Cloud computing platform for virtual screening and drug discovery.

摘要： 这是一个第二阶段的应用程序，用于继续开发化学分析平台，一个可扩展的计算平台。 使用Amazon EC2云计算实现化学库虚拟筛选的基础设施 环境和自动对接工具。 基于结构的虚拟筛选是药物发现过程中的重要工具（1-7）。使用 计算工具已经允许筛选大型化合物库，以识别推定的 配体-受体相互作用（8-9）。有效靶点和治疗化合物的鉴定具有长期意义。 这对公众健康和制药业的经济实力都很重要。 基于受体的虚拟筛选（VS）是一种使用计算工具的技术， 分子量化合物转化为蛋白质受体或酶。这种技术最常用于药物治疗。 发现，其中一个大型的化学结构库可以对接和评分，以评估如果 化合物以结合药物靶标。然而，高通量虚拟筛选是计算密集型的， 而构建、维护和管理专用计算集群的成本限制了对这些资源的访问 大型大学和商业企业的技术。基于互联网的计算，也称为云计算 计算，是一种业务服务模型，其中计算资源按需访问， 需要，并且价格合理，可扩展且安全。 我们已经完成了第一阶段的目标，即构建一个基于Web的界面来管理用户、作业和显示 结果来自虚拟对接屏幕。当前系统采用Amazon EC2环境， 成功地用于筛选超过230万个结构的化学库， 时尚.在与生物技术合作伙伴的合作下，我们正在寻找化学先导， 对抗前列腺癌细胞系。 在此阶段，我们将通过以下技术扩展当前系统的功能 成果：（1）整合了更多的化学品库和库过滤工具，以集中搜索空间 （2）通过整合数据分析，提高最终用户评估结果的能力 和可视化工具;（3）通过我们的筛选结果分析验证这种方法 合作伙伴和商业伙伴。

Abstract: This is a Phase II application for continued development of the Chemalytics Platform, a scalable computational infrastructure to enable virtual screening of chemical libraries using the Amazon EC2 cloud computing environment and automated docking tools. Structure-based virtual screening is an important tool in the drug discovery process (1-7). The use of computational tools has allowed for the screening of large libraries of chemical compounds to identify putative ligand-receptor interactions (8-9). The identification of valid targets and therapeutic compounds has long-term importance both to the public health and the economic strength of the pharmaceutical industry. Receptor-based virtual screening (VS) is a technique in which computational tools are used dock small molecular weight compounds into a protein receptor or enzyme. This technique is most often used in drug discovery, where a large library of chemical structure can be docked and scored to assess the potential if a compound to bind to a drug target. However, high-throughput virtual screening is computationally intensive, and the cost of building, maintaining, and managing a dedicated computing cluster limits access to these technologies to large universities and commercial enterprises. Internet-based computing, also known as cloud computing, is a business service model in which computational resources are accessed on-demand as needed, and is affordable, scalable, and secure. We have completed the Phase I goals of a building a web-based interface to manage users, jobs, and display results from virtual docking screens. The current system employs the Amazon EC2 environment and has been successfully used to screen chemical libraries of more than 2.3 million structures in an economical and rapid fashion. In collaboration with a biotechnology partner, we are now pursuing chemical leads which are active against prostate cancer cell lines. In this phase we will expand the capabilities of the current system through the following technical achievements: (1) integration of additional chemical libraries and library filtering tools to focus search space prior to docking; (2) enhancement of end user ability to evaluate results through integration of data analysis and visualization tools; (3) validation of this approach through analysis of screening results with our collaborators and commercial partners.