About NMRtist

NMRtist is a cloud computing service for the fully automated analysis of protein NMR spectra (e.g. peak picking, chemical shift assignment, structure determination) using deep learning-based approaches. Each project created in NMRtist receives 30 GB of private storage, which can be filled by experimental data and analyzed using the available applications. You don't need to have any hardware resources or follow complex software configuration processes. NMRtist applications can be executed by just few mouse clicks in your web browser. All calculations are executed on NMRtist computational nodes, making the results available for download from NMRtist website.

ARTINA is a deep learning-based application for end-to-end protein structure determination by NMR spectroscopy. Using as input NMR spectra and the protein sequence, the method identifies automatically (strictly without any human intervention): cross-peak positions, chemical shift assignments, upper limit distance restraints, and the protein structure. ARTINA deep learning models have been trained with over 600 000 cross-peak examples from more than 1300 2D/3D/4D spectra. The method demonstrated its ability to solve structures with a median backbone RMSD of 1.44 Å to PDB reference, and identified correctly 91.36% of the chemical shift assignments. View our short video tutorial to learn how to get started with ARTINA.

New Update (27.03.2023): We've added support for additional file types: (a) manual peak lists (.list, .peaks), (b) chemical shift lists (.prot), (c) chemical shift statistics (.stats), (d) lower/upper distance restraints (.lol/.upl), (e) Talos angle restraints (.aco), and (f) protein structure (.pdb). With this latest release, all of these files can now be uploaded to the project storage and utilized as inputs for applications. The new data files enable users to perform structure-based assignment, chemical shift transfer, and to use manually refined ARTINA output files in application runs. Learn more about the supported file formats in our blog article.

You can use the NMRtist platform free-of-charge (academic users) to perform automated peak picking, shift assignment, or full structure determination. Create a free account to use all functions of the service, or start an anonymous project by pressing the button below.

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Getting started tutorial

This tutorial presents the first steps in the NMRtist system. It guides through account and project creation, data upload, and submission of an exemplary structure calculation job. You can go through the tutorial with your own data, or use one of our example datasets. We highly recommend doing this tutorial before making the first application call.


Artificial Intelligence for NMR Applications (ARTINA) is a deep learning-based approach to fully automated NMR protein structure determination. The method takes as input only NMR spectra and the protein sequence, and delivers automatically: peak lists, shift assignments, distance restraints, and the structure.

Video tutorial

This video tutorial introduces beginners to the NMRtist system, guiding them through the process of submitting an automated protein structure determination job, and showcasing representative results from such a job.

Examples of automatically determined structures

Orange - PDB deposition, Blue - structure determined automatically by ARTINA, using as input only NMR spectra and the protein sequence


Jan. 15, 2024, 8:14 p.m.

[Manuscript] The 100-protein NMR spectra dataset: A resource for biomolecular NMR data analysis

Open dataset containing 1329 2D-4D NMR spectra that allow the reproduction of 100 protein structures from original measurements. This dataset was originally compiled for the development of the ARTINA deep learning-based spectra analysis method (see https://nmrdb.ethz.ch and the manuscript).

Nov. 30, 2023, 8:15 p.m.

[Manuscript] Time-optimized protein NMR assignment with an integrative deep learning approach using AlphaFold and chemical shift prediction

Our new study, recently accepted in Science Advances (https://www.science.org/doi/full/10.1126/sciadv.adi9323), explores the integration of in-silico predictions like AlphaFold with ARTINA, enhancing the efficiency and accuracy of NMR data analysis. This research represents a significant leap towards data-efficient use of our system for protein studies.

Feb. 2, 2023, 8:39 p.m.

[Manuscript] NMRtist: an online platform for automated biomolecular NMR spectra analysis

Our manuscript (application note), presenting the NMRtist platform, has been accepted for publication in Bioinformatics (https://doi.org/10.1093/bioinformatics/btad066).

Dec. 21, 2022, midnight

NMRtist usage

Since the release of the platform in February 2022, NMRtist analysed 4 368 2D/3D/4D NMR spectra, completed 1 100 automated chemical shift assignment and 444 automated structure determination jobs.

Dec. 20, 2022, midnight

ARTINA and NMRtist presented to the broader audience

Between 06.2022 and 01.2023, we presented ARTINA and NMRtist at several NMR events, including: Chianti Workshop (Principina Terra, Italy), EUROMAR (Utrecht, The Netherlands), EMBO Practical Course (Basel, Switzerland), EMBO Lecture Course (Berhampur, India), Biomolecular NMR: Advanced Tools, Machine Learning (Gothenburg, Sweden), and ICMRBS (Boston, USA).

Oct. 19, 2022, midnight

[Manuscript] Rapid protein assignments and structures from raw NMR spectra with the deep learning technique ARTINA

Our manuscript, presenting the ARTINA workflow for rapid assignment and structure determination, has been published in Nature Communications (https://doi.org/10.1038/s41467-022-33879-5).

Oct. 2, 2021, midnight

Biomolecular NMR: Advanced Tools workshop

NMRtist was presented at the Biomolecular NMR: Advanced Tools workshop (29.09-01.10 2021). All participants of the training, supervised by Prof. Peter Güntert and Dr. Piotr Klukowski, submitted datasets to the platform, obtaining automatically determined structures and/or assignments.

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