SI2-CHE: ExTASY: Extensible Tools for Advanced Sampling and analYsis

SI2-CHE：ExTASY：用于高级采样和分析的可扩展工具

• 批准号: EP/K039490/1
• 负责人: Charles Laughton
• 金额: $ 33.57万
• 依托单位: University of Nottingham
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2013
• 资助国家: 英国
• 起止时间: 2013 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FK039490%2F1
• 关键词: SI2; CHE; ExTASY; Extensible; Tools

One of the biggest problems we face as we try to develop new materials and new medicines is the enormous gap between the size and complexity of the individual molecules that we understand and can manipulate through chemistry and physics, and the size and complexity of the materials we want to make or biological systems we wish to influence. Computer simulation methods are extremely useful for predicting the properties and behaviour of individual molecules - e.g. of a potential new polymer or a newly-discovered protein - but how will that behaviour relate to the real world situation when we have maybe 1,000,000,000,000,000,000,000 of them together? It is completely beyond the power of computers to deal with this number of individual molecules, but fortunately we don't have to. As long as we can study a big enough sample of them, our predictions of the properties of the bulk material should be reliable. The required sample size is often very large, but fortunately increasingly within the range that the most powerful modern-day computers can deal with. The aim of this project is to develop the software necessary to support these types of 'ensemble' calculations; software which will be very versatile and so theoretically able to applied to very many different areas of science.

当我们试图开发新材料和新药物时，我们面临的最大问题之一是，我们通过化学和物理理解并可以操纵的单个分子的大小和复杂性，与我们想要制造的材料或我们希望影响的生物系统的大小和复杂性之间的巨大差距。计算机模拟方法对于预测单个分子的性质和行为非常有用--例如潜在的新聚合物或新发现的蛋白质--但当我们可能有1,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000，处理这样数量的单个分子完全超出了计算机的能力，但幸运的是，我们不必这样做。只要我们能够研究足够大的样本，我们对大块材料性质的预测应该是可靠的。所需的样本量通常非常大，但幸运的是，越来越多地在现代最强大的计算机可以处理的范围内。这个项目的目的是开发必要的软件来支持这些类型的集合计算；该软件将是非常通用的，因此在理论上能够应用于非常不同的科学领域。

项目成果

Molecular Dynamics Simulations of the Adenosine A2a Receptor in POPC and POPE Lipid Bilayers: Effects of Membrane on Protein Behavior

• DOI: 10.1021/ci400463z
• 发表时间: 2014-02-01
• 期刊: JOURNAL OF CHEMICAL INFORMATION AND MODELING
• 影响因子: 5.6
• 作者: Ng, Hui Wen;Laughton, Charles A.;Doughty, Stephen W.
• 通讯作者: Doughty, Stephen W.

CoCo-MD: A Simple and Effective Method for the Enhanced Sampling of Conformational Space.

• DOI: 10.1021/acs.jctc.8b00657
• 发表时间: 2019-01
• 期刊: Journal of chemical theory and computation
• 影响因子: 5.5
• 作者: Ardita Shkurti;I. D. Styliari;Vivek Balasubramanian;I. Bethune;Conrado Pedebos;S. Jha;C. Laughton

Molecular dynamics simulations of the adenosine A2a receptor: structural stability, sampling, and convergence.

腺苷 A2a 受体的分子动力学模拟：结构稳定性、采样和收敛。

• DOI: 10.1021/ci300610w
• 发表时间: 2013
• 期刊: Journal of chemical information and modeling
• 影响因子: 5.6
• 作者: Ng HW