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Concurrent combined verification: reducing false positives in automated NMR structure verification through the evaluation of multiple challenge control structures
Author(s) -
Golotvin Sergey S.,
Pol Rostislav,
Sasaki Ryan R.,
Nikitina Asya,
Keyes Philip
Publication year - 2012
Publication title -
magnetic resonance in chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.483
H-Index - 72
eISSN - 1097-458X
pISSN - 0749-1581
DOI - 10.1002/mrc.3818
Subject(s) - false positive paradox , heteronuclear single quantum coherence spectroscopy , software , computer science , data mining , algorithm , chemistry , artificial intelligence , programming language , two dimensional nuclear magnetic resonance spectroscopy , stereochemistry
Automated structure verification using 1 H NMR data or a combination of 1 H 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 1 H or even 1 H 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. Copyright © 2012 John Wiley & Sons, Ltd.