使用虚拟选,分子对接和MD模拟,对天然化合物作为抗宏化物耐药蛋白的抑制剂进行计算研究
Abdullah R Alanzi1, Bayan Abdullah Alhaidhal2, Raghad Mohammad Aloatibi2
1Department of Pharmacognosy, College of Pharmacy, King Saud University, Riyadh, 11451, Saudi Arabia. aralonazi@ksu.edu.sa.
Scientific reports
|May 11, 2025
概括
这项研究使用分子建模来识别可能抑制细菌宏类耐药酶的天然产品. 几种化合物显示出高结合亲和力,表明它们可能成为抗生素耐药性的新治疗剂.
科学领域:
- 药用化学 医学化学
- 计算生物学 计算生物学
- 药理学 药理学是指药理学的学科.
背景情况:
- 宏类抗生素对于治疗细菌感染至关重要.
- 增加细菌对宏酸盐的耐药性需要新的治疗策略.
- 像mphA,mphB,EreC和ErmAM这样的酶是克服宏类耐药性的关键目标.
研究的目的:
- 使用分子建模识别关键宏类抗性酶的天然产品抑制剂.
- 通过ADMET分析评估已识别的化合物的治疗潜力.
- 用分子动力学和结合能量的计算来验证计算结果.
主要方法:
- 从LOTUS数据库中对1,400种天然产品进行对接,使用Glide工具对五种宏化物耐药酶进行对接.
- 根据滑行得分和随后的ADMET分析选择排名最高的化合物.
- 分子动态模拟和MM-GBSA计算,以完善结合亲和度评估.
主要成果:
- 对每个酶具有高结合亲和力的特定化合物的鉴定:LTS0271681 (ErmAM),LTS0263188 (排水),LTS0024216 (mphA),LTS0110759 (mphB) 和LTS0100971 (EreC).
- 对ADMET的分析表明,所选化合物的治疗开发潜力.
- 计算验证证实了这些天然产品作为宏类耐药抑制剂的潜力.
结论:
- 这项研究确定了有希望的天然产品候选人,用于抑制细菌的宏类耐药机制.
- 这些化合物代表了开发新药来打击抗生素耐药性的潜在起点.
- 进一步的体外验证对于将这些计算发现转化为临床应用至关重要.
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