结构活动关系的比较效率和蛋白质化学模型
Georgy S Malakhov1, Dmitry A Karasev2, Boris N Sobolev2
1Department of Bioinformatics, Institute of Biomedical Chemistry, 119121, Moscow, Russia; Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University, 119991, Moscow, Russia.
蛋白化学测量 (PCM) 在预测已知的药物联体方面没有优于结构-活性关系 (SAR). 当前的验证方法会增加PCM得分,因此透明的验证方案对于准确的方法比较至关重要.
科学领域:
- 计算化学是一种计算化学.
- 化学信息学 化学信息学
- 药物发现 药物发现
背景情况:
- 虚拟查是识别毒品线索的关键.
- 结构-活性关系 (SAR) 模型比较化学结构.
- 蛋白化学测量 (PCM) 集成蛋白质标描述器,扩展SAR能力.
研究的目的:
- 严格比较SAR和PCM用于预测已知的蛋白质标的配体.
- 评估验证方案对方法性能的影响.
- 解决在特定应用中PCM优于SAR的普遍但尚未被证明的说法.
主要方法:
- 开发一个专门的验证方案来比较SAR和PCM.
- 应用SAR和PCM来预测具有既定连接体光谱的蛋白质的连接体.
- 在新的验证方案下对预测性能进行比较分析.
主要成果:
- 没有发现PCM与SAR相比具有显著优势,用于预测具有已知的联结体光谱的蛋白质联结体.
- 对于PCM模型的标准验证程序会膨胀性能指标.
- 通常使用的验证方案导致PCM疗效与SAR相比被高估.
结论:
- 在预测具有既定连接体光谱的蛋白质连接体方面,PCM没有证明其优于SAR.
- 当前的PCM验证实践可能会误导,导致性能得分升高.
- 透明和适当的验证策略对于药物发现研究中可靠的方法比较至关重要.
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