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NetMoDEzyme

Financiado

Cerrado

Network models for the computational design of proficient enzymes

Billions of years of evolution have made enzymes superb catalysts capable of accelerating reactions by several orders of magnitude. The underlying physical principles of their extraordinary catalytic power still remains highly deb... ver más

31/12/2022

UDG

1M€

Presupuesto del proyecto: 1M€

Líder del proyecto

UNIVERSITAT DE GIRONA No se ha especificado una descripción o un objeto social para esta compañía.

Total investigadores 227

Fecha límite participación Sin fecha límite de participación.

Ver 2 Participantes

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2022-12-31

ERC-StG-2015: ERC Starting Grant

I+D

Cerrada hace 10 años

0% 100%

Información adicional privada

No hay información privada compartida para este proyecto. Habla con el coordinador.

2 Participantes

UDG

1.45M€ | Lider

POWER ELECTRONICS ESPAÑA

2.00M€ | Participante

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Duración del proyecto: 82 meses Fecha Inicio: 2016-02-09
Fecha Fin: 2022-12-31

Líder del proyecto

UNIVERSITAT DE GIRONA No se ha especificado una descripción o un objeto social para esta compañía.

Total investigadores 227

Presupuesto del proyecto 1M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto Billions of years of evolution have made enzymes superb catalysts capable of accelerating reactions by several orders of magnitude. The underlying physical principles of their extraordinary catalytic power still remains highly debated, which makes the alteration of natural enzyme activities towards synthetically useful targets a tremendous challenge for modern chemical biology. The routine design of enzymes will, however, have large socio-economic benefits, as because of the enzymatic advantages the production costs of many drugs will be reduced and will allow industries to use environmentally friendly alternatives. The goal of this project is to make the routine design of proficient enzymes possible. Current computational and experimental approaches are able to confer natural enzymes new functionalities but are economically unviable and the catalytic efficiencies lag far behind their natural counterparts. The groundbreaking nature of NetMoDEzyme relies on the application of network models to reduce the complexity of the enzyme design paradigm and completely reformulate previous computational design approaches. The new protocol proposed accurately characterizes the enzyme conformational dynamics and customizes the included mutations by exploiting the correlated movement of the enzyme active site residues with distal regions. The guidelines for mutation are withdrawn from the costly directed evolution experimental technique, and the most proficient enzymes are easily identified via chemoinformatic models. The new strategy will be applied to develop proficient enzymes for the synthesis of enantiomerically pure β-blocker drugs for treating cardiovascular problems at a reduced cost. The experimental assays of our computational predictions will finally elucidate the potential of this genuinely new approach for mimicking Nature’s rules of evolution.

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