Polar sampling and optimization of protein-ligand cocrystal structures

 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。目前的方法和实践通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一个重大障碍。我们将通过开发一种自动化方法来解决这个问题，该方法结合实验电子密度信息使用极性采样和优化来校正蛋白质-配体共晶结构。这种方法将利用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。该软件具有很大的商业潜力，因为正确拟合结合配体的问题已经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 对基于结构的药物设计的广泛影响。

 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.