Computationally Driven Rational Design of Substrate Promiscuity on Serine Ester Hydrolases

Autor: Manuel Ferrer, Victor Guallar, Gerard Santiago, Laura Fernandez-Lopez, Rubén Cañadas, Sergi Roda
Přispěvatelé: Barcelona Supercomputing Center, European Commission, Ministerio de Ciencia e Innovación (España), Ministerio de Economía y Competitividad (España), Ministerio de Ciencia, Innovación y Universidades (España), Agencia Estatal de Investigación (España)
Rok vydání: 2021
Předmět:
Zdroj: UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
ISSN: 2155-5435
Popis: [EN] Enzymes with a broad substrate specificity are of great interest both at the basic and applied level. Understanding the main parameters that make an enzyme substrate ambiguous could be thus important not only for their selection from the ever-increasing amount of sequencing data but also for engineering a more substrate promiscuous variant. This issue, which remains unresolved, was herein investigated by targeting a serine ester hydrolase (EH102), which exhibits a narrow substrate spectrum, being only capable of hydrolyzing 16 out of 96 esters tested. By using a modeling approach, we demonstrated that one can rationalize active site parameters defining substrate promiscuity, and that based on them the substrate specificity can be significantly altered. This was accomplished by designing two variants, EH102 and EH102, that hydrolyze 51 and 63 esters, respectively, while maintaining similar or higher turnover rates compared to the original enzyme. We hypothesized that the parameters identified here (the volume, size, exposure, enclosure, hydrophobicity, and hydrophilicity of the active site cavity and its tightness) can serve in the future to expand the substrate spectra of esterases and thus expand their use in biotechnology and synthetic chemistry.
This work was funded by grant “INMARE” from the European Union’s Horizon 2020 (grant agreement no. 634486), grant PCIN-2017-078 (within the Marine Biotechnology ERA-NET), and BIO2017-85522-R and PID2019-106370RB-I00/AEI/10.13039/501100011033 grants from the Spanish Ministry of Science and Innovation, Ministerio de Economía, Industria y Competitividad, Ministerio de Ciencia, Innovación y Universidades, Agencia Estatal de Investigación (AEI), Fondo Europeo de Desarrollo Regional (FEDER), and European Union (EU). This work has also been supported by a predoctoral fellowship from the Spanish Ministry of Science and Innovation (FPU19/00608)
Databáze: OpenAIRE