Cancer drug therapy and stochastic modeling of “nano-motors”
作者: Lubna SherinShabieh FarwaAyesha SohailZhiwu LiOA Beg
作者单位: 1COMSATS University Islamabad, Lahore Campus
2COMSATS University Islamabad
3Comsats Institute of Information Technology
4Macau University of Science and Technology
5University of Salford, Manchester, UK
刊名: International Journal of Nanomedicine, 2018, Vol.2018 (default), pp.6429-6440
来源数据库: Dove Journal
DOI: 10.2147/IJN.S168780
原始语种摘要: Controlled inhibition of kinesin motor proteins is highly desired in the field of oncology. Among other interventions, there exists “targeted chemotherapeutic regime/options” of selective Eg5 competitive and allosteric inhibitors, inducing cancer cell apoptosis and tumor regression with improved safety profiles. Though promising, such studies are still under clinical trials, for the discovery of efficient and least harmful Eg5 inhibitors. The aim of present research is to bridge the computational modelling approach with drug design and therapy of cancer cells. Thus a computational model, interfaced with the clinical data of “Eg5 dynamics” and “inhibitors” via special functions is presented in this article. Comparisons are made for the drug efficacy and the threshold values are predicted...
全文获取路径: Dove 
影响因子:3.463 (2012)

  • modeling 制祝型
  • computational 计算的
  • efficient 有用的
  • threshold 阈值
  • bridge 电桥
  • discovery 发现
  • regime 状况
  • improved 改进
  • least 最少的
  • harmful 有害的