Home of the tools and software at the Mulder bioNMR lab
If you use our software programs or databases, then please cite our work as it is only fair and polite, and helps me to maintain a lab and provide even more tools. Please click here, opens an external URL in a new window for a more complete overview of our most recent publications.
CheSPI: Chemical shift based Structure Population Inference
You can now predict DSSP structural classes from chemical shifts using the server here: https://st-protein.chem.au.dk/chespi, opens an external URL in a new window
You can download CheSPI python source code for random coil chemical shift prediction at github: https://github.com/protein-nmr/CheSPI, opens an external URL in a new window
NB: A python3 version that accepts NMRSTAR3.x format is now available for command line execution at github" above
CheSPI: Chemical shift Secondary structure Population Inference (CheSPI), opens an external URL in a new window
Nielsen JT, Mulder FAA.
J Biomol NMR. 2021 Jul;75(6-7):273-291. doi: 10.1007/s10858-021-00374-w
POTENCI
You can predict your 'random coil chemical shifts' using POTENCI at the server here: https://st-protein02.chem.au.dk/potenci/, opens an external URL in a new window
You can download POTENCI python source code for random coil chemical shift prediction at github: https://github.com/protein-nmr/POTENCI, opens an external URL in a new window
POTENCI: prediction of temperature, neighbor and pH-corrected chemical shifts for intrinsically disordered proteins., opens an external URL in a new window (POTENCI)
Nielsen JT, Mulder FAA.
J Biomol NMR. 2018 Mar;70(3):141-165. doi: 10.1007/s10858-018-0166-5
CheZOD disorder database/predictor
You can download the CheZOD database used for testing disorder predictors at these links:
http://www.protein-nmr.org/CheZOD.tar.gz, opens a file and http://www.protein-nmr.org/chezodseqs.txt, opens a file for the "117" protein dataset (used in Nielsen JT & Mulder FAA, Front Mol Biosci. 2016)
http://www.protein-nmr.org/CheZOD1325.tar.gz, opens a file and http://www.protein-nmr.org/allseqs1325.fasta, opens a file for the "1325" protein dataset used for ODiNPred (Dass R, Mulder FAA, Nielsen JT., Sci Rep. 2020)
There is Diversity in Disorder-"In all Chaos there is a Cosmos, in all Disorder a Secret Order"., opens an external URL in a new window (CheZOD database)
Nielsen JT, Mulder FAA.
Front Mol Biosci. 2016 Feb 11;3:4. doi: 10.3389/fmolb.2016.00004
Predict your protein's CheZOD disorder score from assigned NMR chemical shifts at the server: https://st-protein.chem.au.dk/chezod, opens an external URL in a new window
Quantitative Protein Disorder Assessment using NMR Chemical Shifts, opens an external URL in a new window (CheZOD predictor)
Nielsen JT, Mulder FAA.
Methods Mol Biol. 2020;2141:303-317. doi: 10.1007/978-1-0716-0524-0_15.
Protein disorder prediction from sequence (ODiNPred)
You can predict the order/disorder profile for a protein from sequence here: https://st-protein.chem.au.dk/odinpred, opens an external URL in a new window
Quality and bias of protein disorder predictors., opens an external URL in a new window
Nielsen JT, Mulder FAA.
Sci Rep. 2019 Mar 26;9(1):5137. doi: 10.1038/s41598-019-41644-w
ODiNPred: comprehensive prediction of protein order and disorder., opens an external URL in a new window
Dass R, Mulder FAA, Nielsen JT.
Sci Rep. 2020 Sep 8;10(1):14780. doi: 10.1038/s41598-020-71716-1
pepKalc
You can predict peptide/IDP titration curves (and compute pKa constants, etc.) at the server here: https://st-protein02.chem.au.dk/pepkalc/, opens an external URL in a new window
pepKalc: scalable and comprehensive calculation of electrostatic interactions in random coil polypeptides. , opens an external URL in a new window(pepKalc)
Tamiola K, Scheek RM, van der Meulen P, Mulder FAA.
Bioinformatics. 2018 Jun 15;34(12):2053-2060. doi: 10.1093/bioinformatics/bty033.
ncIDP/ncSPC
You can predict your 'random coil chemical shifts' with ncIDP (2010) at the server here: https://st-protein02.chem.au.dk/ncIDP/, opens an external URL in a new window
(NB this tool is superseded by POTENCI, see section on POTENCI)
Sequence-specific random coil chemical shifts of intrinsically disordered proteins. , opens an external URL in a new window(ncIDP)
Tamiola K, Acar B, Mulder FAA.
J Am Chem Soc. 2010 Dec 29;132(51):18000-3. doi: 10.1021/ja105656t
The ncSPC program for assessing structural propensities based on ncIDP is found here: https://st-protein02.chem.au.dk/ncSPC/, opens an external URL in a new window
(NB this tool is superseded by CheSPI, see section on CheSPI)
Using NMR chemical shifts to calculate the propensity for structural order and disorder in proteins., opens an external URL in a new window (ncSPC)
Tamiola K, Mulder FAA.
Biochem Soc Trans. 2012 Oct;40(5):1014-20
Common Impurities Finder for organ(ometall)ic chemists and biochemists
Don't know what that peak is in your spectrum? Query it here against a database of common impurities based chemical shift and coupling pattern: common impurities, opens an external URL in a new window
Bruker NMR Pulse sequence download
(remove extension .txt when placing in PP directory)
- 3D HNCOCO - CO/N/H version (Yoshimura et al., JBNMR 2015): hncocogp3d1, opens a file
- 3D HNCOCO - N/N/H version (Yoshimura et al., JBNMR 2015): hncocogp3d2, opens a file
- Arg head group CN experiment (Yoshimura et al., Angewandte Chemie 2017): arginine_head_group.yy, opens a file
- Paris-DECOR - fast backbone HX by HA(CACO)N (Dass et al., ChemPhysChem 2019): hcacongp3d-hdx, opens a file
- Paris-DECOR - fast backbone HX by CON (Dass et al., Methods Mol Biol. 2020): c_con_sq_bshd_hd_v3, opens a file
NMR assignments and protein structures (ensembles) not deposited to databases (yet)
- NMR backbone assignments of dimeric p53 from https://pubmed.ncbi.nlm.nih.gov/11101222/, opens an external URL in a new window, (get data1, opens a file, data2, opens a file)
- NMR ensemble of the intrinsically disordered protein MOAG-4 from https://pubmed.ncbi.nlm.nih.gov/28336532/, opens an external URL in a new window, (get data, opens an external URL in a new window)