虚拟筛选
对接(动物)
计算生物学
药物发现
癌症研究
白血病
计算机科学
生物信息学
生物
医学
免疫学
护理部
作者
Hao Guo,Zhe-yuan Shen,Yongyi Yuan,Rou-fen Chen,Jingyi Yang,X. Liu,Qing Zhang,Qian-ying Pan,Jianjun Ding,Xinjun He,Qingnan Zhang,Xiaowu Dong,Keshu Zhou
标识
DOI:10.1021/acs.jcim.4c00151
摘要
The lymphocyte-specific protein tyrosine kinase (LCK) plays a crucial role in both T-cell development and activation. Dysregulation of LCK signaling has been demonstrated to drive the oncogenesis of T-cell acute lymphoblastic leukemia (T-ALL), thus providing a therapeutic target for leukemia treatment. In this study, we introduced a sophisticated virtual screening strategy combined with biological evaluations to discover potent LCK inhibitors. Our initial approach involved utilizing the PLANET algorithm to assess and contrast various scoring methodologies suitable for LCK inhibitor screening. After effectively evaluating PLANET, we progressed to devise a virtual screening workflow that synergistically combines the strengths of PLANET with the capabilities of Schrödinger's suite. This integrative strategy led to the efficient identification of four potential LCK inhibitors. Among them, compound 1232030-35-1 stood out as the most promising candidate with an IC
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