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集成的人工智能和机器学习管道确定了针对癌症治疗的新型WEE1激酶抑制剂

Jaikanth Chandrasekaran¹, Dhanushya Gopal², Lokesh Vishwa Sureshkumar²

¹Department of Pharmacology, Sri Ramachandra Faculty of Pharmacy, Sri Ramachandra Institute of Higher Education and Research (Deemed to be University), Chennai, Tamil Nadu, 600116, India. jaikanthjai@gmail.com.

Molecular diversity

|March 19, 2025

概括

人工智能确定了MORLD5036作为一种新的WEE1激酶抑制剂候选者. 这种人工智能驱动的方法通过探索WEE1介导的细胞循环控制的新化学空间,迅速发现潜在的癌症治疗方法.

科学领域:

在瘤学瘤学.
药用化学医学化学
计算生物学计算生物学

背景情况:

WEE1激酶是G2/M细胞周期检查点的关键调节者.
由于WEE1激酶的失调与各种癌症有关,因此具有治疗点.
准WEE1为新型癌症治疗提供了潜力.

研究的目的:

使用人工智能 (AI) 识别新的WEE1激酶抑制剂.
探索未知的化学空间,以发现WEE1抑制剂.
为了计算验证潜在治疗用途的化合物.

主要方法:

利用MORLD AI平台生成和优化2万种不同的化合物.
采用化学信息管道来过和选择242名有前途的候选人.
应用的维度缩小 (UMAP),集群 (K-means),分子对接和分子动力学模拟.

主要成果:

确定了MORLD5036和MORLD6305作为具有高结合亲和力的强效WEE1抑制剂.
通过分子动力学和MM-GBSA分析,MORLD5036表现出卓越的稳定性和功效.
发现了不同于现有的WEE1抑制剂的新型化学型,具有有利的ADME概况.

结论:

MORLD5036是一种计算验证的,具有新特性的有前途的WEE1抑制剂候选者.
由人工智能驱动的MORLD平台有效地加速了下一代激酶抑制剂的发现.
这种方法通过确定WEE1依赖性癌症的潜在治疗方法,促进了精密瘤学的进步.

关键词:

人工智能驱动的药物发现癌症治疗治疗癌症治疗世界上的世界.分子对接是分子对接.分子动力学分子动力学药理动力学药理动力学架构分析架构分析在WEE1激酶中,

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