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通过机器学习驱动的治疗性植物化学品的识别,针对肝细胞癌

V Vanitha Jain¹, Madhu Anabala¹, Deepak Sharma¹

¹School of Bio-Sciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu 632014, India.

Computational biology and chemistry

|August 5, 2025

概括

肝细胞癌 (HCC) 研究确定了像corlumine这样的有希望的植物化学物质作为潜在的药物候选者. 这些化合物在抑制肝癌生长方面表现出有效性,提供了新的治疗途径.

科学领域:

* 药理学药理学药理学
* 计算化学计算机化学
* 瘤学瘤学是一门专业.

背景情况:

*肝细胞癌 (HCC) 是全球癌症死亡的主要原因.
*现有的HCC治疗有局限性,需要新的治疗策略.
* 植物化学物质具有作为抗氧化剂,抗炎剂和抗瘤剂的潜力.

研究的目的:

* 确定具有针对HCC的潜在抗癌活性的新型植物化学物质.
* 开发强大的机器学习模型来预测HCC抑制剂的疗效.
* 评估有前途的植物化学品与HCC标的分子相互作用.

主要方法:

* 利用Huh 7细胞系进行体外HCC建模.
*使用ChemBL数据库检索已知抑制剂的IC50值.
*使用额外树木分类器和光梯度增强机器 (LGBM) 开发了定量结构-活动关系 (QSAR) 模型.
* 进行了ADMET分析和分子对接研究,用于植物化学查.
* 进行了分子动态模拟,以评估复杂的稳定性.

主要成果:

* 额外树木分类器和LGBM分别获得了0.91和0.90的高接收器操作特征 (ROC) 得分.
*植物化学物质比洛博尔,科鲁明和橄酸显示出最佳的查和ADMET概况.
*Corlumine对HSP90AA1和CTNNB1目标表现出强烈的结合亲和力,表现优于参考化合物.
*分子动力学模拟表明CTNNB1-corlumine复合物的稳定性优于HSP90AA1-corlumine.

结论:

*Corlumine显示出作为一种用于抑制HCC的新型药物分子的显著潜力.
*开发的基于ML的QSAR模型为未来的药物发现提供了强大的框架.
* 需要进一步的体外和体内研究来验证corlumine对HCC的治疗疗效.

关键词:

滥用酒精滥用酒精滥用酒精滥用酒精滥用酒精抗氧化剂是一种抗氧化剂.机器学习机器学习分子对接是分子对接.分子动态模拟分子动态模拟植物化学物质植物化学物质

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