Docking the Proteome for New Ligands and Functional Associations

对接蛋白质组以获得新配体和功能关联

• 批准号: 8911649
• 负责人: Trent E Balius
• 金额: $ 2.97万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-01-01 至 2015-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8911649
• 关键词: ADRB2 gene; Aden; Biochemistry; CHES1 gene; Characteristics; Chemicals; Chemistry; Collaborations; Communities; Computing Methodologies; Databases; Development; Docking; Drug Targeting; Drug toxicity; Epidermal Growth Factor Receptor; G Protein-Coupled Receptor Genes; Geometry; Goals; Hand; Histamine; Ligands; Link; MAP Kinase Gene; MAPK14 gene; Mechanics; Methods; Metric; Modeling; Molecular; Nature; One-Step dentin bonding system; Pharmaceutical Preparations; Pharmacology; Proteins; Proteome; Retrospective Studies; Roentgen Rays; Structure; Techniques; Testing; Time; acrosin; base; drug mechanism; interest; public health relevance; small molecule; structural biology; tool

DESCRIPTION (provided by applicant): Two overarching goals in chemical and structural biology are finding ligands for every protein (Schreiber, S. L., Nat Chem Biol 2005), and identifying the functions and associations among proteins based on their structure. For the last decade, these goals have been pursued empirically (Gerlt, J. A.; et al., Biochemistry 2011). I will argue that there is a need for computation in both ligand discovery and functional association of proteins. I will also argue that such goals, correctly framed, are now becoming obtainable for computational methods, and that at scale they are essentially only pragmatic computationally. In the last five years, structure-based docking screens have seen two important advances. First, the technique has predicted new chemotypes for over 60 targets. Whereas docking retains key liabilities, and cannot rank order ligands, it can now, with some reliability, prioritize likely molecules as candidates. Second, the technique has become fast. I will show that the method can screen the structurally accessible and interesting proteome-about 4000 targets-in four months. A second development is the advent of chemoinformatics techniques to compare targets by ligand similarity, rather than the structural or sequence similarity. It turns out that ligand similarity reveals associations that are curiously opaque to sequence and structure, and this has been used to make surprising and high-profile predictions of drug off-targets (Keiser, M. J.; et al., Relating protein pharmacology by ligand chemistry, Nat Biotech 2007,25(2), 197-206), drug mechanism of action (Gregori-Puigjane, E.; et al., Proc Natl Acad Sci U S A 2012; Keiser, M. J.; et al., Nature 2009), and drug toxicities (Lounkine, E.; et al., Nature 2012). Very recently the technique has been expanded to reorganize the GPCR dendogram (Lin, H.; et al., Nature Methods 2013, accepted), and I will take that tack to a whole proteome level by relating docking hit lists to associate proteins. The docking hit lists and the associations among them will enable three questions: "What compounds are available that might modulate my target", "what other targets might my target be associated with?" and, when appropriate, "what is the function of my target?" All results will be made accessible online.

描述（由申请人提供）：化学和结构生物学的两个总体目标正在为每种蛋白质找到配体（Schreiber，S。L.，Nat Chem Biol 2005），并根据其结构确定蛋白质之间的功能和关联。在过去的十年中，这些目标是通过经验追求的（Gerlt，J。A。; et al。，Biochemistry 2011）。我会 认为在配体发现和蛋白质功能关联中都需要计算。我还将认为，正确构架的这样的目标现在可以用于计算方法，并且从本质上讲，它们只是在务实的计算上。在过去的五年中，基于结构的对接屏幕已经看到了两个重要的进步。首先，该技术预测了60多个目标的新化学型。虽然停靠保留了关键负债，并且不能对配体进行排名，但现在可以使用一些可靠性将可能的分子作为候选者确定优先级。其次，该技术已经快速。我将证明该方法可以筛选在四个月内的结构上可访问且有趣的蛋白质组4000个目标。第二个发展是化学信息学技术的出现，以通过配体相似性比较靶标，而不是结构或序列相似性。事实证明，配体相似性揭示了与序列和结构奇怪的不透明的关联，这已被用来对药物脱离靶向的药物进行令人惊讶和高调的预测（Keizer，M。J.; et al。，与配体化学相关的蛋白质药理学，通过配体化学，NAT Biotech 2007,25（2），197-206，药物，杂技（EDJ）。 al。最近，该技术已扩展以重组GPCR树状图（Lin，H。; et al。，Nature Methods 2013，被接受），我将通过将docking Hit列表与将蛋白质关联来将其粘贴到整个蛋白质组水平上。对接命中列表及其中的关联将使三个问题：“有哪些可以调节我的目标的化合物”，“我的目标可能与哪些其他目标相关联？”而且，在适当的时候，“我的目标的功能是什么？”所有结果都将在线访问。