College of Information Engineering, China Jiliang University, 258 Xueyuan Street, Hangzhou 310018, China.
The Advanced Research Institute of Intelligent Sensing Network, Tongji University, 4800 Caoan Road, Shanghai 201804, China.
J Healthc Eng. 2017;2017:4818604. doi: 10.1155/2017/4818604. Epub 2017 Apr 20.
Molecular skin surface (MSS), proposed by Edelsbrunner, is a continuous smooth surface modeling approach of biological macromolecules. Compared to the traditional methods of molecular surface representations (e.g., the solvent exclusive surface), MSS has distinctive advantages including having no self-intersection and being decomposable and transformable. For further promoting MSS to the field of bioinformatics, transformation between different MSS representations mimicking the macromolecular dynamics is demanded. The transformation process helps biologists understand the macromolecular dynamics processes visually in the atomic level, which is important in studying the protein structures and binding sites for optimizing drug design. However, modeling the transformation between different MSSs suffers from high computational cost while the traditional approaches reconstruct every intermediate MSS from respective intermediate union of balls. In this study, we propose a novel computational framework named general MSS transformation framework (GMSSTF) between two MSSs without the assistance of union of balls. To evaluate the effectiveness of GMSSTF, we applied it on a popular public database PDB (Protein Data Bank) and compared the existing MSS algorithms with and without GMSSTF. The simulation results show that the proposed GMSSTF effectively improves the computational efficiency and is potentially useful for macromolecular dynamic simulations.
Edelsbrunner 提出的分子表面（MSS）是一种连续光滑的生物大分子建模方法。与传统的分子表面表示方法（例如溶剂排除表面）相比，MSS 具有独特的优势，包括没有自交点、可分解和可变形。为了进一步将 MSS 推广到生物信息学领域，需要模拟大分子动力学的不同 MSS 表示之间的转换。转换过程有助于生物学家在原子水平上直观地理解大分子动力学过程，这对于研究蛋白质结构和结合位点以优化药物设计非常重要。然而，不同 MSS 之间的建模转换存在计算成本高的问题，而传统方法则从各自的球集合并中重新构建每个中间 MSS。在这项研究中，我们提出了一种新的计算框架，称为一般 MSS 转换框架（GMSSTF），无需球集合并即可在两个 MSS 之间进行转换。为了评估 GMSSTF 的有效性，我们将其应用于流行的公共数据库 PDB（蛋白质数据库），并将具有和不具有 GMSSTF 的现有 MSS 算法进行了比较。模拟结果表明，所提出的 GMSSTF 有效地提高了计算效率，对于大分子动力学模拟具有潜在的用途。
