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Cancer drug therapy and stochastic modeling of "nano-motors".

Background: 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.

Research question: Though promising, such studies are still under clinical trials, for the discovery of efficient and least harmful Eg5 inhibitors. The aim of this research was to bridge the computational modeling approach with drug design and therapy of cancer cells.

Methods: 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 through numerical simulations.

Results: Results are obtained to depict the dynamics induced by ispinesib, when used as an inhibitor of kinesin Eg5, on cancer cell lines.

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