Polar sampling and optimization of protein-ligand cocrystal structures

蛋白质-配体共晶结构的极性采样和优化

• 批准号: 9139557
• 负责人: CHANDRAJIT L BAJAJ
• 金额: $ 22.49万
• 依托单位: GFREE BIO, LLC
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-06-06 至 2018-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9139557
• 关键词: Accounting; Algorithms; Amides; Attention; Binding; Binding Proteins; Biological; Chemicals; Complement; Complex; Computer software; Crystallography; Data; Development; Disease; Drug Design; Electrostatics; Ensure; Environment; Geometry; Imagery; Industry; Iridium; Lead; Ligand Binding; Ligands; Light; Literature; Maps; Marketing; Methodology; Methods; Modeling; Molecular; Molecular Conformation; Phase; Problem Solving; Productivity; Proteins; Protocols documentation; Resolution; Sampling; Scientist; Services; Structure; System; Techniques; Testing; Texas; Uncertainty; Universities; Visual; Work; austin; base; commercialization; density; design; drug candidate; drug discovery; electron density; improved; novel; novel therapeutics; professor; programs; prospective; protein structure; prototype; public health relevance; sound; tool

 DESCRIPTION (provided by applicant): Gfree Bio proposes to collaborate with Professor Bajaj and his group at the University of Texas to develop a general and much more theoretically rigorous algorithm for fitting the ligand binding region of experimental protein-ligand cocrystal structures. Current methods and practices often lead to very poor geometries for the bound ligand. This is a significant impediment to the most effective use of crystallography in drug discovery. We will solve this problem by developing an automated method for using polar sampling and optimization in conjunction with the experimental electron density information to correct protein-ligand cocrystal structures. This methodology will capitalize on recent advances in the Bajaj lab with respect to fast multidimensional optimization, linear scaling electrostatics and solvation methods, and advanced data structures for representing molecular systems. This software has great commercial potential since the problem of properly fitting bound ligands has been receiving increasing attention in the literature, and industry. As such our solution will have broad impact on structure-based drug design.

 描述（由申请人提供）：Gfree Bio 提议与德克萨斯大学的 Bajaj 教授及其团队合作开发一种通用且理论上更加严格的算法，用于拟合实验蛋白质-配体共晶结构的配体结合区域。实践常常导致结合配体的几何形状非常差，这是在药物发现中最有效地使用晶体学的重大障碍，我们将通过开发一种在药物发现中使用极性采样和优化的自动化方法来解决这个问题。结合实验电子密度信息来校正蛋白质-配体共晶结构，该方法将利用 Bajaj 实验室在快速多维优化、线性缩放静电和溶剂化方法以及用于表示分子系统的先进数据结构方面的最新进展。具有巨大的商业潜力，因为正确拟合结合配体的问题在文献和工业中受到越来越多的关注，因此我们的解决方案将具有巨大的商业潜力。 对基于结构的药物设计产生广泛影响。