NMR paper Mapping the population of protein conformational energy sub-States from NMR dipolar couplings.

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[NMR paper] Mapping the population of protein conformational energy sub-States from NMR dipolar couplings.

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NMR processing:

MDD

NMR assignment:

Backbone:

Side-chains:

NOEs:

Structure from NMR restraints:

Ab initio:

Fragment-based:

Rosetta-NMR (Robetta)

Template-based:

GeNMR

I-TASSER

Refinement:

Amber

Structure from chemical shifts:

Fragment-based:

Homology-based:

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:

NMR model quality:

NOEs, other restraints:

Chemical shifts:

RDCs:

Pseudocontact shifts:

Protein geomtery:

SAVES2 or SAVES4

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:

Isotope labeling:

Solid-state NMR:

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10-17-2013, 12:49 PM

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Mapping the population of protein conformational energy sub-States from NMR dipolar couplings.

From Mendeley Biomolecular NMR group:

Mapping the population of protein conformational energy sub-States from NMR dipolar couplings.

Angewandte Chemie (International ed. in English) (2013). Volume: 52, Issue: 11. Pages: 3181-5. Paul Guerry, Loïc Salmon, Luca Mollica, Jose-Luis Ortega Roldan, Phineus Markwick, Nico a J van Nuland, J Andrew McCammon, Martin Blackledge et al.

Molecular dynamics: A general method for the statistical mechanical description of conformational energy landscapes of proteins in solution is proposed. This method combines NMR residual dipolar couplings (RDCs), sampling of conformational space using accelerated molecular dynamics simulation, and ensemble selection using model-free ensemble interpretation of RDCs.

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