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Fast & Accurate NMR Prediction from Chemical Structures

Mnova NMRPredict provides fast and accurate NMR spectra predictions from chemical structures. It uses Ensemble NMR Prediction, a novel approach that combines multiple prediction engines, including Machine Learning methods and Modgraph Consultants’ Increments and HOSE-code algorithms.

NMRPredict includes Modgraph and Mestrelab Predictors licenses.

Download Mnova for a 45-Day Free Trial of Mnova NMRPredict

NMRPredict

Benefits

Compute and display accurate chemical shifts for 1H, 13C, and other nuclides such as 11B, 15N,17O, 19F, 29Si, 31P as well as J(HH), J(HF), J(HP), J(CF) and J(CP).

A combination of powerful algorithms (including Machine Learning, HOSE-code and Increments-based methods) run behind the scenes.

Train your predictions by building your NMR databases from already assigned molecular structures.

Helps in peak assignment and structure confirmation when coupled to Mnova NMR processing and analysis tools.

Ability to drill-down user assigned 1H and 13C experimental data.

Each predicted value is accompanied by its confidence interval.

NMRPredict

Features

Combined algorithms from Mestrelab and Modgraph

Mnova NMRPredict shows outstanding prediction accuracy and a reduction in the number of prediction outliers.

Several powerful algorithms run behind the scenes:

  • HOSE Code
  • Machine Learning
  • Increments Method
Mnova-NMR-Predict-feature

Compare predicted & experimental spectra

Use Predict & Compare (or Predict & Verify) to carry out your assignments. Just need to open a 1D dataset with a molecular structure, carry out a multiplet analysis first if it is a 1H spectrum.

Choosing the command ‘Prediction/Predict & Compare’ and Mnova will synthesize the corresponding 1

Mnova-NMR-Predict-feature

Train your predictions

Build 1H, 13C and X nuclei (11B, 31P, 19F, 15N, 17O, 29Si) NMR databases from any Mnova document containing a molecular structure with the resulting assignments; which can be used to enhance the prediction results of similar structures.

Leverage your chemistry knowledge to improve the precision of the NMR predictions!

Mnova-NMR-Predict-feature
Latest NMRPredict news

Chemical shift prediction in 13C NMR spectroscopy using ensembles of message passing neural networks (MPNNs)

This study reports a deep learning approach that utilises message passing neural networks (MPNNs) for predicting chemical shifts in 13C NMR spectra of small molecules. MPNNs were trained on two distinct datasets: one with approximately 4000 labelled structures and another with over 40,000.

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Mestrelab peer reviewed papers

NMR signal processing, prediction and structure verification with Machine Learning techniques

Machine learning (ML) methods have been present in the field of NMR since decades, but it has experienced a tremendous growth in the last few years, especially thanks to the emergence of deep learning (DL) techniques taking advantage of the increased amounts of data and available computer power.

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ensemble-NMRprediction

Ensemble NMR Prediction

Introduction Since the very first release of Mnova, we have been (and still are!) very fortunate to include in the software the prediction of NMR spectra […]
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NMRPredict

Videos

Help & Resources

Guides & Manuals

Mnova 15 - Quick Guidelines NEW Starting Guide NMRPredict

Videos

Workshop - NMR Prediction Mnova Tip 6 - Accurate NMR Prediction for your reagents and products Mnova Tip 11 - NMR Prediction using different frequencies Mnova Tip 14 - Improving Spectral NMR Prediction of Salts

Resources

Ensemble NMR Prediction 1H NMR Auto-assignments Assisted NMR assignments using the predictions

Publications

Chemical shift prediction in 13C NMR spectroscopy using ensembles of message passing neural networks (MPNNs) NMR signal processing, prediction and structure verification with Machine Learning techniques
NMRPredict

Related Applications

Academic, Government & Industrial

Target Audience

Medicinal Chemists
Organic Chemists
Academic Researchers
Analytical Chemists
NMRPredict

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