School of Computer Science, University of Waterloo, and Simulated Biomolecular Systems, 650 Winterberry Av., Waterloo, Ontario N2V2X4, Canada.
IEEE/ACM Trans Comput Biol Bioinform. 2011 Jul-Aug;8(4):1120-33. doi: 10.1109/TCBB.2010.70.
Predicting the binding mode(s) of a drug molecule to a target receptor is pivotal in structure-based rational drug design. In contrast to most approaches to solve this problem, the idea in this paper is to analyze the search problem from a computational perspective. By building on top of an existing docking tool, new methods are proposed and relevant computational results are proven. These methods and results are applicable for other place-and-join frameworks as well. A fast approximation scheme for the docking of rigid fragments is described that guarantees certain geometric approximation factors. It is also demonstrated that this can be translated into an energy approximation for simple scoring functions. A polynomial time algorithm is developed for the matching phase of the docked rigid fragments. It is demonstrated that the generic matching problem is NP-hard. At the same time, the optimality of the proposed algorithm is proven under certain scoring function conditions. The matching results are also applicable for some of the fragment-based de novo design methods. On the practical side, the proposed method is tested on 829 complexes from the PDB. The results show that the closest predicted pose to the native structure has the average RMS deviation of 1.06 A.
预测药物分子与靶标受体的结合模式对于基于结构的合理药物设计至关重要。与解决此问题的大多数方法不同,本文的思路是从计算的角度分析搜索问题。通过在现有对接工具的基础上,提出了新的方法并证明了相关的计算结果。这些方法和结果也适用于其他位置和连接框架。描述了一种用于刚性片段对接的快速逼近方案,该方案保证了某些几何逼近因子。还证明了这可以转化为简单评分函数的能量逼近。为对接的刚性片段开发了一种多项式时间算法。证明了通用匹配问题在某些评分函数条件下是 NP 难的。同时,证明了所提出算法的最优性。匹配结果也适用于某些基于片段的从头设计方法。在实际方面,该方法在 PDB 中的 829 个复合物上进行了测试。结果表明,与天然结构最接近的预测构象的平均 RMS 偏差为 1.06Å。