Determinants and Prediction of Esterase Substrate Promiscuity Patterns
Mónica Martínez-Martínez,Cristina Coscolín,Gerard Santiago,Jennifer Chow,Peter J. Stogios,Rafael Bargiela,Christoph Gertler,José Navarro-Fernández,Alexander Bollinger,Stephan Thies,Celia Méndez-García,Ana Popovic,Greg Brown,Tatyana N. Chernikova,Antonio García-Moyano,Gro Elin Kjæreng Bjerga,Pablo Pérez-García,Tran Hai,Mercedes V. del Pozo,Runar Stokke,Ida Helene Steen,Hong Cui,Xiaohui Xu,Boguslaw Nocek,María Alcaide,Marco A. Distaso,Victoria Mesa,Ana Isabel Pelaez,Jesús Sánchez,Patrick C. F. Buchholz,Jürgen Pleiss,Antonio Fernandez-Guerra,Antonio Fernandez-Guerra,Antonio Fernandez-Guerra,Frank Oliver Glöckner,Frank Oliver Glöckner,Olga V. Golyshina,Michail M. Yakimov,Alexei Savchenko,Karl-Erich Jaeger,Karl-Erich Jaeger,Alexander F. Yakunin,Wolfgang R. Streit,Peter N. Golyshin,Victor Guallar,Victor Guallar,Manuel Ferrer +46 more
TL;DR: An extensive analysis of the substrate spectra of 145 phylogenetically and environmentally diverse microbial esterases, when tested with 96 diverse esters, finds a structural parameter that helps rank (classify) the promiscuity level of esterase from sequence data at 94% accuracy.
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Abstract: Esterases 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, ...
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