U.S.-France Cooperative Research: Implicit Solvent Models for Biomolecular Simulations

0128783案例这项为期三年的美法合作计算生物物理学奖涉及法国斯特拉斯堡斯克里普斯研究所和分子和细胞生物学与遗传学研究所的研究人员。美国的大卫·A·凯斯、查尔斯·L·布鲁克斯三世和法国的托马斯·西蒙森领导了这个合作项目。这项联合工作的目的是开发和分发用于蛋白质和核酸分子动力学模拟的计算机代码。具体目标包括执行参数化关键测试和广义Born溶剂模型的实现，以及在核磁共振结构精化和生物分子行为方面的新应用。研究人员在生物分子模拟和广泛使用的计算机程序方面有互补的专业知识：CNS/XploR(Simonson)、CHARMM(Brooks)和Amber(Case)。新的分布式计算机代码将允许进行新型的生物分子模拟。改进的广义Born模型将被用于结构预测、蛋白质-配体相互作用的预测、蛋白质折叠、结构-功能分析。这一奖项代表了美国方面对NSF和法国国家科学研究中心(CNRS)的平行建议。NSF将支付美国调查人员和研究生的旅费和生活费。CNRS将支持法国与会者访问美国。该项目为研究生的研究培训增加了国际层面，并增加了未来合作伙伴关系的机会。

0128783CaseThis three-year award for U.S.-France collaboration in computational biophysics involves researchers at the Scripps Research Institute and the Institute for Molecular and Cellular Biology and Genetics in Strasbourg, France. David A. Case, Charles L. Brooks III in the US and Thomas Simonson in France lead the collaborative program. The joint effort is aimed at the development and distribution of computer codes for molecular dynamics simulations of proteins and nucleic acids. The specific aims include performance of critical tests for parameterizations and implementation of the generalized Born solvent model and new applications for NMR (Nuclear Magnetic Resonance) structure refinement and for behavior of biomolecules. The investigators have complementary expertise in biomolecular simulation and in widely used computer programs: CNS/XPLOR (Simonson), CHARMM (Brooks) and AMBER (Case). The new distributed computer codes will allow new types of biomolecular simulations. The enhanced generalized Born model will be used for structure prediction, prediction of protein-ligand interactions, protein folding, structure-function analyses. This award represents the US side of parallel proposals to the NSF and the French National Center for Scientific Research (CNRS). NSF will cover travel funds and living expenses of the US investigators and graduate students. The CNRS will support visits to the US by the French participants. The project adds an international dimension to research training of graduate students and enhances opportunities for future collaborative partnerships.