Anchor: A PDB-Wide And Web-Based Discovery Resource Of Small Molecular Weight Pro

锚点：小分子量 Pro 的 PDB 范围和基于网络的发现资源

• 批准号: 7737989
• 负责人: Carlos J. Camacho
• 金额: $ 25.86万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-08 至 2011-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7737989
• 关键词: Agonist; Amino Acids; Ants; Area; Attributes of Chemicals; Binding; Binding Proteins; Biochemical; Biological; Cellular biology; Chemicals; Chemistry; Classification; Collaborations; Collection; Communities; Complement; Complex; Computational Biology; Computer Simulation; Computer software; Data Set; Databases; Disease; Docking; Generic Drugs; Goals; Hot Spot; Internet; Intervention; Libraries; Malignant Neoplasms; Maps; Medical; Methods; Minority; Molecular; Molecular Conformation; Molecular Weight; Nature; Oncogenes; Online Systems; Organism; Pathway interactions; Pennsylvania; Pharmaceutical Chemistry; Pharmaceutical Preparations; Pharmacologic Substance; Pharmacy facility; Play; Predisposition; Property; Protein Databases; Protein p53; Proteins; Reaction; Research; Resolution; Resources; Role; Sampling; Screening procedure; Solvents; Source; Specific qualifier value; Staging; Structure; Surface; Techniques; Technology; Triplet Multiple Birth; Universities; Validation; Virtual Library; Weight; abstracting; analog; base; design; drug discovery; flexibility; high throughput screening; improved; insight; interest; medical schools; molecular recognition; novel; numb protein; programs; protein complex; protein protein interaction; protein structure; scaffold; small molecule; small molecule libraries; tool; virtual

DESCRIPTION (provided by applicant): R21: ANCHOR: A PDB-Wide And Web-based Discovery Resource of Small Molecular Weight Protein Interaction (Ant)agonists. PI: Alexander Doemling Departments of Pharmacy and Chemistry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15260, USA PI: Carlos J. Camacho Department of Computational Biology, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA Abstract Protein-protein interactions (PPIs) constitute an emerging class of targets for pharmaceutical intervention with the PDB providing a highly valuable source for structural information. However, the diversity of PPIs does not fit well in the current drug discovery paradigm that focus almost exclusively on screening large historical collections of (commercially available) small molecular weight compounds. Despite computational limitations on the sampling of chemical space and scoring of protein-small molecule docked conformations, in silico screening methods continue to be developed and improved as credible and complementary alternatives to high-throughput biochemical compound screening (HTS). The ultimate goal of this proposal is to overcome these limitations by developing a virtual screening technology of virtual libraries that by design have a built-in amino acid hot spot, or "anchor," that is burying deep into acceptor proteins complemented with real multi-component reaction (MCR) chemistry. Specific aims are to (a) classify the PDB based on their drug-like susceptibility such as single anchors or higher motifs, doublets and triplets of amino-acids; (b) develop a unique set of anchor- analogs for the 20 amino acids and a database of >100 small molecular weight scaffolds to create a novel virtual, but chemically accessible, library to target pre-screened protein-protein interactions; (c) set up a systematic virtual screening of the PPIs based on the pre-docking of anchor-analogs to the PPI complex structure; and (d), provide a public resource for the prediction of (ant)agonists based on novel compounds, while proactively contact structural groups with easy access to the target protein to establish collaborations where compounds will be rapidly synthesized in a one-pot manner (i.e., using MCR) for validation. A PDB wide mapping of drug-like targets combined with novel compounds specifically designed to mimic the chemistry and structure of deeply buried anchor residues of PPIs is an original approach to discover (ant)agonists as tools to elucidate biological pathways or as starting points for medicinal chemistry programs.

描述（由申请人提供）：R21：锚：小分子量蛋白质相互作用（Ant）激动剂的PDB范围和基于Web的发现资源。主要研究者：亚历山大·杜姆林（Alexander Doemling），匹兹堡大学医学院药学和化学系，匹兹堡，宾夕法尼亚州15260，美国PI：卡洛斯J.卡马乔计算生物学系，匹兹堡大学，匹兹堡，宾夕法尼亚州15260，蛋白质-蛋白质相互作用（PPI）构成一类新兴的药物干预靶点，PDB为结构信息提供了非常有价值的来源。然而，PPI的多样性并不适合当前的药物发现范式，该范式几乎完全集中在筛选大量（市售）小分子量化合物的历史集合上。尽管在化学空间的采样和蛋白质-小分子对接构象的评分上存在计算限制，但计算机筛选方法继续被开发和改进，作为高通量生化化合物筛选（HTS）的可靠和补充替代方案。该提议的最终目标是通过开发虚拟文库的虚拟筛选技术来克服这些限制，所述虚拟文库通过设计具有内置的氨基酸热点或“锚”，所述氨基酸热点或“锚”深埋到受体蛋白中，并补充有真实的多组分反应（MCR）化学。具体目的是（a）基于它们的药物样敏感性（例如单锚或更高基序、氨基酸的双联体和三联体）对PD B进行分类;（B）开发一组独特的20种氨基酸的锚-类似物和>100种小分子量支架的数据库，以创建新的虚拟的、但化学上可接近的文库，以靶向预先筛选的蛋白质-蛋白质相互作用;（c）基于锚类似物与PPI复合物结构的预对接，建立PPI的系统虚拟筛选;以及（d）提供用于基于新化合物预测（抗）激动剂的公共资源，同时主动接触易于接近靶蛋白的结构基团以建立合作，其中化合物将以一锅法（即，使用MCR）进行验证。PDB广泛的药物样靶点图谱结合专门设计用于模拟PPI深埋锚残基化学和结构的新型化合物，是发现（抗）激动剂作为阐明生物学途径工具或作为药物化学项目起点的原始方法。