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在心脏毒性模拟中使用相对预测的合规系数
Alla P Toropova1, Andrey A Toropov1, Alessandra Roncaglioni1
1Department of Environmental Health Science, Istituto di Ricerche Farmacologiche Mario Negri (IRCCS), Via Mario Negri 2, 20156 Milano, Italy.
Toxics
|April 25, 2025
概括
本研究探讨了使用两个数据库预测心脏毒性的CORAL软件描述符. 该方法证明了用于识别心脏毒性化合物的更好的预测潜力.
科学领域:
- 计算化学是一种计算化学.
- 毒理学 毒理学 毒理学
- 药物发现 药物发现
背景情况:
- 心脏毒性是药物开发中的一个主要问题.
- 预测模型对于早期识别潜在心脏毒性化合物至关重要.
- CORAL软件生成用于QSAR建模的分子描述符.
研究的目的:
- 评估 CORAL 软件生成的描述符作为心脏毒性的预测模型.
- 评估两个不同的心脏毒性数据库的预测性能.
- 研究模型构建算法的对预测准确性的影响.
主要方法:
- 使用CORAL软件生成最佳的分子描述符.
- 应用蒙特卡洛和拉斯维加斯算法用于模型构建和数据分割.
- 采用基于SMILES的分子特征和相关性预测 (CCCP) 的一致系数进行优化.
- 在两个不同尺寸和格式的心脏毒性数据库上验证了模型.
主要成果:
- 珊瑚描述符显示了作为心脏毒性预测模型的潜力.
- 建模方法在两个不同的心脏毒性数据集上得到了验证.
- 使用CCCP的优化提高了开发模型的预测能力.
- 在不同的数据集和建模策略中观察到一致的性能.
结论:
- 珊瑚描述符为开发心脏毒性预测模型提供了一个有希望的途径.
- 应用的计算方法为心脏毒性评估提供了一个强大的框架.
- 进一步完善描述器和算法可以提高药物安全性评估中的预测准确性.
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