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Determinants and prediction of esterase substrate promiscuity patterns

AuthorsMartínez-Martínez, Mónica ; Coscolín, Cristina; Santiago, Gerard; Chow, Jennifer; Stogios, Peter J.; Bargiela, Rafael ; Gertler, Christoph; Navarro-Fernández, José; Bollinger, Alexander; Thies, Stephan; Méndez-García, Celia; Popovic, Ana; Brown, Greg; Chernikova, Tatyana; García-Moyano, Antonio; Bjerga, Gro E. K.; Pérez-García, Pablo ; Hai, Tran; Pozo, Mercedes V. del ; Stokke, Runar; Steen, Ida H.; Cui, Hong; Xu, Xiaohui; Nocek, Boguslaw P.; Alcaide, María ; Distaso, Marco; Mesa, Victoria; Peláez, Ana I.; Sánchez, Jesús; Buchholz, Patrick C. F.; Pleiss, Jürgen; Fernández-Guerra, Antonio; Glöckner, Frank O.; Golyshina, Olga V. ; Yakimov, Michail M.; Savchenko, Alexei; Jaeger, Karl-Erich; Yakunin, Alexander F.; Streit, Wolfgang R.; Golyshin, Peter N.; Guallar, Victor; Ferrer, Manuel ; INMARE Consortium
Issue Date28-Nov-2017
PublisherAmerican Chemical Society
CitationACS Chemical Biology 13(1): 225-234 (2018)
AbstractEsterases receive special attention because of their wide distribution in biological systems and environments and their importance for physiology and chemical synthesis. The prediction of esterases’ substrate promiscuity level from sequence data and the molecular reasons why certain such enzymes are more promiscuous than others remain to be elucidated. This limits the surveillance of the sequence space for esterases potentially leading to new versatile biocatalysts and new insights into their role in cellular function. Here, we performed an extensive analysis of the substrate spectra of 145 phylogenetically and environmentally diverse microbial esterases, when tested with 96 diverse esters. We determined the primary factors shaping their substrate range by analyzing substrate range patterns in combination with structural analysis and protein–ligand simulations. We found a structural parameter that helps rank (classify) the promiscuity level of esterases from sequence data at 94% accuracy. This parameter, the active site effective volume, exemplifies the topology of the catalytic environment by measuring the active site cavity volume corrected by the relative solvent accessible surface area (SASA) of the catalytic triad. Sequences encoding esterases with active site effective volumes (cavity volume/SASA) above a threshold show greater substrate spectra, which can be further extended in combination with phylogenetic data. This measure provides also a valuable tool for interrogating substrates capable of being converted. This measure, found to be transferred to phosphatases of the haloalkanoic acid dehalogenase superfamily and possibly other enzymatic systems, represents a powerful tool for low-cost bioprospecting for esterases with broad substrate ranges, in large scale sequence data sets.
Publisher version (URL)https://doi.org/10.1021/acschembio.7b00996
Appears in Collections:(ICTP) Artículos
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