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UBioRec

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Development and Testing of a Reference Computational Platform for Understanding...

Development and Testing of a Reference Computational Platform for Understanding Biomolecular Recognition Due to its fundamental regulatory role, molecular recognition has been extensively studied by both experiments and simulations. During the last 30 years impressive technical advances allowed significant progress in understanding m... ver más

31/05/2020

UNIVERSITY COLLEGE...

195K€

Presupuesto del proyecto: 195K€

Líder del proyecto

UNIVERSITY COLLEGE LONDON No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2020-05-31

MSCA-IF-2017: Individual Fellowships

I+D

Cerrada hace 7 años

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

1 Participantes

UNIVERSITY COLLEGE LONDON

195.45K€ | Lider

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Duración del proyecto: 25 meses Fecha Inicio: 2018-04-12
Fecha Fin: 2020-05-31

Líder del proyecto

UNIVERSITY COLLEGE LONDON No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 195K€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto Due to its fundamental regulatory role, molecular recognition has been extensively studied by both experiments and simulations. During the last 30 years impressive technical advances allowed significant progress in understanding molecular recognition mechanisms. However, the matter is far from settled and contradictory reports are still appearing in the literature. Lately, I have been studying these processes using a combination of computational and experimental approaches in different systems. Here I propose to study several representative model systems in great details, taking advantages of new force fields, DFT functionals and enhanced sampling algorithms recently emerged. These systems are small enough to allow the use of state-of-the-art simulation techniques; still they are sufficiently complex not only to mimic the behaviour of far larger systems but also to use apparently different mechanisms. Indeed, their molecular recognition needs complex conformational changes, the re-arrangement of water molecules in the binding cavity, and an active role of the ligand in the binding/release mechanisms. The overarching objective of my proposal is to learn the state-of-the-art enhanced sampling techniques developed at UCL and combine them with QM/MM approaches to: i) understand how bio-molecular recognition works in both isoforms, ii) fully characterize the thermodynamics and kinetic processes that govern them and iii) validate the computational approaches against high-quality experimental data. If successful, the in-depth understanding of the molecular binding mechanism will shed light on an intriguing and important biological system and provide a much needed benchmark to the computational community. This challenging but feasible project will have a far reaching impact on a number of H2020 priority areas, including drug discovery and bio-molecular engineering.

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