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What’s New in Version 11- Improved 1D NMR Structure Verification Accuracy

Automated structure verification using ACD/Labs software is a method that compares the chemical shifts, intensities, and multiplicities of signals in experimental NMR spectra with those from a predicted NMR spectrum with a proposed structure.

Naturally, in order for this process to be effective the chemical shift prediction, multiplet characterization, and integration measurements must be accurate. This process is described in detail in a 2006 publication in MRC.

As mentioned in the previous post, in version 11 the automated multiplet analysis
algorithm in ACD/Labs software has been significantly improved.

The purpose of this post is to show you how much the improvements of the automated multiplet analysis algorithm in version 11 impacts the performance of automated verification of 1H NMR spectra.

The following results compare the verification improvements in version 11 based on the multiplet analysis enhancements ONLY. In version 11 we made several other improvements in NMR prediction and analysis, and I will get to them in a future post. For now:

For this study, two different data sets each consisting of the 1H NMR spectra of 30 samples and the correct chemical structures were automatically processed, analyzed, and evaluated by the software.

Test Set 1- A set of 30 spectra and their respective chemical structures with reasonably good signal to noise:

Good V10good V11good_2

Test Set 2- A set of 30 spectra and their respective chemical structures with lower signal to noise:

Poor

V10poor

V11poor

As you can see clearly, the improvements in multiplet analysis in version 11 heavily impact the performance of automated NMR verification of 1H NMR data in both datasets. Based on the dataset used for this study, the software (employing the version 11 multiplet analysis algorithm) was able to correctly confirm the consistency between the proposed chemical structure and the experimental spectrum ~60% of the time in both datasets.

For a real world application of this system, check out a previous post that described Anthony Macherone’s workflow at ASDI (and a link to his presentation).

The next questions is, "If you use more data, how well does this system perform?"

A future post will describe a study that highlights the latest performance statistics of a "combined verification" approach that can automatically identify  correct and incorrect chemical structures based on their 1D 1H and 2D HSQC NMR data. This system was described in a 2007 publication in MRC.

Stay Tuned.