CCP-BioSim: Biomolecular Simulation at the Life Sciences Interface

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"Everything that living things do can be understood in terms of the jigglings and wigglings of atoms" as Richard Feynman provocatively stated nearly fifty years ago. But how can we 'see' this wiggling and jiggling and understand how it drives biology? Increasingly, computer simulations of biological macromolecules are helping to meet this challenge. Experiments can provide detailed structures of biological macromolecules such as proteins, but it is hard to study directly how the structures of individual molecules change on short timescales as they function. Similarly it is not yet possible to study directly by experiment alone the molecular mechanisms of fast processes such as chemical reactions in enzymes or ion transport through membranes. Simulations based on fundamental physics offer the potential of filling-in these crucial 'gaps', modelling how proteins and other biomolecules move, fluctuate, interact, react and function.Physics-based simulations complement experiments in building a molecular level understanding of biology: they can test hypotheses and interpret and analyse experimental data in terms of interactions at the atomic level. A wide variety of simulation techniques have been developed, applicable to a range of different problems in biomolecular science. Simulations have already shown their worth in helping to analyse how enzymes catalyse biochemical reactions, and how proteins adopt their functional structures. They can help in the design of drugs and catalysts, and in understanding the molecular basis of disease. And simulations have played a key role in developing the conceptual framework now at the heart of biomolecular science, that is, the understanding that the way that biological molecules move and flex - their dynamics - is central to their function, demonstrating the truth of Feynman's assertion.Developing methods from chemical physics and computational science will open exciting new opportunities in biomolecular science, including in drug design and development, synthetic biology, biotechnology and biocatalysis. Much biomolecular simulation demands HEC resources: e.g. large-scale simulations of biological machines such as the ribosome, proton pumps and motors, membrane receptor complexes and even whole viruses. A particular challenge is the integration of simulations across length and timescales: different types of simulation method are required for different types of problems). We work to develop 'multiscale' modelling and simulation methods to tackle these large problems, in areas such as drug metabolism and transport.