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最近在使用AI/CADD方法开发DprE1抑制剂方面取得的进展

Kepeng Chen¹, Ruolan Xu¹, Xueping Hu²

¹College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China.

Drug discovery today

|April 26, 2024

概括

结核病 (TB) 药物发现的目标是必不可少的酶decapenylphosphoryl-β-d-ribose 2′-oxidase (DprE1). 人工智能和计算机辅助药物设计 (AI/CADD) 加快了用于治疗结核病的新型DprE1抑制剂的识别.

科学领域:

药用化学医学化学
药物发现药物发现药物发现
计算生物学计算生物学

背景情况:

结核病 (TB) 仍然是一个重大的全球健康威胁,由Mycobacterium tuberculosis (Mtb) 引起.
酵素decapenylphosphoryl-β-d-ribose 2′-oxidase (DprE1) 对于mtb细胞壁生物合成至关重要,并且是一个有前途的抗结核病药物标.
现有的治疗方法面临挑战,需要新的治疗策略.

研究的目的:

审查DprE1抑制剂的发现.
阐明DprE1抑制剂的作用机制.
突出 AI/CADD 在发现和优化 DprE1 抑制剂方面的最新进展.

主要方法:

关于DprE1抑制剂发现的文献综述.
分析DprE1的作用机制.
应用在DprE1抑制剂开发中的AI/CADD方法的概述.

主要成果:

DprE1是开发抗结核病药物的验证目标.
已经报告了新的支架和DprE1抑制剂的改善生物活性.
人工智能/CADD方法在加速抑制剂发现方面已经显示出显著的潜力.

结论:

人工智能/CADD技术是发现新型DprE1抑制剂的强大工具.
使用AI/CADD进行进一步的研究可以导致有效的抗结核病候选药物.
准DprE1为抗击结核病提供了一个有希望的途径.

关键词:

DprE1 抑制剂的使用人工智能药物设计人工智能计算机辅助药物设计结核病是一种肺结核病.

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