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NMR processing:
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Side-chains:
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NOEs:
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ASDP
Structure from NMR restraints:
Ab initio:
GeNMR
Cyana
XPLOR-NIH
ASDP
UNIO ATNOS-Candid
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Fragment-based:
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Template-based:
GeNMR
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Refinement:
Amber
Structure from chemical shifts:
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WeNMR CS-Rosetta
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Homology-based:
CS23D
Simshift
Torsion angles from chemical shifts:
Preditor
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Secondary structure from chemical shifts:
CSI (via RCI server)
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Flexibility from chemical shifts:
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Interactions from chemical shifts:
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Chemical shifts re-referencing:
Shiftcor
UNIO Shiftinspector
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NMR model quality:
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RDCs:
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Pseudocontact shifts:
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iCing
PSVS
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SAVES2 or SAVES4
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NMR spectrum prediction:
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Flexibility from structure:
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Methyl S2
B-factor
Molecular dynamics:
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Chemical shifts prediction:
From structure:
Shiftx2
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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 Simpler model gets to the point with proteins - Phys.Org


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Simpler model gets to the point with proteins
Phys.Org
Clementi said the data can come from any one or a combination of sources like Förster resonance energy transfer (FRET), mutagenesis or nuclear magnetic resonance. The computational framework takes advantage of Markov models to combine multiple ...



Simpler model gets to the point with proteins - Phys.Org
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