Determinants and prediction of esterase substrate promiscuity patterns

Electronic versions

Documents

  • Main Text_rev7 NO TRACK CHANGES

    Accepted author manuscript, 1 MB, PDF-document

    Embargo ends: 28/11/18

  • Mónica Martínez-Martínez
    Institute of Catalysis
  • Cristina Coscolín
    Institute of Catalysis, Consejo Superior de Investigaciones Científicas (CSIC), Madrid
  • Gerard Santiago
    Barcelona Supercomputing Center (BSC),
  • Jennifer Chow
    Universität Hamburg
  • Peter J. Stogios
    University of Toronto, Canada
  • Rafael Bargiela
    Institute of Catalysis
  • Christoph Gertler
  • J. Navarro-Fernández
    Institute of Catalysis, Consejo Superior de Investigaciones Científicas (CSIC), Madrid
  • Alexander Bollinger
    Heinrich-Heine-Universität , Dusseldorf
  • Stephanie Thies
    Heinrich-Heine-Universität , Dusseldorf
  • Celia Méndez-García
    Universidad de Oviedo
  • Anna Popovic
    University of Toronto, Canada
  • Greg Brown
    University of Toronto, Canada
  • Tatyana Chernikova
  • Antonio García-Moyano
    Center for Applied Biotechnology, Bergen
  • Gro E.K. Bjerga
    Center for Applied Biotechnology, Bergen
  • Pablo Perez-Garcia
    Universität Hamburg
  • Tran Hai
  • Mercedes V. del Pozo
    Institute of Catalysis, Consejo Superior de Investigaciones Científicas (CSIC), Madrid
  • Runar Stokke
    Center for Applied Biotechnology, Bergen
  • Ida H. Steen
    Center for Applied Biotechnology, Bergen
  • Hong Cui
    University of Toronto, Canada
  • Xiaohui Xu
    Center for Applied Biotechnology, Bergen
  • Boguslaw Nocek
    Argonne National Laboratory, Argonne, IL.
  • Maria Alcaide
    Institute of Catalysis, Consejo Superior de Investigaciones Científicas (CSIC), Madrid
  • Marco Disasto
    Bangor University
  • Victoria Mesa
    Universidad de Oviedo
  • Ana I. Pelaez
    Universidad de Oviedo
  • Jesus Sanchez
    Universidad de Oviedo
  • Patrick C.F. Buchholz
    University of Stuttgart
  • Jurgen Pleiss
    University of Stuttgart
  • Antonio Fernández-Guerra
    Bremen University
  • Frank O. Glockner
    Bremen University
  • Olga Golyshina
  • Michail M. Yakimov
    Institute for Coastal Marine Environment
  • Alexei Savchenko
    University of Toronto, Canada
  • Karl-Erich Jaeger
    Bremen University
  • Alexander F. Yakunin
    University of Toronto, Canada
  • Wolfgang R. Streit
    Universität Hamburg
  • Peter Golyshin
  • Victor Guallar
    Barcelona Supercomputing Center (BSC),
  • Manuel Ferrer
    Institute of Catalysis, Consejo Superior de Investigaciones Científicas (CSIC), Madrid
Esterases receive special attention because 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 ranking (classifying) 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 datasets.
Original languageEnglish
JournalACS Chemical Biology
StateE-pub ahead of print - 28 Nov 2017
View graph of relations