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首页> 外文期刊>Magnetic Resonance in Chemistry: MRC >Concurrent combined verification: Reducing false positives in automated NMR structure verification through the evaluation of multiple challenge control structures
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Concurrent combined verification: Reducing false positives in automated NMR structure verification through the evaluation of multiple challenge control structures

机译:并行组合验证:通过评估多个挑战控制结构来减少自动NMR结构验证中的误报

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摘要

Automated structure verification using ~1H NMR data or a combination of ~1H and heteronuclear single-quantum correlation (HSQC) data is gaining more interest as a routine application for qualitative evaluation of large compound libraries produced by synthetic chemistry. The goal of this automated software method is to identify a manageable subset of compounds and data that require human review. In practice, the automated method will flag structure and data combinations that exhibit some inconsistency (i.e. strange chemical shifts, conflicts in multiplicity, or overestimated and underestimated integration values) and validate those that appear consistent. One drawback of this approach is that no automated system can guarantee that all passing structures are indeed correct structures. The major reason for this is that approaches using only ~1H or even ~1H and HSQC spectra often do not provide sufficient information to properly distinguish between similar structures. Therefore, current implementations of automated structure verification systems allow, in principle, false positive results. Presented in this work is a method that greatly reduces the probability of an automated validation system passing incorrect structures (i.e. false positives). This novel method was applied to automatically validate 127 non-proprietary compounds from several commercial sources. Presented also is the impact of this approach on false positive and false negative results.
机译:作为常规应用,对合成化学生产的大型化合物库进行定性评估,使用〜1H NMR数据或〜1H和异核单量子相关(HSQC)数据的组合进行自动结构验证越来越引起人们的兴趣。这种自动化软件方法的目标是识别需要人工检查的化合物和数据的可管理子集。在实践中,自动方法将标记结构和数据组合,这些结构和数据组合表现出一些不一致之处(即奇怪的化学位移,多重性冲突或积分值被高估和低估)并验证那些看起来一致的数据。这种方法的一个缺点是没有自动化系统可以保证所有经过的结构确实是正确的结构。这样做的主要原因是,仅使用〜1H或什至〜1H和HSQC光谱的方法通常无法提供足够的信息来正确地区分相似的结构。因此,自动结构验证系统的当前实现原则上允许假阳性结果。这项工作提出了一种大大降低自动验证系统通过不正确结构(即误报)的可能性的方法。这种新颖的方法被用于自动验证来自几种商业来源的127种非专有化合物。还提出了这种方法对假阳性和假阴性结果的影响。

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