Communications and Remote Sensing Laboratory, Université catholique de Louvain, Place du Levant, 2 (TELE), 1348 Louvain-la-neuve, Belgium.
IEEE/ACM Trans Comput Biol Bioinform. 2011 Jan-Mar;8(1):59-68. doi: 10.1109/TCBB.2009.53.
Travel Depth, introduced by Coleman and Sharp in 2006, is a physical interpretation of molecular depth, a term frequently used to describe the shape of a molecular active site or binding site. Travel Depth can be seen as the physical distance a solvent molecule would have to travel from a point of the surface, i.e., the Solvent-Excluded Surface (SES), to its convex hull. Existing algorithms providing an estimation of the Travel Depth are based on a regular sampling of the molecule volume and the use of the Dijkstra's shortest path algorithm. Since Travel Depth is only defined on the molecular surface, this volume-based approach is characterized by a large computational complexity due to the processing of unnecessary samples lying inside or outside the molecule. In this paper, we propose a surface-based approach that restricts the processing to data defined on the SES. This algorithm significantly reduces the complexity of Travel Depth estimation and makes possible the analysis of large macromolecule surface shape description with high resolution. Experimental results show that compared to existing methods, the proposed algorithm achieves accurate estimations with considerably reduced processing times.
旅行深度（Travel Depth）由 Coleman 和 Sharp 于 2006 年提出，是分子深度的一种物理解释，分子深度是一个常用于描述分子活性位点或结合位点形状的术语。旅行深度可以被视为溶剂分子从表面（即溶剂排除表面，SES）上的一个点到其凸包所需的物理距离。现有的提供旅行深度估计的算法基于对分子体积的规则采样和使用 Dijkstra 最短路径算法。由于旅行深度仅在分子表面上定义，因此这种基于体积的方法由于处理位于分子内部或外部的不必要样本而具有较大的计算复杂性。在本文中，我们提出了一种基于表面的方法，该方法将处理限制在 SES 上定义的数据。该算法显著降低了旅行深度估计的复杂性，并使得对具有高分辨率的大型大分子表面形状描述进行分析成为可能。实验结果表明，与现有方法相比，所提出的算法具有相当小的处理时间，并且可以实现准确的估计。
