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）：本提案是“用于配体结合的蛋白质计算图谱”资助的竞争性修订（通知NOT-OD-09-58，NIH宣布恢复法案资金可用于竞争性修订申请）。定位方法将分子探针-小分子或功能基团-置于蛋白质表面，以确定最有利的结合位置。由于蛋白质表面的区域是药物-蛋白质相互作用中的结合自由能的主要贡献者，也结合各种小的有机分子，因此映射可以识别这样的“热点”，并且结合的探针分子的数量是可药用性的良好预测因子。母公司的建议集中在“传统”的药物靶点，自然结合小分子配体。这一修订的总体目标是将分析扩展到蛋白质-蛋白质界面中可药用位点的鉴定和表征。这种分析有助于发现可以抑制或调节两种蛋白质结合的小分子，这是药物研究中的一个重要问题。应用映射到一些蛋白质-蛋白质相互作用（PPI）的目标已经表明，该方法总是确定至少一些分数的网站，可以结合小分子抑制剂的蛋白质-蛋白质界面区域内，即使从一个配体的蛋白质的结构开始。在目标1中，我们将进一步研究这一观察的一般性，通过映射各种PPI的结构和生化信息的目标。我们还将研究片段之间的相互作用和它们的蛋白质环境中的结合位点，通过使用靶特异性探针库的基础上，每个目标的已知配体。由于小分子的结合经常需要构象变化以在相对平坦的蛋白质-蛋白质界面中形成适当的口袋，因此在目标2中，我们开发了一种方法来在映射之前考虑侧链的灵活性。该算法结合了统计分析和能量最小化，以确定“可移动”的侧链和它们的潜在构象状态的“热点”附近的初始映射。蛋白质结构是通过结合可移动侧链的潜在构象而产生的。这种调整后的结构的重新映射通常与配体结合蛋白质获得的结果一致，因此大大提高了该方法的预测能力。目的3是热点的理论和实验表征，所述热点使得小分子抑制剂能够在IL-2与IL-2 R1（示例性PPI靶标）的结合界面中结合。已知抑制剂的不同部分从它们与蛋白质的相互作用中获得的结合能尚未被系统地阐明。我们将使用定量生物化学和生物物理分析以及X射线晶体学测量来自这些已知IL-2抑制剂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作为探针计算获得的结果进行比较。这些结果将提供有关使PPI位点难以药物化的物理化学和结构特征的新信息，我们将使用这些信息来进一步完善我们的计算方法。 公共卫生相关性：作图方法将分子探针-小分子或官能团-放置在蛋白质表面上，以鉴定最有利的结合位置，并提供关于该位点的可药用性的信息。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用位点，这是药学研究中的一个重要新兴问题。