Solution NMR Structure of DE NOVO DESIGNED Ferredoxin Fold PROTEIN sfr3, Northeast Structural Genomics Consortium (NESG) Target OR358
SOLUTION NMR
| NMR Experiment | ||||||||
|---|---|---|---|---|---|---|---|---|
| Experiment | Type | Sample Contents | Solvent | Ionic Strength | pH | Pressure | Temperature (K) | Spectrometer |
| 1 | 2D 1H-15N HSQC | 0.787 mM OR358.006 | 90% H2O/10% D2O | 6.5 | ambient | 298 | ||
| 2 | 2D 1H-13C HSQC | 0.787 mM OR358.006 | 90% H2O/10% D2O | 6.5 | ambient | 298 | ||
| 3 | 3D HNCO | 0.787 mM OR358.006 | 90% H2O/10% D2O | 6.5 | ambient | 298 | ||
| 4 | 3D CBCA(CO)NH | 0.787 mM OR358.006 | 90% H2O/10% D2O | 6.5 | ambient | 298 | ||
| 5 | 3D HNCACB | 0.787 mM OR358.006 | 90% H2O/10% D2O | 6.5 | ambient | 298 | ||
| 6 | 3D 1H-13C arom NOESY | 0.787 mM OR358.006 | 90% H2O/10% D2O | 6.5 | ambient | 298 | ||
| 7 | 3D simutaneous 13C-aromatic,13C-aliphatic,15N edited 1H-1H NOESY | 0.787 mM OR358.006 | 90% H2O/10% D2O | 6.5 | ambient | 298 | ||
| 8 | 3D CCH-TOCSY | 0.787 mM OR358.006 | 90% H2O/10% D2O | 6.5 | ambient | 298 | ||
| NMR Spectrometer Information | |||
|---|---|---|---|
| Spectrometer | Manufacturer | Model | Field Strength |
| 1 | Bruker | AVANCE | 800 |
| 2 | Varian | INOVA | 600 |
| 3 | Varian | INOVA | 600 |
| NMR Refinement | ||
|---|---|---|
| Method | Details | Software |
| distance geometry, simulated annealing, molecular dynamics, null | null, null | CNS |
| NMR Ensemble Information | |
|---|---|
| Conformer Selection Criteria | target function |
| Conformers Calculated Total Number | 100 |
| Conformers Submitted Total Number | 20 |
| Representative Model | 1 (lowest energy) |
| Computation: NMR Software | ||||
|---|---|---|---|---|
| # | Classification | Version | Software Name | Author |
| 1 | refinemen,structure solution,geometry optimization | CNS | Brunger, Adams, Clore, Gros, Nilges and Read | |
| 2 | refinement,geometry optimization,structure solution | CYANA | 3.0 | Guntert, Mumenthaler and Wuthrich |
| 3 | data analysis,refinement | AutoStructure | 2.1 | Huang, Tejero, Powers and Montelione |
| 4 | data analysis,chemical shift assignment | AutoAssign | 2.1 | Zimmerman, Moseley, Kulikowski and Montelione |
| 5 | processing | NMRPipe | Delaglio, Grzesiek, Vuister, Zhu, Pfeifer and Bax | |
| 6 | data analysis,peak picking,chemical shift assignment | XEASY | Bartels et al. | |
| 7 | collection | TopSpin | Bruker Biospin | |
| 8 | collection | VnmrJ | Varian | |
| 9 | data analysis | Sparky | Goddard | |
| 10 | geometry optimization | TALOS+ | Shen, Cornilescu, Delaglio and Bax | |
| 11 | geometry optimization | PALES | PALES (Zweckstetter, Bax) | |
| 12 | geometry optimization | REDCAT | Valafar, Prestegard | |
| 13 | structure validation | PSVS | Bhattacharya, Montelione | |
| 14 | refinement | CYANA | Huang, Tejero, Powers and Montelione | |
| 15 | refinement | CNS | Brunger, Adams, Clore, Gros, Nilges and Read | |














