A Web-Based Automatic Virtual Screening System

项目总结/摘要 一个长期的目标是把小分子带给生物学家和化学生物学家， 快速识别试剂的工具和库。第二个目标使用这些库和工具来预测 生物活性的关键化合物类，推进科学和演示的概念验证。 该研究项目引入的工具已成为虚拟筛选的核心。ZINC数据库 是该领域中使用最广泛的化合物库，而我们的DUD和DUD-E基准测试在 虚拟筛选近年来，我国超大型图书馆的发展受到了业界的广泛关注。的 相似性包围法（SEA）将化学信息学目标预测带到了一个大的社区，我们 已经用它来预测药物脱靶，它们的副作用，以及所谓的惰性分子的活动。 在这里，我们扩展了这两个项目，进一步开发了aim 1中的社区库和工具， 目标2中的生物活性预测。具体目标是： 目标1.将化学引入生物学的新工具。最后一个时期的一个令人兴奋的结果是， 超大图书馆虽然一个可访问的超过200亿个分子的库扩展了我们的视野，但这两个 它们所源自的组分反应不可避免地受到限制。我们将A。建立“化学共同体” 从学术实验室获得的更精细的虚拟分子，在目标2，B中测试它们。扩大 化学可用于共价对接，以开发新的社区可访问的选择性 用于共价抑制剂发现的亲电体，C.我们将优化广泛使用的DUDE基准测试， 引入新的子集来解决它们仍然存在的偏见。D.我们将整合到ZINC 方法，使相似性搜索的类似物在次线性时间。 目标2.高价值化合物库及其活性。我们将A。测试更精细的 来自aim 1的虚拟库，其中它们被实验性地测试，B。测试新的共价亲电子文库 在针对SARS-2相关蛋白酶3CLPro和TMPRSS 2的对接活动中。C.扩大我们对 通过化学信息学进行目标发现，重点关注在生物学中广泛使用的化合物，因为它们 无活性：药物辅料和通常被视为安全的食品添加剂。D.询问GRAS是否 分子具有靶向药理学，正如我们在药物赋形剂中发现的那样， 实验性的 虽然这些目标雄心勃勃，但广泛的初步结果支持其可行性。

PROJECT SUMMARY / ABSTRACT A long-term goal is to bring small molecules to biologists and chemical biologists, developing easy-to-use tools and libraries that rapidly identify reagents. A second goal uses these libraries and tools to predict biological activity for key compound classes, advancing the science and demonstrating proof-of-concept. The tools introduced by this research program have become central to virtual screening. The ZINC database is the most widely used compound library in the field, while our DUD and DUD-E benchmarks are ubiquitous in virtual screening. Recently, our development of ultra-large libraries has been embraced by the field. The Similarity Ensemble Approach (SEA) brings chemoinformatic target prediction to a large community, and we have used it to predict drug off-targets, their side effects, and the activities of supposedly inert molecules. Here we extend both projects, further developing community libraries and tools in aim 1, applying these to the prediction of biological activities in aim 2. The specific aims are: Aim 1. New tools to bring chemistry to biology. An exciting result of the last period was the introduction of ultra-large libraries. While an accessible library of >20 billion molecules has expanded our horizons, the two component reactions from which they derive are inevitably limiting. We will A. develop a “chemistry commons” of more elaborate virtual molecules available from academic labs, testing them in aim 2, B. expand the chemistry available for covalent docking to develop new community-accessible libraries of selective electrophiles for covalent inhibitor discovery, C. We will optimize the widely-used DUDE benchmarks, introducing new subsets to address the biases that they certainly still retain. D. We will integrate into ZINC methods that enable similarity searches for analogs in sublinear time. Aim 2. Libraries of high value compounds, and their activities. We will A. test the utility of more elaborate virtual libraries from aim 1 where they are experimentally tested, B. test the new covalent electrophilic libraries in docking campaigns against SARS-2 relevant proteases 3CLPro and TMPRSS2. C. expand our interest in target discovery by chemoinformatics, focusing on compounds that are widely used in biology because they are inactive: drug excipients and Generally Regarded As Safe food additives. D. ask whether GRAS molecules have on-target pharmacology, as we found with drug excipients, testing our predictions experimentally. Whereas these goals are ambitious, extensive preliminary results support their feasibility.