NMR paper NMR Spectroscopic Approach Reveals Metabolic Diversity of Human Blood Plasma Associated with Protein-Drug Interaction.

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[NMR paper] NMR Spectroscopic Approach Reveals Metabolic Diversity of Human Blood Plasma Associated with Protein-Drug Interaction.

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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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08-21-2013, 08:49 PM

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NMR Spectroscopic Approach Reveals Metabolic Diversity of Human Blood Plasma Associated with Protein-Drug Interaction.

NMR Spectroscopic Approach Reveals Metabolic Diversity of Human Blood Plasma Associated with Protein-Drug Interaction.

NMR Spectroscopic Approach Reveals Metabolic Diversity of Human Blood Plasma Associated with Protein-Drug Interaction.

Anal Chem. 2013 Aug 19;

Authors: Du Y, Lan W, Ji Z, Zhang X, Jiang B, Zhou X, Li C, Liu M

Abstract
Although blood plasma has been used to diagnose diseases and to evaluate physiological conditions, it is not easy to establish a global normal concentration range for the targeting components in the plasma due to the inherent metabolic diversity. We showed here that NMR spectroscopy coupled with principal component analysis (PCA) may provide a useful method for quantitatively characterizing metabolic diversity of human blood plasma. We analyzed 70 human blood plasma samples with and without addition of ibuprofen. By defining the PC score values as diversity index (Idiv) and the drug induced PC score value change as interaction index (Idist), we find that the two indexes are highly correlated (P

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