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.

这个子项目是许多利用 由NIH/NCRR资助的中心赠款提供的资源。子项目和 研究者（PI）可能从另一个NIH来源获得了主要资金， 因此可以在其他CRISP条目中表示。所列机构为 中心，但不一定是研究者所在的机构。 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-功能研究中具有广泛的应用。 具体目标是： 1.开发在几何和化学复杂性不断增加的层次结构中对接配体的算法。 虽然配体-蛋白质复合物的构型空间是巨大的，但它也是高度冗余的，并且受到复合物的排除体积的限制。 将分子对接为状态集合允许利用这些特征的方法。 通过将分子表示为复杂性不断增加的层次结构，有可能在计算的早期排除最不利的构象。 这样的分层算法应该以与相关构象相同的方式适用于相关化学。 这些方法将探索更多的状态和化学比现在可以考虑对接计算。 溶剂化能模型的改进也将进行研究。 2.在一个性能良好的实验系统中测试新算法。 新的算法将测试他们的能力，以预测新的配体和几何形状的两个模型系统：AmpC β-内酰胺酶和溶菌酶中的空腔网站。 这两种蛋白质都易于使用，并为对接研究提供了明确的位点。 在最简单的层面上，实验测试将评估算法的“命中率”及其通过结构确定的准确性。 更重要的是，这将为复杂地层中热力学驱动力的研究提供基础. 大量的初步结果表明，新算法是可行的。 例如，见以下条款： a.构象系综在柔性配体对接中的应用 B.通过家族对分子进行对接以增加数据库筛选中命中的多样性 C.具有多配体残基构象和多残基同一性的蛋白质-蛋白质对接 该模型系统似乎非常适合测试新的算法。 例如，见以下条款： a. AmpC β-内酰胺酶活性位点的热点定位 B.基于结构的新型AmpC β-内酰胺酶非共价抑制剂的发现 C.分子对接评分函数的模型结合位点 通过RBVI提供的交互式计算机图形是可视化和评估对接计算的关键，也是基于结构发现新配体的关键。 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。