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DP4-AI automated NMR data analysis: straight from spectrometer to structure.

Published version
Peer-reviewed

Type

Article

Change log

Authors

Howarth, Alexander 
Goodman, Jonathan M  ORCID logo  https://orcid.org/0000-0002-8693-9136

Abstract

A robust system for automatic processing and assignment of raw 13C and 1H NMR data DP4-AI has been developed and integrated into our computational organic molecule structure elucidation workflow. Starting from a molecular structure with undefined stereochemistry or other structural uncertainty, this system allows for completely automated structure elucidation. Methods for NMR peak picking using objective model selection and algorithms for matching the calculated 13C and 1H NMR shifts to peaks in noisy experimental NMR data were developed. DP4-AI achieved a 60-fold increase in processing speed, and near-elimination of the need for scientist time, when rigorously evaluated using a challenging test set of molecules. DP4-AI represents a leap forward in NMR structure elucidation and a step-change in the functionality of DP4. It enables high-throughput analyses of databases and large sets of molecules, which were previously impossible, and paves the way for the discovery of new structural information through machine learning. This new functionality has been coupled with an intuitive GUI and is available as open-source software at https://github.com/KristapsE/DP4-AI.

Description

Keywords

34 Chemical Sciences

Journal Title

Chem Sci

Conference Name

Journal ISSN

2041-6520
2041-6539

Volume Title

11

Publisher

Royal Society of Chemistry (RSC)
Sponsorship
Engineering and Physical Sciences Research Council (EP/P020259/1)
EPSRC (DTP Studentship to Alexander Howarth) Leverhulme Trust (K. E. ECF-2017-255) Isaac Newton Trust (K. E. 17.08(d)) Cambridge Tier-2 system operated by the University of Cambridge Research Computing Service (http://www.hpc.cam.ac.uk) funded by EPSRC Tier-2 capital grant EP/P020259/1