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Details of Grant 

EPSRC Reference: EP/X035603/1
Title: HECBioSim: The UK High End Computing Consortium for Biomolecular Simulation.
Principal Investigator: Khalid, Professor S
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Department: Biochemistry
Organisation: University of Oxford
Scheme: Standard Research - NR1
Starts: 03 January 2023 Ends: 02 January 2027 Value (£): 518,497
EPSRC Research Topic Classifications:
Chemical Biology Software Engineering
EPSRC Industrial Sector Classifications:
Pharmaceuticals and Biotechnology
Related Grants:
Panel History:
Panel DatePanel NameOutcome
01 Jan 3000 High End Computing Consortia Full Proposal Announced
Summary on Grant Application Form
Biomolecular simulations enable us to predict the behaviour of biological systems given the structures (or models) of the components. Combined with the structural biology and new advancements in machine learning methods, molecular simulations provide the scope for unprecedented insights into biomolecular systems.

The level of detail afforded by these methods, along with their ability to rationalise and augment experimental data and their predictive power in generating new hypotheses are already enabling them to make significant contributions in a wide variety of areas that are crucial for healthcare, the environment, quality of life and consequently, to the economy. The UK biomolecular simulation community has a strong international reputation, with world-leading research in in drug design and development, biocatalysis, bionano-technology, chemical biology and medicine. This has recently been demonstrated by the enormous impact our work has made on research into the SARS-CoV2 virus, in helping identify target sites for vaccine and antiviral development and has lead to our members winning and being shortlisted for international prizes, establishing new collaborations with industrial partners and being key participants in large international consortia.

Furthermore, in addition to our work on Covid-19, we have delivered outstanding research with impact in bionanotechology, drug design, AMR as well as in developing novel models (e.g. fluctuating finite elements models), methodologies (e.g. conversion between fine-grained and coarse-grained resolutions) and enabling technologies (e.g.tools for efficient submission of calculations) for application across the full spectrum of biophysical and biochemical sciences. We are now at a time when we can take giant leaps in terms of the scope of our work. Having access to the largest, most modern computing facilities in the UK is essential for this. Renewal of the Consortium will enable us to continue allocating time ARCHER2 and Tier 2 resources for our cutting-edge biomolecular simulations.

We will place a special emphasis on reaching out to experimentalists (indeed we already have a strong reputation for doing this) and scientists working in industry in order to foster interactions between computational and experimental scientists, and academia and industry to encourage integrated multidisciplinary studies of key problems.

Biomolecular simulation is an integral part of drug design and development. The pharmaceutical industry needs well-trained scientists in this area, as well as the development of new methods (e.g. for prediction of drug binding affinities, ligand selectivity and metabolism). Members of the consortium have a strong track record of collaboration with industry to deliver trained scientists and new methodologies. For example, PhD students trained by consortium members have recently taken up positions in UCB, Unilever, Oxford Nanopore Technologies and Exscientia. Many of these academic-industry collaborations have been strengthened and in some cases, been established on the basis of work done through HECBioSim allocations.

The Consortium will continue to welcome new members from across the whole community including ECRs. Indeed we have an excellent track record of ECRs from within our community going on to independent academic posts. We will continue to develop computational tools and training for both experts and non-experts using biomolecular simulation on HEC resources. We propose to develop new tools that will enable more efficient simulations by harnessing tools from the machine learning field an augmenting them with our own codes to make best use of the UK HEC landscape.

In summary, HECBioSim will expand our portfolio of collaborative endeavours with experimental scientists and those working in industry to harness expertise from all domains to inform our own work and thus to maintain the UK as a world-leader in biomolecular simulation.
Key Findings
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Organisation Website: http://www.ox.ac.uk