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Details of Grant 

EPSRC Reference: EP/P011306/1
Title: Efficient modelling and validation of cryptic protein binding sites for drug discovery
Principal Investigator: Gervasio, Professor F
Other Investigators:
Researcher Co-Investigators:
Project Partners:
CCP-Biosim UCB University of Bristol
Department: Chemistry
Organisation: UCL
Scheme: Standard Research
Starts: 01 July 2017 Ends: 30 June 2020 Value (£): 272,316
EPSRC Research Topic Classifications:
Biological & Medicinal Chem. Biophysics
EPSRC Industrial Sector Classifications:
Healthcare R&D
Related Grants:
EP/P011330/1
Panel History:
Panel DatePanel NameOutcome
24 Jan 2017 EPSRC Physical Sciences - January 2017 Announced
25 Oct 2016 EPSRC Physical Sciences - October 2016 Deferred
Summary on Grant Application Form
Over 75% of disease-involved proteins cannot be readily targeted by conventional chemical biology approaches. New approaches are needed to increase the scope of molecular medicine.

Cryptic binding pockets, i.e. pockets that transiently form in a folded protein, but are not apparent in the crystal structure of the unliganded apo-form, offer outstanding opportunities to target proteins otherwise deemed 'undruggable' and are thus of considerable interest in academia and the pharmaceutical industry. Unfortunately, not only they are notoriously difficult to identify, but also the molecular mechanism by which they form is still debated. The aim of this collaborative project is to address the knowledge gaps and develop an efficient computational platform based on atomistic molecular simulations to systematically detect druggable cryptic pockets in targets of biopharmaceutical interest. The platform will build on our successful experience in developing and applying enhanced-sampling simulation algorithms to molecular recognition, and will be extensively tested on validated drug targets harbouring cryptic sites. The computational results will be further validated on novel targets by a combination of experiments in collaboration with an industrial partner (UCB).

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