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NMR processing:
MDD
NMR assignment:
Backbone:
Autoassign
MARS
UNIO Match
PINE
Side-chains:
UNIO ATNOS-Ascan
NOEs:
UNIO ATNOS-Candid
UNIO Candid
ASDP
Structure from NMR restraints:
Ab initio:
GeNMR
Cyana
XPLOR-NIH
ASDP
UNIO ATNOS-Candid
UNIO Candid
Fragment-based:
BMRB CS-Rosetta
Rosetta-NMR (Robetta)
Template-based:
GeNMR
I-TASSER
Refinement:
Amber
Structure from chemical shifts:
Fragment-based:
WeNMR CS-Rosetta
BMRB CS-Rosetta
Homology-based:
CS23D
Simshift
Torsion angles from chemical shifts:
Preditor
TALOS
Promega- Proline
Secondary structure from chemical shifts:
CSI (via RCI server)
TALOS
MICS caps, β-turns
d2D
PECAN
Flexibility from chemical shifts:
RCI
Interactions from chemical shifts:
HADDOCK
Chemical shifts re-referencing:
Shiftcor
UNIO Shiftinspector
LACS
CheckShift
RefDB
NMR model quality:
NOEs, other restraints:
PROSESS
PSVS
RPF scores
iCing
Chemical shifts:
PROSESS
CheShift2
Vasco
iCing
RDCs:
DC
Anisofit
Pseudocontact shifts:
Anisofit
Protein geomtery:
Resolution-by-Proxy
PROSESS
What-If
iCing
PSVS
MolProbity
SAVES2 or SAVES4
Vadar
Prosa
ProQ
MetaMQAPII
PSQS
Eval123D
STAN
Ramachandran Plot
Rampage
ERRAT
Verify_3D
Harmony
Quality Control Check
NMR spectrum prediction:
FANDAS
MestReS
V-NMR
Flexibility from structure:
Backbone S2
Methyl S2
B-factor
Molecular dynamics:
Gromacs
Amber
Antechamber
Chemical shifts prediction:
From structure:
Shiftx2
Sparta+
Camshift
CH3shift- Methyl
ArShift- Aromatic
ShiftS
Proshift
PPM
CheShift-2- Cα
From sequence:
Shifty
Camcoil
Poulsen_rc_CS
Disordered proteins:
MAXOCC
Format conversion & validation:
CCPN
From NMR-STAR 3.1
Validate NMR-STAR 3.1
NMR sample preparation:
Protein disorder:
DisMeta
Protein solubility:
camLILA
ccSOL
Camfold
camGroEL
Zyggregator
Isotope labeling:
UPLABEL
Solid-state NMR:
sedNMR


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Default On deriving spatial protein structure from NMR or X-ray diffraction data.

On deriving spatial protein structure from NMR or X-ray diffraction data.

Related Articles On deriving spatial protein structure from NMR or X-ray diffraction data.

Ciba Found Symp. 1991;161:150-9; discussion 159-66

Authors: van Gunsteren WF, Gros P, Torda AE, Berendsen HJ, van Schaik RC

During the last decade it has become possible to derive the spatial structure of small proteins in solution using multidimensional NMR spectroscopy measurements and interpreting the data in terms of a chemical atomic model. The NMR experiments generate a set of interproton distance constraints, which is subsequently used to generate spatial structures that satisfy the experimental data. Correspondingly, crystallographic least-squares and molecular dynamics refinement is routinely applied to obtain a protein structure that is compatible with the observed structure factor amplitudes. The quality of the structure obtained will depend on the number and quality of the experimental data and on the searching power of the refinement method and protocol. The potential energy annealing conformational search (PEACS) algorithm is shown to be an improvement over standard molecular dynamics search methods. The use of time-dependent distance or structure factor restraints in molecular dynamics refinement yields a much better representation of experimental information than the fixed, static restraints which have generally been used until now. Conventional structure refinement methods lead to a too static and rigid picture of a protein in solution or in the crystalline state.

PMID: 1814692 [PubMed - indexed for MEDLINE]



Source: PubMed
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