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使用基于药的虚拟查,分子对接和MD模拟研究来识别新型PAD2抑制剂

Prakash Jha¹, Prerna Rajoria¹, Priya Poonia¹

¹Laboratory of Molecular Modeling and Anti-Cancer Drug Development, Dr. B. R. Ambedkar Center for Biomedical Research, University of Delhi, Delhi, 110007, India.

Scientific reports

|November 14, 2024

概括

这项研究确定了潜在的新药物,其向蛋白质氨酸减弱酶2 (PAD2),这是一种涉及癌症和神经系统疾病的酶. 计算方法揭示了有希望的重用药物和PAD2的新兴抑制剂,为新的治疗策略铺平了道路.

科学领域:

生物化学和分子生物学
计算化学的计算化学
药理学药理学是指药理学的学科.

背景情况:

蛋白质氨酸减小酶2 (PAD2) 是一个关键的表观遗传调节器,涉及神经系统疾病,类风湿性关节炎,多发性硬化和癌症.
之前没有任何in silico研究集中在PAD2上,用于识别化合物.

研究的目的:

使用计算方法识别针对PAD2的重用药物和选择性抑制剂.
探索PAD2相关疾病的新型治疗策略.

主要方法:

基于结构的药模拟和数百万种化合物的虚拟选.
分子对接,分子动力学 (MD) 模拟和基本动力学研究 (PCA,自由能源景观).
MM-PBSA用于稳定性验证,PCA用于结构分析.

主要成果:

开发了一种具有高选择性和ROC曲线质量的最佳药模型 (Pharm_01).
选了920万种化合物,产生了2575个结果,顶级分子通过MD模拟验证.
从DrugBank中确定了两个有前途的重用PAD2抑制剂和一个来自ZINC数据库的新型抑制剂.

结论:

已识别的化合物显示出作为强大的PAD2抑制剂的潜力.
需要进一步的临床前和临床研究,以开发针对癌症和神经系统疾病的可行治疗方法.

关键词:

药物重新定位是药物重新定位.模拟MD的模拟方法在PAD2中使用PAD2.在PCA分析中使用PCA分析.基于结构的药解体模型虚拟选是一个虚拟的选.

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