Density functional theory-guided drug loading strategy for sensitized tumor-homing thermotherapy
Density functional theory-guided drug loading strategy for sensitized tumor-homing thermotherapy
复制标题
密度泛函理论指导的致敏肿瘤归巢热疗载药策略
DOI:
10.1016/j.cej.2021.130146
复制
发表时间:
2021
影响因子:
15.1
通讯作者:
Xue Wei
中科院分区:
文献类型:
--
作者:
Huo Cong-Min;Chen Liheng;Wang Hai-Yang;Luo Si-Man;Wang Xiang;Shi Yun-Feng;Zhu Jing-Yi;Xue Wei
Strong interactions between loading drugs and nanocarriers contribute greatly to the high loading capacity while bringing about the problems on effective drug release. To solve this dilemma, we develop a density functional theory (DFT)-guided drug loading strategy to construct a dismountable nanoplatform for sensitized tumor-homing thermotherapy. DFT, a kind of computational method, is used to screen out a heat shock protein90 (HSP90) inhibitor, geldanamycin (GDM), that highly matched the structure of nanocarriers, thus providing a high drug loading efficiency (~ 42%). Of special note, GDM could be effectively released inside tumor cells because the isoelectric points of cancer cell membrane (CCM) and polydopamine (PDA) are both around pH 4.0 ~ 5.0, which could exactly match with the acidic environment of endo/lysosome. The CCM envelope enables self-targeting of PDA/GDM@CCM to the source cancer cells and homologous tumors while effectively inhibiting recognition and clearance by macrophages. Efficient photothermal ablation is attributed to the efficient suppression of tumor heat resistance by GDM and precise selection of the best matched tumor type by using The Cancer Genome Atlas (TCGA). This DFT-guided drug loading strategy points out a new avenue for optimization of drug-loading into nanocarriers, and ultimately contributes to the high drug availability and excellent curative effect.
登录
查看更多内容
影响因子:
16.6
作者:
Bogojeski M;Vogt-Maranto L;Tuckerman ME;Müller KR;Burke K
通讯作者:
Burke K
影响因子:
26.6
作者:
Adekoya D;Qian S;Gu X;Wen W;Li D;Ma J;Zhang S
通讯作者:
Zhang S
影响因子:
5.2
作者:
Diaz-Diaz, Andrea;Roca-Lema, Daniel;Figueroa, Angelica
通讯作者:
Figueroa, Angelica
影响因子:
21.8
作者:
Falivene, Laura;Cao, Zhen;Cavallo, Luigi
通讯作者:
Cavallo, Luigi
影响因子:
15.1
作者:
Hu, Qi;Bu, Yusi;Wang, Sicen
通讯作者:
Wang, Sicen