Dereplication of natural products using minimal NMR data inputs.

A strategy for the dereplication of a complete or a partial structure using (1)H NMR, (1)H-(13)C HSQC and (1)H-(1)H COSY spectral data, a molecular formula composition range and structural fragments against a massive database of about 22 million compounds is considered. As the increasing availability of public online databases containing natural products continues to grow the potential of utilizing these resources for dereplication purposes increases. This work examines approaches for NMR dereplication of natural products and includes a comparison with approaches for molecular formula and mass-based dereplication. The strategy is an application of computer-assisted structure elucidation using ACD/Structure Elucidator and data obtained from the ChemSpider database hosted by the Royal Society of Chemistry.

Concurrent combined verification: reducing false positives in automated NMR structure verification through the evaluation of multiple challenge control structures.

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.

Automated structure verification based on a combination of 1D (1)H NMR and 2D (1)H - (13)C HSQC spectra.

A method for structure validation based on the simultaneous analysis of a 1D (1)H NMR and 2D (1)H - (13)C single-bond correlation spectrum such as HSQC or HMQC is presented here. When compared with the validation of a structure by a 1D (1)H NMR spectrum alone, the advantage of including a 2D HSQC spectrum in structure validation is that it adds not only the information of (13)C shifts, but also which proton shifts they are directly coupled to, and an indication of which methylene protons are diastereotopic. The lack of corresponding peaks in the 2D spectrum that appear in the 1D (1)H spectrum, also gives a clear picture of which protons are attached to heteroatoms. For all these benefits, combined NMR verification was expected and found by all metrics to be superior to validation by 1D (1)H NMR alone. Using multiple real-life data sets of chemical structures and the corresponding 1D and 2D data, it was possible to unambiguously identify at least 90% of the correct structures. As part of this test, challenging incorrect structures, mostly regioisomers, were also matched with each spectrum set. For these incorrect structures, the false positive rate was observed as low as 6%.