RAPID AND RIGOROUS BINDING AFFINITY COMPUTATION

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 目前计算结合亲和力(DeltaG)的方法需要非常长的模拟时间。因此，这种方法在药物设计中是不可行的，因为在药物设计中，化合物的虚拟筛选是重要的。建议项目的目的是研究DeltaG计算的新方法，最终目标是非常快速和准确地估计结合亲和力。这位研究人员在统计力学和计算分子生物物理学方面拥有坚实的背景，最近发表了五篇关于新型deltaG方法的同行评议论文。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Current approaches for computing binding affinities (deltaG) require very long simulation. Thus, such methods are not feasible for use in drug design, where virtual screening of compounds is important. The purpose of the proposed project is to investigate novel approaches for deltaG computation, the eventual goal being very fast and accurate estimation of binding affinities. The investigator has a solid background in statistical mechanics and computational molecular biophysics, and has recently published five peer-reviewed papers on novel deltaG methodologies.