Hu Langhua, Chen Duan, Wei Guo-Wei
Department of Mathematics Michigan State University, MI 48824, USA.
Mathematical Biosciences Institute The Ohio State University, Columbus, OH, 43210, USA.
Mol Based Math Biol. 2013 Jan 1;1. doi: 10.2478/mlbmb-2012-0001,.
Fractional derivative or fractional calculus plays a significant role in theoretical modeling of scientific and engineering problems. However, only relatively low order fractional derivatives are used at present. In general, it is not obvious what role a high fractional derivative can play and how to make use of arbitrarily high-order fractional derivatives. This work introduces arbitrarily high-order fractional partial differential equations (PDEs) to describe fractional hyperdiffusions. The fractional PDEs are constructed via fractional variational principle. A fast fractional Fourier transform (FFFT) is proposed to numerically integrate the high-order fractional PDEs so as to avoid stringent stability constraints in solving high-order evolution PDEs. The proposed high-order fractional PDEs are applied to the surface generation of proteins. We first validate the proposed method with a variety of test examples in two and three-dimensional settings. The impact of high-order fractional derivatives to surface analysis is examined. We also construct fractional PDE transform based on arbitrarily high-order fractional PDEs. We demonstrate that the use of arbitrarily high-order derivatives gives rise to time-frequency localization, the control of the spectral distribution, and the regulation of the spatial resolution in the fractional PDE transform. Consequently, the fractional PDE transform enables the mode decomposition of images, signals, and surfaces. The effect of the propagation time on the quality of resulting molecular surfaces is also studied. Computational efficiency of the present surface generation method is compared with the MSMS approach in Cartesian representation. We further validate the present method by examining some benchmark indicators of macromolecular surfaces, i.e., surface area, surface enclosed volume, surface electrostatic potential and solvation free energy. Extensive numerical experiments and comparison with an established surface model indicate that the proposed high-order fractional PDEs are robust, stable and efficient for biomolecular surface generation.
分数阶导数或分数阶微积分在科学和工程问题的理论建模中发挥着重要作用。然而,目前仅使用了相对低阶的分数阶导数。一般来说,高阶分数阶导数能发挥什么作用以及如何利用任意高阶分数阶导数并不明显。这项工作引入了任意高阶分数阶偏微分方程(PDEs)来描述分数阶超扩散。这些分数阶偏微分方程是通过分数阶变分原理构建的。提出了一种快速分数阶傅里叶变换(FFFT)来对高阶分数阶偏微分方程进行数值积分,以避免在求解高阶演化偏微分方程时受到严格的稳定性约束。所提出的高阶分数阶偏微分方程被应用于蛋白质表面生成。我们首先在二维和三维设置下用各种测试示例验证了所提出的方法。研究了高阶分数阶导数对表面分析的影响。我们还基于任意高阶分数阶偏微分方程构建了分数阶偏微分方程变换。我们证明,在分数阶偏微分方程变换中使用任意高阶导数会导致时频定位、频谱分布控制和空间分辨率调节。因此,分数阶偏微分方程变换能够对图像、信号和表面进行模式分解。还研究了传播时间对所得分子表面质量的影响。将当前表面生成方法的计算效率与笛卡尔表示中的MSMS方法进行了比较。我们通过检查大分子表面的一些基准指标,即表面积、表面封闭体积、表面静电势和溶剂化自由能,进一步验证了本方法。广泛的数值实验以及与已建立的表面模型的比较表明,所提出的高阶分数阶偏微分方程对于生物分子表面生成是稳健、稳定且高效的。