Harnessing conformational dynamics in enzyme catalysis to achieve nature-like catalytic efficiencies: the shortest path map tool for computational enzyme redesign
dc.contributor.author
dc.date.accessioned
2024-07-02T09:11:59Z
dc.date.available
2024-07-02T09:11:59Z
dc.date.issued
2024-03-18
dc.identifier.issn
1359-6640
dc.identifier.uri
dc.description.abstract
Enzymes exhibit diverse conformations, as represented in the free energy landscape (FEL). Such conformational diversity provides enzymes with the ability to evolve towards novel functions. The challenge lies in identifying mutations that enhance specific conformational changes, especially if located in distal sites from the active site cavity. The shortest path map (SPM) method, which we developed to address this challenge, constructs a graph based on the distances and correlated motions of residues observed in nanosecond timescale molecular dynamics (MD) simulations. We recently introduced a template based AlphaFold2 (tAF2) approach coupled with 10 nanosecond MD simulations to quickly estimate the conformational landscape of enzymes and assess how the FEL is shifted after mutation. In this study, we evaluate the potential of SPM when coupled with tAF2-MD in estimating conformational heterogeneity and identifying key conformationally-relevant positions. The selected model system is the beta subunit of tryptophan synthase (TrpB). We compare how the SPM pathways differ when integrating tAF2 with different MD simulation lengths from as short as 10 ns until 50 ns and considering two distinct Amber forcefield and water models (ff14SB/TIP3P versus ff19SB/OPC). The new methodology can more effectively capture the distal mutations found in laboratory evolution, thus showcasing the efficacy of tAF2-MD-SPM in rapidly estimating enzyme dynamics and identifying the key conformationally relevant hotspots for computational enzyme engineering
dc.description.sponsorship
We thank the Generalitat de Catalunya for the consolidated group TCBioSys (SGR 2021 00487), Spanish MICIN for grant projects PID2021-129034NB-I00 and PDC2022-133950-I00. S. O. is grateful to the funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (ERC-2015-StG-679001, ERC-2022-POC-101112805, and ERC-2022-CoG-101088032), and the Human Frontier Science Program (HFSP) for project grant RGP0054/2020. C. D. was supported by the Spanish MINECO for a PhD fellowship (PRE2019-089147), and G. C. by a research grant from ERC-StG (ERC-2015-StG-679001) and ERC-POC (ERC-2022-POC-1011128)
Open Access funding provided thanks to the CSUC agreement with Royal Society of Chemistry (RSC)
dc.format.mimetype
application/pdf
dc.language.iso
eng
dc.publisher
Royal Society of Chemistry (RSC)
dc.relation
PID2021-129034NB-I00
PDC2022-133950-I00
dc.relation.isformatof
Reproducció digital del document publicat a: https://doi.org/10.1039/D3FD00156C
dc.relation.ispartof
Faraday Discussions, 2024, Advance Article
dc.relation.ispartofseries
Articles publicats (D-Q)
dc.rights
Attribution-NonCommercial 4.0 International
dc.rights.uri
dc.subject
dc.title
Harnessing conformational dynamics in enzyme catalysis to achieve nature-like catalytic efficiencies: the shortest path map tool for computational enzyme redesign
dc.type
info:eu-repo/semantics/article
dc.rights.accessRights
info:eu-repo/semantics/openAccess
dc.relation.projectID
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2021-129034NB-I00/ES/DISEÑO COMPUTACIONAL DE ENZIMAS CONFORMACIONALMENTE DIRIGIDO PARA MEJORAR LA ACTIVIDAD AISLADA O EN COMPLEJO/
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PDC2022-133950-I00/ES/EVOLUCION COMPUTACIONAL DE NUEVOS (BIO)CATALIZADORES/
info:eu-repo/grantAgreement/EC/H2020/679001/EU/Network models for the computational design of proficient enzymes/NetMoDEzyme
info:eu-repo/grantAgreement/EC/HE/101112805/EU/Computational design of industrial enzymes for green chemistry/GREENZYME
info:eu-repo/grantAgreement/EC/HE/101088032/EU/Fast yet accurate routine rational design of novel enzymes/FASTEN
dc.type.version
info:eu-repo/semantics/publishedVersion
dc.identifier.doi
dc.identifier.idgrec
038794
dc.contributor.funder
dc.type.peerreviewed
peer-reviewed
dc.relation.FundingProgramme
dc.relation.ProjectAcronym
dc.identifier.eissn
1364-5498