Identifying inhibitors of protein interactions using pocket optimization

使用口袋优化识别蛋白质相互作用的抑制剂

• 批准号: 8826142
• 负责人: John Karanicolas
• 金额: $ 27.71万
• 依托单位: UNIVERSITY OF KANSAS LAWRENCE
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-04-01 至 2016-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8826142
• 关键词: Address; Adopted; Allosteric Site; Binding; Binding Sites; Biochemical; Biological; Categories; Cell Proliferation; Chemicals; Complement; Complex; Computer Simulation; Computing Methodologies; Disease; Effectiveness; Health; Homologous Gene; In Vitro; Learning; Libraries; Ligands; Malignant Neoplasms; Membrane Proteins; Methodology; Methods; Molecular Conformation; Mutation; Physiological; Plant Roots; Proteins; Proteus; Proxy; Research; Sampling; Screening Result; Shapes; Site; Structure; Surface; Testing; Work; base; conformational conversion; cost; driving force; falls; high throughput screening; inhibitor/antagonist; innovation; insight; interest; meetings; novel; protein protein interaction; protein structure; screening; small molecule; small molecule libraries; stem; survivin; tool

DESCRIPTION (provided by applicant): Identifying small-molecule inhibitors of protein interactions has traditionally presented a challenge for modern screening methods, despite interest stemming from the fact that such interactions comprise the underlying mechanisms for cell proliferation, differentiation, and survival. The objective of this application is to employ insights from computational methodology we have recently developed to address the distinct challenges associated with finding inhibitors of different classes of protein surface. Our central hypothesis is that exploring protein fluctuations leading to formation of surface pockets is criticl for understanding the regions of chemical space in which suitable inhibitory compounds may be found. We propose to meet our objective by pursuit of the following three specific aims: 1) Apply pocket optimization for selecting and characterizing protein targets. 2) Employ protein-ligand complementarity to build libraries enriched in protein interface inhibitors. 3) Extend these tools to allosteric inhibitors of protein interfaces. The proposed research is innovative in its ue of insight from protein fluctuations to identify binding pockets. By first confirming the ability o a target protein to form a suitable pocket and second assembling a complementary library, we collectively address the two main hurdles outlined above that have hitherto hindered identification of small molecules that directly inhibit protein-protein interactions. By combining this approach with in vitro biochemical screening, we expect to identify novel inhibitors of protei interactions involving each of three well-validated cancer targets: Bcl-xL, survivin, and b- TrCP.

描述（由申请人提供）：识别蛋白质相互作用的小分子抑制剂传统上对现代筛选方法提出了挑战，尽管这种相互作用包含细胞增殖、分化和存活的潜在机制这一事实引起了人们的兴趣。本应用程序的目的是利用我们最近开发的计算方法的见解来解决与寻找不同种类蛋白质表面抑制剂相关的独特挑战。我们的中心假设是，探索导致表面口袋形成的蛋白质波动对于理解可能发现合适抑制化合物的化学空间区域至关重要。为了实现这一目标，我们提出了以下三个具体目标：1)将口袋优化应用于蛋白质靶点的选择和表征。2)利用蛋白质-配体互补构建富含蛋白质界面抑制剂的文库。3)扩展这些