A numerical algorithm for investigating the role of the motor-cargo linkage in molecular motor-driven transport

We extend the numerical algorithm developed by Wang et al. (2003. J. Theor. Biol. 221, 491-511) for studying biomolecular transport processes to include the linkage that connects molecular motors to their cargo. The new algorithm is used to investigate how the stiffness of the linkage affects the average velocity, effective diffusion coefficient, and randomness parameter. Three different models for molecular motors are considered: (1) a discrete stepping motor (2) a motor moving in a tilted-periodic potential and (3) a motor driven by a flashing potential. We demonstrate that a flexible motor-cargo linkage can make inferences on motor behavior based on measurements of the cargo's position difficult. We also show that even for the case of a tilted-periodic potential there exists an optimal stiffness of the linkage at which transport is maximized. The MATLAB code used in this paper is available at: http://www.unc.edu/approximatelytelston/code/.     

新型粒子群优化算法在多序列联配中的应用

将粒子群优化算法应用于序列联配,提出了一种改进的粒子群优化算法,该算法在粒子群的进化过程中根据粒子的适应值动态地调整粒子群的惯性权重与粒子群飞行速度范围,提高了算法的收敛速度和收敛精度;针对PSO算法可能出现的早熟现象,引入重新初始化机制,增强了算法的搜索能力,实验表明该算法是有效的。