虚拟筛选
原癌基因酪氨酸蛋白激酶Src
癌症研究
药物发现
小分子
化学
计算生物学
对接(动物)
三阴性乳腺癌
达沙替尼
激酶
生物
癌症
生物化学
信号转导
乳腺癌
医学
遗传学
护理部
酪氨酸激酶
作者
Roufen Chen,Yuchen Wang,Zheyuan Shen,Chenyi Ye,Yu Guo,Lu Yan,Jianjun Ding,Xiaowu Dong,Donghang Xu,Xiaoli Zheng
标识
DOI:10.1002/ardp.202400066
摘要
Abstract Oncogenic overexpression or activation of C‐terminal Src kinase (CSK) has been shown to play an important role in triple‐negative breast cancer (TNBC) progression, including tumor initiation, growth, metastasis, drug resistance. This revelation has pivoted the focus toward CSK as a potential target for novel treatments. However, until now, there are few inhibitors designed to target the CSK protein. Responding to this, our research has implemented a comprehensive virtual screening protocol. By integrating energy‐based screening methods with AI‐driven scoring functions, such as Attentive FP, and employing rigorous rescoring methods like Glide docking and molecular mechanics generalized Born surface area (MM/GBSA), we have systematically sought out inhibitors of CSK. This approach led to the discovery of a compound with a potent CSK inhibitory activity, reflected by an IC 50 value of 1.6 nM under a homogeneous time‐resolved fluorescence (HTRF) bioassay. Subsequently, molecule 2 exhibits strong growth inhibition of MD anderson ‐ metastatic breast (MDA‐MB) ‐231, Hs578T, and SUM159 cells, showing a level of growth inhibition comparable to that observed with dasatinib. Treatment with molecule 2 also induced significant G1 phase accumulation and cell apoptosis. Furthermore, we have explored the explicit binding interactions of the compound with CSK using molecular dynamics simulations, providing valuable insights into its mechanism of action.
科研通智能强力驱动
Strongly Powered by AbleSci AI