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作者机构:Xi An Jiao Tong Univ Sch Math & Stat Xian 710049 Shaanxi Peoples R China IIT Dept Appl Math Chicago IL 60616 USA Huazhong Univ Sci & Technol Ctr Math Sci Wuhan 430074 Hubei Peoples R China Huazhong Univ Sci & Technol Sch Math & Stat Wuhan 430074 Hubei Peoples R China
出 版 物:《JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT》 (统计力学杂志:理论和实验)
年 卷 期:2019年第2019卷第3期
页 面:033501-033501页
核心收录:
学科分类:07[理学] 070201[理学-理论物理] 0702[理学-物理学] 0801[工学-力学(可授工学、理学学位)]
基 金:NSF NSFC [11372233, 11531006, 11771449, 11772241] program of China Scholarship Council
主 题:numerical simulations stochastic particle dynamics stochastic search
摘 要:We study the target search on DNA for proteins in the presence of non-constant drift. This search is realized by the facilitated diffusion process. Existing works on this problem focus on the case of constant drift. Starting from a non-local Fokker-Planck equation with the alpha-order fractional Laplace operator and a sink term, we obtain the possibility density function for a protein occurring at position x at time t. Based on this, we further compute the survival probability and the first arrival density in order to quantify the searching mechanisms. The numerical results show that in the linear drift case, there is an optimal a index for the search to be most likely successful (searching reliability reaches its maximum). This optimal alpha index depends on the initial position-target separation. It is also found that the diffusion intensity plays a positive role in improving the search success. The nonlinear double-well drift could drive the protein to reach the target with a larger possibility than the linear drag at the initial time period, but viewed over a long time duration, the linear drift is more beneficial for target search success. In contrast to the linear drift case, the search reliability and efficiency with nonlinear double-well drift have a monotonic relationship with the alpha index, that is, the smaller the alpha index is, the higher the likelihood of a protein finding its target.