基于人工智能的天然抑制剂针对RPS20用于结直肠癌治疗,使用集成计算方法
Nouman Ali1, Roman Akbar2, Amna Saleem3
1Department of Biotechnology, Faculty of Science and Technology, University of Central Punjab, Lahore, Punjab, Pakistan. Nouman.ali.anwar336@gmail.com.
Scientific reports
|July 10, 2025
概括
这项研究确定了天然化合物印鲁作为结直肠癌的有希望的候选药物. 使用计算方法和人工智能,发现其作为一种有效的癌症抑制剂,副作用最小的潜力.
科学领域:
- 计算机化药物发现.
- 在瘤学瘤学.
- 生物信息学是一种生物信息学.
背景情况:
- 全球癌症发病率需要新的治疗策略.
- 机器学习和人工智能加速了抗癌点的识别和药物开发.
- 自然化合物为新药发现提供了丰富的来源.
研究的目的:
- 探索天然化合物作为结直肠癌的潜在治疗方法.
- 使用计算方法识别和验证新的抗癌标.
- 为了发现一种强大的天然药物候选人,用于结直肠癌.
主要方法:
- 从PubChem获得20种天然化合物,并从AlphaFold获得RPS20蛋白质结构.
- 使用Ramachandran图和ERRAT验证蛋白质结构,并使用DeepSite识别结合部位.
- 虚拟查,ADMET分析,基于人工智能的药物设计 (WADDAICA),分子对接,分子动力学 (MD) 模拟,MMGBSA和DFT计算.
主要成果:
- 印鲁被确定为具有有利的ADMET标准和结合亲和力的主要候选药物.
- 基于AI的药物设计和随后的验证证实了Indirubin的潜力.
- DFT计算显示了适度的HOMO-LUMO差距,表明潜在的反应性和生物标相互作用.
结论:
- 印鲁显示出作为一种强效的结直肠癌抑制剂的显著潜力.
- 这项研究强调了计算方法和人工智能在加速药物发现方面的有效性.
- 印度鲁可能提供一种具有高疗效和最小副作用的治疗选择.
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