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使用相关性强度指数构建皮皮瑞丁衍生物心脏毒性模型

Alla P Toropova¹, Andrey A Toropov¹, Alessandra Roncaglioni¹

¹Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Department of Environmental, Health Science, Via Mario Negri 2, 20156 Milano, Italy.

Molecules (Basel, Switzerland)

|September 28, 2023

概括

在药物化学中,开发心脏毒性预测模型至关重要. 这项研究利用蒙特卡洛技术和最佳描述符,为piperidine衍生物创建精确的定量结构-活性关系 (QSAR) 模型,实现高预测性能.

科学领域:

药用化学医学化学
计算化学计算化学
毒理学毒理学毒理学

背景情况:

心脏毒性评估在药物开发中构成了重大挑战.
定量结构-活性关系 (QSAR) 为预测药物毒性提供了一个有希望的方法.
开发可靠的预测模型对于早期的安全查至关重要.

研究的目的:

开发和验证使用混合最佳描述器对心脏毒性的预测模型.
探索蒙特卡洛技术在构建强大的心脏毒性QSAR模型中的实用性.
评估开发的模型对piperidine衍生物的预测性能.

主要方法:

蒙特卡洛技术用于描述符生成的应用.
开发与心脏毒性相关的混合最佳描述器.
使用定量结构-活动关系 (QSAR) 建模.
开发的心脏毒性模型的外部验证.

主要成果:

开发的QSAR模型显示了对心脏毒性的良好预测潜力.
外部验证集的确定系数在0.90到0.94.9之间.
相对应强度指数进一步提高了模型的预测性能.

结论:

混合最佳描述符与蒙特卡洛技术相结合,可以有效预测心脏毒性.
开发的QSAR模型显示了对piperidine衍生物的高精度和可靠性.
这种方法为药物化学家在开发早期评估药物安全时提供了宝贵的工具.

关键词:

这就是 CORAL 软件.蒙特卡洛方法蒙特卡洛方法心脏有毒性心脏有毒性计算化学计算化学相关性强度指数的相关性强度指数

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