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战略和效率 - - 重新定义了新型纳米分子铁酶抑制剂的发现:AI de novo分子生成 + 专家指导的结构优化

Yinyan Sun¹, Jiahui Wang¹, Wenchao Chen¹

¹School of Pharmacy, Hangzhou Normal University, Hangzhou 311121, PR China; Key Laboratory of Elemene Class Anti-Cancer Chinese Medicines, Collaborative Innovation Center of Traditional Chinese Medicines of Zhejiang Province, Hangzhou Normal University, Hangzhou 311121, PR China.

Journal of advanced research

|December 30, 2025

概括

这项研究介绍了一种AI模型,用于新的分子生成,准氨酶. 优化的化合物V-24显示出显著的抗黑色素活性,为皮肤色素治疗提供了一种新的策略.

科学领域:

药用化学医学化学
计算化学计算化学
药物发现药物发现药物发现

背景情况:

人工智能 (AI) 显著帮助新药的发现.
铁酶是治疗皮肤色素障碍的关键标.

研究的目的:

开发一种以人工智能驱动的新型分子生成模型,针对氨酶.
识别和优化治疗皮肤色素的强效铁酶抑制剂.

主要方法:

利用基于软行为体-批判性 (SAC) 的强化学习 (RL) 模型进行分子生成.
综合化学反应模板,构建块,分子对接和药物相似性评估.
在人工智能生成的化合物上采用专家指导的结构优化.

主要成果:

生成的分子具有强大的铁酶亲和力,最佳的类似药物的特性和合成可行性.
确定了化合物V,优化衍生物V-24显示增强活性 (纳米范围).
化合物V-24在细胞和斑马鱼模型以及3D皮肤模型中显示出低细胞毒性和显著的抗黑色素效应.

结论:

"AI de novo分子生成 + 专家指导的结构优化"方法是药物发现的新有效策略.
优化化合物V-24显示出作为皮肤色素治疗的铁酶抑制剂的前景.
将人工智能与传统药物化学相结合,可以加快有效的候选药物的识别.

关键词:

人工智能 (AI) 是一种人工智能.在新的分子生成中.由专家指导的结构优化.抑制黑色素的抑制作用铁酶抑制剂铁酶抑制剂

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