SMASH - Small Molecule NMR Conference

ChemSpider is a free access online database of over 26 million chemical compounds sourced from over 400 different sources including government laboratories, chemical vendors, public resources and publications. ChemSpider allows its users to deposit data including structures, properties, links to external resources and various forms of spectral data. ChemSpider has aggregated over 3000 high quality NMR spectra and continues to expand as the community deposits additional data. The majority of spectral data is licensed as Open Data allowing it to be downloaded and reused. The validation of the data can be performed by members of the community but an automated validation of the data was undertaken using ACD/Labs software using NMR prediction and verification routines. The dataset is a real world dataset containing the contributions of a number of laboratories around the world supplying data of varying quality including S/N issues, misreferencing, impurities etc. This work will report on the batch analysis of the ChemSpider spectral data including the identification of multiple errors in the spectra.

In parallel with the development of new 2D-NMR techniques, the last two decades have seen the development of new approaches for Computer-Assisted Structure Elucidation (CASE). Starting from a number of pioneering works published in the late 1960s, researchers created several generations of CASE expert systems. Nowadays expert systems are powerful analytical tools capable of assisting in the elucidation of very complex molecular structures. These systems adequately mimic the systematic reasoning of spectroscopists but markedly outperform the human expert in logical-combinatorial reasoning. Experience accumulated in the application of expert systems show that CASE methods can dramatically accelerate the procedure of structure elucidation, provide improved reliability of results and, consequently, can save researchers significant amounts of time. This work will investigate two recent examples from the literature that were deemed by the authors as impossible or too difficult to elucidate using traditional methods of 1D and 2D NMR spectra structural interpretation. The application of Computer Assisted Structure Elucidation on these examples will be explored and the CASE results will be presented and explained. It was demonstrated that the application of a CASE approach allowed solving both problems quickly and reliably. We conclude that a modern CASE expert system should be considered as an integral part of a spectroscopist's armory for quick and reliable structure elucidation. It is now impossible to evaluate the capabilities of NMR experimental techniques in isolation from powerful mathematical aids developed for 2D NMR data analysis. We believe that in future CASE software will become a common tool for NMR spectroscopists to apply, much like the software that is today an integral part of X-ray crystallography.

Automated structure verification using 1H NMR data or a combination of 1H and HSQC NMR data is gradually gaining more interest as a routine software application for quality evaluation of large compound libraries produced by synthetic chemistry. The goal of this software application is to identify a manageable subset of compounds and data that require human expertise and review. In practice, the software will flag structure and data combinations that exhibit some inconsistency and automatically validate those that appear consistent. One drawback of this approach is that no automated software system can guarantee that all passed structures are indeed correct structures with correct structural assignments. The major reason for this is that approaches using only 1H or even 1H and HSQC spectra do not always provide enough information to properly distinguish between similar structures. As a result, 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 to pass incorrect structures (i.e. false positives). The essence of the approach is to validate the proposed structure as well as several similar compounds against the same experimental NMR data. The software then evaluates all structures under tighter conditions to determine whether multiple structures can be clearly distinguished from the data. This novel method was applied to automatically validate a series of spectra for non-proprietary compounds from several sources. Presented and discussed is the impact of this approach on false positive and false negative results.