DESIGN AND TESTING OF DOCKING ALGORITHMS

对接算法的设计和测试

• 批准号: 8170498
• 负责人: Brian K Shoichet
• 金额: $ 1.78万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-07-01 至 2011-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8170498
• 关键词: Active Sites; Address; Algorithms; AmpC beta-lactamases; Binding Sites; Biological Models; Chemicals; Chemistry; Complex; Computer Graphics; Computer Retrieval of Information on Scientific Projects Database; Databases; Docking; Family; Funding; Goals; Grant; Hot Spot; Institution; Investigation; Ligands; Maps; Methods; Modeling; Molecular; Molecular Conformation; Muramidase; Proteins; Research; Research Personnel; Resources; Site; Source; Structure; System; Testing; Thermodynamics; United States National Institutes of Health; Work; base; design; driving force; flexibility; inhibitor/antagonist; novel; protein complex

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Our long term goal is to address the "docking problem," that of predicting the structures and ligand identities of protein-ligand complexes. Methods to do so would have wide application in structure-function studies. The specific aims are: 1. To develop algorithms that dock ligands in hierarchies of increasing geometrical and chemical complexity. Although the configuration space for ligand-protein complexes is enormous, it is also highly redundant and constrained by the excluded volume of the complex. Docking molecules as ensembles of states allow for methods that take advantage of these features. By representing molecules in hierarchies of increasing complexity, it may be possible to exclude most unfavorable conformations early in the calculation. Such a hierarchical algorithm should be applicable to related chemistries in the same way as to related conformations. These methods would explore many more states and chemistries than can now be considered in docking calculations. Improvements to solvation energy models will also be investigated. 2. To test the new algorithms in a well-behaved experimental system. The new algorithms will be tested for their ability to predict new ligands and geometries for two model systems: AmpC beta-lactamase and a cavity site in lysozyme. Both proteins are easy to work with and provide well defined sites for docking studies. At the simplest level, the experimental tests will evaluate "hit-rates" for the algorithms and their accuracy through structure determination. More fundamentally, this will alllow for investigation of the thermodynamic driving forces in complex formation. Extensive prelimary results suggest that the new algorithms are feasible. See the following articles for instance: a. Flexible Ligand Docking Using Conformational Ensembles b. Docking Molecules by Families to Increase the Diversity of Hits in Database Screens c. Protein-Protein Docking with Multiple Ligand Residue Conformations and Multiple Residue Identities The model system seems to be well suited to testing the new algorithms. See the following articles for instance: a. Mapping the Active Site of AmpC beta-Lactamase for Hot Spots b. Structure-based Discovery of a Novel, Non-Covalent Inhibitor of AmpC beta-Lactamase c. A Model Binding Site for Testing Scoring Functions in Molecular Docking Interactive computer graphics available through the RBVI are key to visualizing and evaluating how well docking calculations have performed, and to the structure-based discovery of new ligands. They are also very useful for crystallographic modeling and structure determination, which is part of the experimental testing aspect of this project.

该子项目是利用该技术的众多研究子项目之一 资源由 NIH/NCRR 资助的中心拨款提供。子项目及 研究者 (PI) 可能已从 NIH 的另一个来源获得主要资金， 因此可以在其他 CRISP 条目中表示。列出的机构是 对于中心来说，它不一定是研究者的机构。 我们的长期目标是解决“对接问题”，即预测蛋白质-配体复合物的结构和配体身份。 这样做的方法将在结构功能研究中有广泛的应用。 具体目标是： 1. 开发将配体对接在几何和化学复杂性不断增加的层次结构中的算法。 尽管配体-蛋白质复合物的构型空间巨大，但它也是高度冗余的，并且受到复合物排除体积的限制。 将分子对接为状态集合允许利用这些特征的方法。 通过以复杂性不断增加的层次结构来表示分子，可以在计算早期排除最不利的构象。 这种分层算法应该以与相关构象相同的方式适用于相关化学。 这些方法将探索比现在对接计算中可以考虑的更多的状态和化学性质。 还将研究溶剂化能量模型的改进。 2. 在性能良好的实验系统中测试新算法。 新算法将测试其预测两个模型系统新配体和几何结构的能力：AmpC β-内酰胺酶和溶菌酶中的空腔位点。 这两种蛋白质都易于使用，并为对接研究提供明确的位点。 在最简单的层面上，实验测试将通过结构确定来评估算法的“命中率”及其准确性。 更重要的是，这将允许研究复杂地层中的热力学驱动力。 大量的初步结果表明新算法是可行的。 例如，请参阅以下文章： 一个。使用构象集合进行灵活的配体对接 b.通过家族对接分子以增加数据库筛选中命中的多样性 c.具有多个配体残基构象和多个残基身份的蛋白质-蛋白质对接 该模型系统似乎非常适合测试新算法。 例如，请参阅以下文章： 一个。绘制 AmpC β-内酰胺酶的热点活性位点图 b.基于结构的 AmpC β-内酰胺酶新型非共价抑制剂的发现 c.用于测试分子对接中评分功能的模型结合位点 通过 RBVI 提供的交互式计算机图形对于可视化和评估对接计算的执行情况以及基于结构的新配体发现至关重要。 它们对于晶体学建模和结构测定也非常有用，这是该项目实验测试方面的一部分。