A worldwide e-Infrastructure for NMR and structural biology

UNIO - High-throughput and High-output NMR Data Analysis for Protein Structure Determination and More


UNIO enables you to perform automated NMR data analysis for protein 3D structure determination. UNIO represents the result of more than a decade of innovative research performed in order to enable accurate, objective and highly automated protein structure determination by NMR. 
UNIO NMR data analysis assembles the MATCH algorithm for backbone assignment (1), the ASCAN algorithm for side-chain assignment (2), the CANDID algorithm for NOE assignment (3) and the ATNOS algorithm for NMR signal identification (4) forming the core of UNIO and are accessed via a user-friendly and flexible graphical user interface. Crucial key elements in order to seamlessly integrate the principal data analysis components are novel routines for chemical shift referencing and chemical shift adaptation between the different NMR spectra used. The standard UNIO data analysis protocol requires only a minimal set of six NMR spectra, namely 3 APSY and 3 NOESY, and features high computational efficiency. Triple-resonance NMR experiments can alternatively be used instead of APSY data for obtaining the backbone resonance assignments. Powerful interactive graphic and text tools facilitate and enhance expert intervention at the structure refinement stage in form of validation, correction and completion of intermediate and final results.
The underlying NMR data analysis models in UNIO were designed for real-world applications in ”standard” NMR laboratories (requiring magnetic field strengths of 500MHz equipped with cryoprobe or 600MHz or above).
The experience gained so far (> 30 de novo structure determinations performed with the entire protocol ranging from backbone resonance assignment to 3D structure calculation) shows that the UNIO approach leads to accurate and objective NMR data interpretation (see UNIO structures). Typically, protein structures are determined within two weeks, including time spent on the NMR experiments.
(1) Volk, J.; Herrmann, T.; Wüthrich, K. J. Biomol.NMR. 2008, 41, 127-138.
(2) Fiorito, F.; Damberger, F.F.; Herrmann, T.; Wüthrich, K. J. Biomol. NMR 2008, 42, 23-33.
(3) Herrmann, T.; Güntert, P.; Wüthrich, K. J. Mol. Biol. 2002, 319, 209-227.
(4) Herrmann, T.; Güntert, P.; Wüthrich, K. J. Biomol. NMR 2002, 24, 171-189.



Cite WeNMR/WestLife

Usage of the WeNMR/WestLife portals should be acknowledged in any publication:
"The FP7 WeNMR (project# 261572) and H2020 West-Life (project# 675858) European e-Infrastructure projects are acknowledged for the use of their web portals, which make use of the EGI infrastructure and DIRAC4EGI service with the dedicated support of CESNET-MetaCloud, INFN-PADOVA, NCG-INGRID-PT, RAL-LCG2, TW-NCHC, SURFsara and NIKHEF, and the additional support of the national GRID Initiatives of Belgium, France, Italy, Germany, the Netherlands, Poland, Portugal, Spain, UK, South Africa, Malaysia, Taiwan and the US Open Science Grid."
And the following article describing the WeNMR portals should be cited:
Wassenaar et al. (2012). WeNMR: Structural Biology on the Grid.J. Grid. Comp., 10:743-767.


The WeNMR Virtual Research Community has been the first to be officially recognized by the EGI.

European Union

WeNMR is an e-Infrastructure project funded under the 7th framework of the EU. Contract no. 261572

WestLife, the follow up project of WeNMR is a Virtual Research Environment e-Infrastructure project funded under Horizon 2020. Contract no. 675858