five

Computational study of diol camptothecin drug delivery process using MPEG-1-based nanosome structure: molecular dynamics approach

收藏
DataCite Commons2026-02-23 更新2025-09-08 收录
下载链接:
https://tandf.figshare.com/articles/dataset/Computational_study_of_diol_camptothecin_drug_delivery_process_using_MPEG-1-based_nanosome_structure_molecular_dynamics_approach/28943658/1
下载链接
链接失效反馈
官方服务:
资源简介:
In recent years, the drug delivery process has become important for effective treatments of various diseases. However, drug carrier design is a complex procedure and many of designed structures do not perform well. Nanostructures are promising systems for effective drug delivery process. Between nanostructures, nanosomes are effective vesicles of spherical shape that can be created from different self-assembled nanosize components. It is expected the appropriate design of nanosome-based samples, introduced a suitable drug carrier for clinical applications. In current research, we introduced macrophage-expressed gene (MPEG-1) protein-based nanosome performance in diol camptothecin (CPT(OH)<sub>2</sub>) drug delivery process in aqueous environment for the first time. The molecular dynamics (MD) method implemented for this purpose by using dreiding force field. Our MD simulations were performed two main phases. In the first phase, defined samples equilibrated at initial condition (<i>T</i><sub>0</sub> = 300 K and <i>P</i><sub>0</sub> = 1 bar). Then, drug delivery performance of equilibrated samples was reported. Computational outputs predicted atomic stability of samples in standard condition. This performance is conducted from kinetic and potential energies convergence in equilibrium phase. Also, drug delivery process was detected after 0.12 ns in aqueous environment. Numerically, drug delivery ratio reached to 66%. Furthermore, zeta potential converged to −2.20 mV after 100 ns. From these outputs, we concluded MPEG-1-based nanosome can be used in actual cases for drug delivery in clinical applications.
提供机构:
Taylor & Francis
创建时间:
2025-05-07
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作