CCP-BioSim: Biomolecular Simulation at the Life Sciences Interface

“生物所做的一切都可以用原子的摆动来理解”，理查德·费曼在将近50年前就这样说过。但是我们如何能“看到”这种摆动和抖动，并理解它是如何驱动生物学的呢？越来越多的生物大分子的计算机模拟正在帮助应对这一挑战。实验可以提供蛋白质等生物大分子的详细结构，但很难直接研究单个分子的结构在短时间内如何变化。同样，目前还不可能仅通过实验直接研究快速过程的分子机制，如酶中的化学反应或离子通过膜的传输。基于基础物理学的模拟提供了填补这些关键“空白”的潜力，模拟了蛋白质和其他生物分子如何移动、波动、相互作用、反应和功能。基于物理学的模拟补充了建立分子水平生物学理解的实验：它们可以测试假设，并在原子水平的相互作用方面解释和分析实验数据。各种各样的模拟技术已经发展起来，适用于生物分子科学中的一系列不同问题。模拟已经显示出它们在帮助分析酶如何催化生化反应以及蛋白质如何采用其功能结构方面的价值。它们可以帮助设计药物和催化剂，并帮助理解疾病的分子基础。模拟在发展生物分子科学的核心概念框架方面发挥了关键作用，即理解生物分子运动和弯曲的方式-它们的动力学-是它们功能的核心，证明了费曼断言的真理。发展化学物理和计算科学的方法将为生物分子科学带来令人兴奋的新机会，包括药物设计和开发、合成生物学、生物技术和生物催化。许多生物分子模拟需要HEC资源：例如，大规模模拟生物机器，如核糖体，质子泵和马达，膜受体复合物甚至整个病毒。一个特别的挑战是跨长度和时间尺度的模拟集成：不同类型的问题需要不同类型的模拟方法）。我们致力于开发“多尺度”建模和模拟方法，以解决药物代谢和运输等领域的这些大问题。

"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.