NMR paper Sequential assignment of 2D-NMR spectra of proteins using genetic algorithms.

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[NMR paper] Sequential assignment of 2D-NMR spectra of proteins using genetic algorithms.

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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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08-21-2010, 11:53 PM

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Sequential assignment of 2D-NMR spectra of proteins using genetic algorithms.

Sequential assignment of 2D-NMR spectra of proteins using genetic algorithms.

Related Articles Sequential assignment of 2D-NMR spectra of proteins using genetic algorithms.

J Chem Inf Comput Sci. 1993 Mar-Apr;33(2):245-51

Authors: Wehrens R, Lucasius C, Buydens L, Kateman G

The application of genetic algorithms to the problem of the sequential assignment of two-dimensional protein NMR spectra is discussed. The problem is heavily underconstrained since in most cases more patterns are available than amino acid positions, and uncertainties may exist in the preliminary assignments. The results indicate that relatively large amounts of errors may be present in the input data for the genetic algorithm while useful results may still be obtained.

PMID: 8314929 [PubMed - indexed for MEDLINE]

Source: PubMed

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