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首要目标是为每种蛋白质找到配体（Schreiber， S. L., Nat Chem Biol 2005），并根据蛋白质的结构确定蛋白质之间的功能和联系。在过去的十年中，这些目标一直在追求经验（Gerlt， J. A. et al., Biochemistry 2011）。我将