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.

项目摘要 /摘要 一个长期的目标是将化学试剂带入生物学，扩展了开发工具的开发 社区越来越依赖：锌（http：//zinc.docking.org），花花公子（http://dude.docking.org），码头 Blaster（http://blaster.docking.org）和SEA（http://sea.docking.org）。第二个进球探讨了 基于配体的药理学组织的基本基础和影响，利用它来预测 与生物学相关的多药学，我们首次在该领域主张。 1。将化学变成生物学的新公共工具。答：我们开发的锌工具使人们能够输入 目标并找到所有以其已知的试剂，或输入分子以找到其已知和预测的靶标， 测试其中几个。 B.目标在途径和网络中运行。我们介绍了允许一个人的工具 从化学和生物形式的相似性组织的“可点击”网络中的目标到目标。 C.通过将化学信息学直接引入码头爆炸器，调查人员可以搜索他们的命中列表中的类似物，以了解 脚手架，官能团及其对接的相互作用。 D.我们开发一个库来解决密钥 通过将所有库化合物预通向目标的表型筛选，目标ID的问题，每个目标 具有两个或多个正交分子注释（带有诺华和Sigma-Aldrich）。当这样的正交时 分子在屏幕上共享表型，这表明基本目标。 2。比较和结合基于配体的基于结构和生物信息学的相似性。链接目标 配体相似性揭示了与生物信息学所暗示的相似之处。这是 令人满意但难题。我们在这里A.全面将生物信息学目标网络与预测的目标网络进行比较 通过配体相似性。初步结果表明，这些网络主要是正交的，但很有趣 重叠区域（在C中探索，下面）。 B.了解相同结合的结构基础 配体“无关”蛋白质，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，不同的蛋白质结合了完全相同的配体 程序。这些程序是否可以识别无关蛋白质中的结合位点实际上相似？如何 蛋白质可以识别出多种方法吗？ C.在生物和生物 化学信息学社区重叠，生物信息学在疾病中实现成对的目标，而 化学信息学表明这对可以由试剂共同调节。对于这些对，共享 多疗法在功能上是有意义的。我们预测并测试50。 尽管这些目标是雄心勃勃的，但它们的合理性得到了广泛的初步结果的支持。