Computational Mapping of Proteins for Binding of Ligands

配体结合的蛋白质计算图谱

• 批准号: 7818904
• 负责人: SANDOR VAJDA
• 金额: $ 48.75万
• 依托单位: BOSTON UNIVERSITY (CHARLES RIVER CAMPUS)
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-30 至 2011-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7818904
• 关键词: Accounting; Algorithms; Amino Acids; Applications Grants; Binding; Binding Proteins; Binding Sites; Biochemical; Biological Assay; Chemistry; Complex; Computing Methodologies; Docking; Drug Delivery Systems; Drug Design; Environment; Free Energy; Funding; Future; Generations; Goals; Grant; Hot Spot; Interleukin 2 Receptor; Interleukin-2; Libraries; Ligand Binding; Ligands; Location; Maps; Measures; Membrane Proteins; Methods; Molecular; Molecular Conformation; Molecular Probes; Nature; Parents; Peptide Fragments; Pharmaceutical Preparations; Pharmacologic Substance; Positioning Attribute; Protein Binding; Protein Region; Protein-Protein Interaction Map; Proteins; Recovery; Reporting; Research; Roentgen Rays; Side; Site; Structure; Surface; United States National Institutes of Health; Work; X-Ray Crystallography; base; cytokine; design; flexibility; functional group; improved; inhibitor/antagonist; interleukin 2 inhibitor; numb protein; protein protein interaction; protein structure; public health relevance; receptor; small molecule

DESCRIPTION (provided by applicant): This proposal is the competitive revision (Notice NOT-OD-09-58, NIH Announces the Availability of Recovery Act Funds for Competitive Revision Applications) of the grant "Computational Mapping of Proteins for the Binding of Ligands". Mapping methods place molecular probes - small molecules or functional groups - on the surface of proteins in order to identify the most favorable binding positions. Since regions of the protein surface that are major contributors to the binding free energy in drug-protein interactions also bind a variety of small organic molecules, mapping can identify such "hot spots" and the number of probe molecules bound is a good predictor of druggability. The parent proposal focused on "traditional" drug targets that naturally bind small molecular ligands. The general goal of this revision is to extend the analysis to the identification and characterization of druggable sites in protein-protein interfaces. Such analysis facilitates the discovery of small molecules that can inhibit or modulate the association of two proteins, an important emerging problem in pharmaceutical research. Application of mapping to a number of protein-protein interaction (PPI) targets has shown that the method always identifies at least some fraction of the site which can bind small molecular inhibitors within the protein-protein interface region, even when starting from the structure of a ligand-free protein. In Aim 1 we will further study the generality of this observation by mapping a variety of PPI targets on which structural and biochemical information is available. We will also study the interactions between fragments and their protein environments in the binding site by using target-specific probe libraries based on the known ligands of each target. Since binding of small molecules frequently requires conformational changes to form appropriate pockets in a relatively flat protein-protein interface, in Aim 2 we develop a method to account for side chain flexibility prior to mapping. The algorithm combines statistical analysis and energy minimization to identify "moveable" side chains and their potential conformational states in the vicinity of the "hot spot" identified by the initial mapping. Protein structures are generated by combining the potential conformations of moveable side chains. The re-mapping of such adjusted structures generally agrees well with results obtained for the ligand-bound proteins, and hence substantially improves the predictive power of the method. Aim 3 is the theoretical and experimental characterization of hot spots that enable the binding of small molecular inhibitors in the binding interface of IL-2 with IL-2R1, an exemplary PPI target. The binding energies that different portions of the known inhibitors derive from their interactions with the protein have not been systematically elucidated. We will measure experimental binding energies and binding orientations for different molecular fragments derived from these known IL-2 inhibitors, using quantitative biochemical and biophysical assays as well as X-ray crystallography, and will compare the results with those obtained computationally using these same fragments as probes. The results will provide new information on the physicochemical and structural features that render a difficult PPI site druggable, which we will use to further refine our computational method. PUBLIC HEALTH RELEVANCE: Mapping methods place molecular probes - small molecules or functional groups - on the surface of proteins in order to identify the most favorable binding positions, and provide information on the druggability of such site. We focus on the identification and characterization of druggable sites capable of binding small molecular inhibitors of protein-protein interactions, an important emerging problem in pharmaceutical research.

描述（由申请人提供）：该提案是竞争性修订（NOT-OD-09-58，NIH，宣布用于竞争性修订应用程序的恢复法案资金）的赠款“蛋白质的计算映射以结合配体的结合”。映射方法将分子探针（小分子或官能基团）放在蛋白质的表面上，以识别最有利的结合位置。由于蛋白质表面的区域是药物蛋白相互作用中结合自由能的主要促成者的区域，还结合了多种小有机分子，映射可以识别这种“热点”，并且结合的探针分子的数量是吸毒性的良好预测指标。父母的建议集中于自然结合小分子配体的“传统”药物靶标。此修订的一般目标是将分析扩展到蛋​​白质 - 蛋白质界面中可药物位点的识别和表征。这种分析促进了可以抑制或调节两种蛋白质的关联的小分子的发现，这是药物研究中一个重要的新兴问题。将映射到许多蛋白质蛋白相互作用（PPI）靶标的应用表明，该方法始终识别位点的至少一部分，即使从配体无蛋白质的结构开始时，该方法即使蛋白质蛋白界面区域内的小分子抑制剂也可以结合小分子抑制剂。在AIM 1中，我们将通过绘制各种PPI目标，进一步研究该观察结果的一般性，这些靶标有结构和生化信息。我们还将通过根据每个靶标的已知配体使用目标特异性探针文库来研究片段及其蛋白质环境之间的相互作用。由于小分子的结合经常需要构象变化才能在相对平坦的蛋白质 - 蛋白质界面中形成适当的口袋，因此在AIM 2中，我们开发了一种在映射之前说明侧链灵活性的方法。该算法结合了统计分析和能量最小化，以识别“可移动”的侧链及其潜在的构象状态在初始映射确定的“热点”附近。通过结合可移动侧链的潜在构象来产生蛋白质结构。这种调整后的结构的重新映射通常与配体结合蛋白的结果非常吻合，因此实质上提高了该方法的预测能力。 AIM 3是热点的理论和实验表征，它使IL-2的结合界面中的小分子抑制剂与IL-2R1（示例性PPI靶标）结合。尚未系统地阐明已知抑制剂与蛋白质相互作用的不同部分从其与蛋白质相互作用的结合能。我们将使用定量的生化和生物物理测定法以及X射线晶体学来测量从这些已知的IL-2抑制剂中得出的不同分子片段的实验结合能和结合方向，并将结果与​​使用这些相同片段与探针相同的计算获得的结果进行比较。该结果将提供有关物理化学和结构特征的新信息，这些特征使PPI站点难以吸毒，我们将用来进一步完善我们的计算方法。 公共卫生相关性：映射方法将分子探针（小分子或官能团）放在蛋白质的表面上，以识别最有利的结合位置，并提供有关该位点可药物的信息。我们专注于鉴定和表征能够结合蛋白质 - 蛋白质相互作用的小分子抑制剂的可药位点，这是药物研究中的一个重要新兴问题。