PREDACTED
Financiado
Predictive computational models for Enzyme Dynamics Antimicrobial resistance C...
Predictive computational models for Enzyme Dynamics Antimicrobial resistance Catalysis and Thermoadaptation for Evolution and Design
Enzymes are superlative catalysts, honed by billions of years of evolution to achieve high specificity and efficiency. Understanding how enzymes function and are adapted to different environments will be essential in developing bi...
Enzymes are superlative catalysts, honed by billions of years of evolution to achieve high specificity and efficiency. Understanding how enzymes function and are adapted to different environments will be essential in developing biocatalysts for the circular economy and in combating drug resistance. Basic principles of catalysis and mechanistic understanding have come from experiments and simulations, and significant progress has been made in designing and evolving de novo protein catalysts. Truly predictive understanding is limited, however. There is a need for models able to predict, e.g. whether an enzyme is able to break down a particular antibiotic and how to inhibit it; temperature dependence of catalysis; how mutations affect activity and temperature optima; to understand how catalytic power evolves and use those principles in the development of new biocatalysts.
Theoretical developments, and emerging multiscale methods, provide a route to the predictive understanding required. Fundamentally, protein dynamics are vital, not in ‘driving’ reaction but rather as a fundamental facet of natural enzymes on which evolution acts. PREDACTED will simulate enzyme dynamics and dynamical changes associated with catalysis. We will (1) Investigate the adaptation of enzyme activity using the emerging theoretical framework of macromolecular rate theory, and develop simulation approaches to predict enzyme temperature optima, with relevance e.g. for understanding ecosystem response to climate change, and for the development of biocatalysts for practical industrial applications. (2) Develop predictive simulation models for enzymes responsible for antibiotic resistance, analyse allosteric effects and predict spectrums of activity. (3) Model antibiotic breakdown and inhibition of beta-lactamases (4) Apply the understanding developed in redesigning and engineering natural and artificial enzymes to test the catalytic principles and demonstrate how they can be applied in practice.
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Duración del proyecto: 64 meses
Fecha Inicio: 2021-05-11
Fecha Fin: 2026-09-30
Fecha Fin: 2026-09-30
Línea de financiación: concedida
El organismo H2020 notifico la concesión del proyecto el día 2021-05-11
Línea de financiación objetivo
El proyecto se financió a través de la siguiente ayuda:
ERC-2020-ADG:
ERC ADVANCED GRANT
Cerrada
hace 4 años
Presupuesto
El presupuesto total del proyecto asciende a
2M€
Líder del proyecto
UNIVERSITY OF BRISTOL
No se ha especificado una descripción o un objeto social para esta compañía.
Perfil tecnológico
TRL
4-5
Perfil tecnológico
TRL
4-5
271.34K€ |
Participante