通过深度学习识别的TIPE3蛋白的小分子抑制剂抑制了体外癌细胞的生长
Xiaodie Chen1,2, Zhen Lu1, Jin Xiao3
1Center for Cancer Immunology, Institute of Biomedicine and Biotechnology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.
Cells
|May 10, 2024
概括
研究人员确定了针对瘤坏死因子-α诱导蛋白8-Like 3 (TIPE3) 的新型小分子抑制剂,这是促进癌症生长的蛋白质. 三种化合物在体外显示出显著的抗瘤作用,两种化合物对癌细胞具有选择性毒性,为新的癌症疗法提供了有前途的途径.
科学领域:
- 在瘤学瘤学.
- 计算化学计算化学
- 药物发现 药物发现 药物发现
背景情况:
- 瘤缩因子α诱导的8-样蛋白3 (TIPE3) 在各种人类癌症中被上调,促进瘤的增殖,迁移,入侵,并抑制亡.
- 准TIPE3是一种潜在的抗癌策略.
- 人工智能 (AI) 正在加速抗癌药物开发.
研究的目的:
- 使用计算方法的组合,识别TIPE3的新型抑制剂.
- 评估已识别的化合物的体外抗瘤活性.
- 研究潜在候选药物的选择性和分子相互作用.
主要方法:
- 使用深度学习 (DFCNN,DeepBindBC),分子对接 (Autodock Vina) 和分子动力学 (MD,元动力学) 来进行虚拟选.
- 对TIPE3.3进行选,对ZINC化合物数据集进行了选.
- 选择了六个候选人进行实验验证,重点关注三个有前途的化合物.
主要成果:
- 三种小分子化合物 (K784-8160,E745-0011,7238-1516) 在体外表现出显著的抗瘤活性,降低活力,增殖和迁移,同时增强亡.
- 化合物E745-0011和7238-1516表现出对TIPE3高表达瘤细胞的选择性细胞毒性,节省了正常细胞.
- 分子对接证实了抑制剂和TIPE3之间的相互作用,揭示了关键的疏水性相互作用和残留物.
结论:
- 人工智能驱动的药物发现,集成深度学习和MD模拟,是有效的识别TIPE3抑制剂.
- 这些已识别的化合物显示出开发针对TIPE3.3的新抗癌疗法的巨大潜力.
- 对这些选择性抑制剂的进一步研究可能会导致新的癌症治疗方法.
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