          When species evolve, their genes duplicate and diverge to allow for adaptation of their functional repertoires to the changing environment. In this scenario, unrelated genes can convergently evolve to produce proteins with the same molecular function, termed “functionally analogous.” A quantitative determination of the reaction similarities among functionally analogous enzymes could provide insight about the different structural solutions nature has used to evolve similar catalysts. Bond changes between substrates and products, and between successive reaction intermediates, were used to compare the reactions catalyzed and the mechanisms of catalysis for 95 pairs of functionally analogous enzymes. Less than half of the reactions catalyzed by unrelated enzymes, but defined as similar by the Enzyme Commission (EC) classification, are similar in terms of bond changes, suggesting that this classification often fails to capture quantitative differences between many enzyme reactions. Furthermore, we addressed for the first time whether the chemical mechanisms by which similar overall reactions are achieved in functional analogs are also similar. We conclude that convergence of reaction is often accompanied by convergence of chemical mechanism. These results will be useful for classifying enzymes, guiding functional annotation of newly determined enzyme sequences and structures and for informing the engineering of enzymes with new functions.

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          Gene Ontology: tool for the unification of biology

          Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
            Bookmark
            • Record: found
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            • Article: not found

            Identification of common molecular subsequences.

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              • Record: found
              • Abstract: found
              • Article: not found

              Assigning protein functions by comparative genome analysis: protein phylogenetic profiles.

              Determining protein functions from genomic sequences is a central goal of bioinformatics. We present a method based on the assumption that proteins that function together in a pathway or structural complex are likely to evolve in a correlated fashion. During evolution, all such functionally linked proteins tend to be either preserved or eliminated in a new species. We describe this property of correlated evolution by characterizing each protein by its phylogenetic profile, a string that encodes the presence or absence of a protein in every known genome. We show that proteins having matching or similar profiles strongly tend to be functionally linked. This method of phylogenetic profiling allows us to predict the function of uncharacterized proteins.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Comput Biol
                plos
                ploscomp
                PLoS Computational Biology
                Public Library of Science (San Francisco, USA )
                1553-734X
                1553-7358
                March 2010
                March 2010
                12 March 2010
                : 6
                : 3
                : e1000700
                Affiliations
                [1 ]Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, California, United States of America
                [2 ]Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, California, United States of America
                [3 ]California Institute for Quantitative Biosciences, University of California San Francisco, San Francisco, California, United States of America
                [4 ]Biological and Medical Informatics Graduate Program, University of California San Francisco, San Francisco, California, United States of America
                [5 ]Centre for Biomolecular Sciences, University of St Andrews, St Andrews, United Kingdom
                University College London, United Kingdom
                Author notes

                Conceived and designed the experiments: DEA JBOM PCB. Performed the experiments: DEA ERY. Analyzed the data: DEA. Wrote the paper: DEA ERY JBOM PCB.

                Article
                09-PLCB-RA-1000R2
                10.1371/journal.pcbi.1000700
                2837397
                20300652
                508c28de-cf13-4c46-8606-1f97bb526c10
                Almonacid et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 20 August 2009
                : 2 February 2010
                Page count
                Pages: 18
                Categories
                Research Article
                Biochemistry/Biocatalysis
                Biochemistry/Bioinformatics
                Biochemistry/Chemical Biology of the Cell
                Biochemistry/Macromolecular Chemistry
                Biochemistry/Molecular Evolution
                Biochemistry/Small Molecule Chemistry
                Biophysics/Biomacromolecule-Ligand Interactions
                Biophysics/Protein Chemistry and Proteomics
                Biotechnology/Bioengineering
                Computational Biology/Evolutionary Modeling
                Genetics and Genomics/Functional Genomics
                Genetics and Genomics/Gene Function

                Quantitative & Systems biology
                Quantitative & Systems biology

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