| NESG ID: | NAME |
| PDB ID: | |
| Deposition date: | |
| Common Name: | |
| Class: | |
| Length (a.a.): | 158 |
| Organism: | |
| SwissProt / TrEMBL ID: | |
| # models: | 20 |
| Oligomerization: | monomer |
| Molecular weight: | 16854 |
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Analyses performed for user defined residues.
The constraints analysis is based on the following files: NOE distance constraints file. Angular constraints file. H-bond constraints file.
Procheck analysis,RMSD calculation and structure superimposition are based on: User defined residues
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Secondary Structure Elements:
alpha helices: 54A-60A, 105A-112A, 123A-136A
beta strands: 14L-16L, 22E-24E, 27L-29L, 42A-43A, 33E-35E, 140L-144L, 91L-95L, 117Y-121Y
| Total number of restricting constraints per restrained residue: | 10.0 |
| Restricting long range constraints per restrained residue: | 4.0 |
Distance violations per model
Calculated using sum over r^-6
| 0.1 - 0.2 Å | 0.2 - 0.5 Å | > 0.5 Å |
| 2.65 | 0.6 | 1.15 |
Dihedral angle violations per model
1 - 10 ° > 10 ° 0.85 0.35
FIDs deposited in the BMRB? no
| RMSD | All residues | Ordered residues2 | Selected residues3 |
| All backbone atoms | 5.0 Å | 0.6 Å | 0.6 Å |
| All heavy atoms | 5.5 Å | 1.0 Å | 1.0 Å |
Ramachandran Plot Summary for selected residues3 from Procheck
| Most favoured regions | Additionally allowed regions | Generously allowed regions | Disallowed regions |
| 94.9% | 5.1% | 0.0% | 0.0% |
Ramachandran Plot Summary for selected residues3 from Richardson Lab's Molprobity
| Most favoured regions | Allowed regions | Disallowed regions | View plot View model summary |
| 98.4% | 1.5% | 0.1% |
Global quality scores
| Program | Verify3D | ProsaII (-ve) | Procheck (phi-psi)3 | Procheck (all)3 | MolProbity Clashscore |
| -Raw score | 0.42 | 0.40 | -0.13 | 0.06 | 4.70 |
| Z-score1 | -0.64 | -1.03 | -0.20 | 0.35 | 0.72 |
Close Contacts and Deviations from Ideal Geometry (from PDB validation software)
| Number of close contacts (within 1.6 Å for H atoms, 2.2 Å for heavy atoms): | 0 |
| RMS deviation for bond angles: | 0.7 ° |
| RMS deviation for bond lengths: | 0.009 Å |
1 With respect to mean and standard deviation for a set of 252 X-ray structures < 500 residues, of resolution <= 1.80 Å, R-factor <= 0.25 and R-free <= 0.28; a positive value indicates a 'better' score
2Order residues: 13A-16A,21A-24A,27A-37A,40A-63A,89A-95A,100A-146A
3Selected residues: 13A-16A,21A-24A,27A-37A,40A-63A,89A-95A,100A-145A
Residue Plot of Ramachandran anlysis(based on data from Richardson Lab's Molprobity)
References:
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2. Bowie J U, Luthy R and Eisenberg D, "A Method to Identify Protein Sequences that Fold into a Known Three-Dimensional Structure", Science 253 (1991): 164-169
3. Sippl M J, "Recognition of Errors in Three-Dimensional Structures of Proteins", Proteins 17 (1993): 355-362
4. Sippl M J, "Calculation of Conformation Ensembles from Potentials of Mean Force", J Mol Biol 213 (1990): 859-883
5. Laskowski R Ai et al, "AQUA and PROCHECK_NMR: Programs for checking the quality of proteins structures solved by NMR", J Biomolec NMR 8 (1996): 477-486
6. Laskowski R A et al "PROCHECK: a program to check the stereochemical quality of protein structures" J Appl Cryst, 26 (1993): 283-291
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10. Tejero R and Montelione G T, "PDBStat", unpublished
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12. Richardson D C, Richardson J S, "The kinemage: a tool for scientific communication", Prot Sci 1(1) (1992): 3-9
13. Koradi, R, et al, "MOLMOL: a program for display and analysis of macromolecular structures ", J Mol Graphics 14 (1996): 51-55.
14. Güntert, P, Mumenthaler, C & Wüthrich, K "Torsion angle dynamics for NMR structure calculation with the new program DYANA", J. Mol. Biol 273 (1997): 283-298
15. Lovell S C et al, "Structure validation by Calpha geometry: phi,psi and Cbeta deviation" Proteins (2003) 50: 437-450
16. Kabsch W, Sander C, "Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features", Biopolymers (1983) 22: 2577-2637
17. Bagaria, A., Jaravine, V., Huang, Y.J., Montelione, G.T., and Guntert, P. "Protein structure validation by generalized linear model root-mean-square deviation prediction". Protein Sci 21(2012), 229-238.