Real-time prediction of 1H and 13C chemical shifts with DFT accuracy using a 3D graph neural network-Reference-Cited by-同舟云学术

Real-time prediction of 1H and 13C chemical shifts with DFT accuracy using a 3D graph neural network

Published:2021 Issue:36 Volume:12 Page:12012-12026
ISSN:2041-6520
Container-title:Chemical Science
language:en
Short-container-title:Chem. Sci.

Author:

Guan Yanfei¹^ORCID,Shree Sowndarya S. V.¹^ORCID,Gallegos Liliana C.¹^ORCID,St. John Peter C.²^ORCID,Paton Robert S.¹^ORCID

Affiliation:

1. Department of Chemistry, Colorado State University, Fort Collins, CO, 80523, USA

2. Biosciences Center, National Renewable Energy Laboratory, Golden, CO 80401, USA

Abstract

From quantum chemical and experimental NMR data, a 3D graph neural network, CASCADE, has been developed to predict carbon and proton chemical shifts. Stereoisomers and conformers of organic molecules can be correctly distinguished.

Funder

National Science Foundation

U.S. Department of Energy

Publisher

Royal Society of Chemistry (RSC)

Subject

General Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2021/SC/D1SC03343C

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4. Predicting NMR Spectra by Computational Methods: Structure Revision of Hexacyclinol

5. The Correct Structure of Aquatolide—Experimental Validation of a Theoretically-Predicted Structural Revision

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