CHEMINFORMATICS DATA-MINING FOR MOLECULAR FINGERPRINT CALCULATION

这个子项目是许多利用资源的研究子项目之一 由NIH/NCRR资助的中心拨款提供。子项目的主要支持 而子项目的主要调查员可能是由其他来源提供的， 包括其它NIH来源。 列出的子项目总成本可能 代表子项目使用的中心基础设施的估计数量， 而不是由NCRR赠款提供给子项目或子项目工作人员的直接资金。 项目1。我们正在建立一个10亿个小分子化学（或1B）库，以促进化学信息学研究和化学库设计，以帮助虚拟药物筛选或组合化学库设计。作为目标的一部分，我们将需要访问PSC的集群，以允许我们将化学库SMILE格式转换为2D分子指纹格式，然后我们可以将2D指纹实现到1B库中，我们已经开发了分子结构搜索引擎和平台。项目2.我们将继续进行MD模拟，以完善预测的3D GPCR CB 2受体结构模型（初步工作完成了两篇出版物）。膜模型中3D CB 2受体结构的进一步分子动力学（MD）计算（在脂质/水模拟双层膜系统中）。如此大的生物系统需要在PSC可用的高功率计算设施。此外，我们将探索活性配体结合构象，并进一步评估结合能使用量子力学方法，包括高斯从头计算

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. Project 1. We are in process of building a 1 billion of small molecule chemical (or 1B) library to facilitate the cheminformatics studies and chemical library design in aid of virtual drug screening or combinatorial chemical library design. As a part of goals, we will need to access the cluster at PSC to allow us to convert the chemical library SMILE format to 2D molecular fingerprints format, and then we can implement the 2D fingerprints into the 1B library in which we have already developed the molecular structure search engine and platform. Project2. We will continue the MD simulations to refine the predicted 3D GPCR CB2 receptor structure models (preliminary work completed with two publications). Further molecular dynamics (MD) calculations of the 3D CB2 receptor structure in membrane model (in a lipid/water simulated bilayer membrane system). Such a large biosystem requires high power computing facility that is available @PSC. In addition, we will explore the active ligand binding conformations and further evaluate the binding energy using QM approaches, including GAUSSIAN for ab initio computations