A Web-Based Automatic Virtual Screening System

基于网络的自动虚拟筛选系统

• 批准号: 9183613
• 负责人: John J. Irwin
• 金额: $ 34.87万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-08-01 至 2020-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9183613
• 关键词: Address; Area; Base Sequence; Benchmarking; Binding; Binding Proteins; Binding Sites; Bioinformatics; Biological; Biology; Chemicals; Chemistry; Communities; Complex; Databases; Disease; Docking; Drug Targeting; Goals; Gold; Informatics; Internet; Island; Laboratories; Libraries; Ligands; Link; Location; Methods; Neighborhoods; Online Systems; Pathway interactions; Pharmacology; Phenotype; Positioning Attribute; Proteins; Reagent; Research Personnel; Role; Sea; Side; Site; Structure; System; Techniques; Testing; Time; Visit; Work; Zinc; abstracting; analog; base; design; drug discovery; flexibility; functional genomics; functional group; interest; programs; scaffold; screening; small molecule; tool; tool development; virtual

Project Summary / Abstract A long-term goal is to bring chemical reagents to biology, extending the development of tools on which the community increasingly depends: ZINC (http://zinc.docking.org), DUDE (http://dude.docking.org), DOCK Blaster (http://blaster.docking.org) and SEA (http://sea.docking.org) among them. A second goal explores the fundamental bases and implications of a ligand-based organization of pharmacology, leveraging it to predict biologically-relevant polypharmacology, we argue for the first time in the field. 1. New public tools to bring chemistry to biology. A. We develop ZINC tools that enable one to input a target and find all available reagents known for it, or to input a molecule to find its known and predicted targets, testing several of these. B. Targets operate in pathways and networks. We introduce tools that allow one to island hop from target-to-target in “clickable” networks organized by both chemo- and bio-informatic similarity. C. By bringing chemoinformatics directly into DOCK Blaster, investigators can search their hit lists for analogs, scaffolds, functional groups, and their docked interactions. D. We develop a library that addresses the key problem of phenotypic screening, target ID, by pre-annotating all library compounds to targets, with each target having two or more orthogonal molecules annotated (with Novartis & Sigma-Aldrich). When such orthogonal molecules share a phenotype in a screen, it suggests the underlying target. 2. Comparing and combining ligand-based, structure-based & bioinformatic similarity. Linking targets by ligand similarity reveals associations very different from what bioinformatics would suggest. This is gratifying but puzzling. Here we A. Comprehensively compare bioinformatic target networks to those predicted by ligand similarity. Preliminary results suggest that these networks are mostly orthogonal but have intriguing areas of overlap (explored in C, below). B. To understand the structural basis for the binding of identical ligands by “unrelated” proteins, we compare the x-ray structures of hundreds of complexes where two dissimilar proteins bind exactly the same ligands, using widely-used, structure-based site comparison programs. Can these programs recognize the binding sites in the unrelated proteins as, in fact, similar? How many ways can proteins recognize the same ligand functional groups? C. In the areas where the bio- and chemoinformatics neighborhoods overlap, the bioinformatics implicates pairs of targets in a disease, while chemoinformatics suggest that that the pair can be co-modulated by a reagent. For these pairs, shared polypharmacology is functionally meaningful. We predict and test 50. Whereas these goals are ambitious, their plausibility is supported by extensive preliminary results.

项目概要/摘要 长期目标是将化学试剂引入生物学，扩展工具的开发 社区越来越依赖：ZINC (http://zinc.docking.org)、DUDE (http://dude.docking.org)、DOCK 其中包括 Blaster (http://blaster.docking.org) 和 SEA (http://sea.docking.org)。第二个目标探索 基于配体的药理学组织的基本基础和影响，利用它来预测 生物学相关的多药理学，我们首次在该领域争论。 1. 将化学引入生物学的新公共工具。 A. 我们开发了 ZINC 工具，使人们能够输入 定位并找到已知的所有可用试剂，或输入分子以找到其已知和预测的目标， 测试其中几个。 B. 目标在路径和网络中运作。我们推出的工具可以让人们 在由化学和生物信息学相似性组织的“可点击”网络中从目标到目标的岛跳跃。 C. 通过将化学信息学直接引入 DOCK Blaster，研究人员可以在他们的命中列表中搜索类似物， 支架、功能组及其对接的相互作用。 D. 我们开发了一个解决关键问题的库 表型筛选、目标 ID 的问题，通过将所有库化合物预先注释到目标，每个目标 具有两个或多个注释的正交分子（使用 Novartis & Sigma-Aldrich）。当这样的正交 分子在屏幕上共享一个表型，它表明了潜在的目标。 2. 比较和结合基于配体、基于结构和生物信息学的相似性。链接目标 通过配体相似性揭示的关联与生物信息学所暗示的非常不同。这是 令人欣慰但又令人费解。在这里我们 A. 全面比较生物信息学目标网络与预测的网络 通过配体相似性。初步结果表明，这些网络大多是正交的，但有一些有趣的地方 重叠区域（在下面的 C 中进行了探讨）。 B. 了解相同分子结合的结构基础 通过“不相关”蛋白质的配体，我们比较了数百个复合物的 X 射线结构，其中两个 使用广泛使用的基于结构的位点比较，不同的蛋白质结合完全相同的配体 程序。这些程序能否将不相关蛋白质中的结合位点识别为实际上相似的结合位点？如何 蛋白质可以通过多种方式识别相同的配体官能团？ C. 在生物和 化学信息学邻域重叠，生物信息学暗示疾病中的靶标对，而 化学信息学表明该对可以通过试剂共同调节。对于这些对，共享 多药理学具有功能意义。我们预测并测试 50。 尽管这些目标雄心勃勃，但其合理性得到了广泛的初步结果的支持。