MERA: a webserver for evaluating backbone torsion angle distributions in dynamic and disordered proteins from NMR data

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MERA: a webserver for evaluating backbone torsion angle distributions in dynamic and disordered proteins from NMR data

Webservers

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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07-28-2015, 04:51 PM

nmrlearner

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MERA: a webserver for evaluating backbone torsion angle distributions in dynamic and disordered proteins from NMR data

MERA: a webserver for evaluating backbone torsion angle distributions in dynamic and disordered proteins from NMR data

Abstract

MERA (Maximum Entropy Ramachandran map Analysis from NMR data) is a new webserver that generates residue-by-residue Ramachandran map distributions for disordered proteins or disordered regions in proteins on the basis of experimental NMR parameters. As input data, the program currently utilizes up to 12 different parameters. These include three different types of short-range NOEs, three types of backbone chemical shifts (15N, 13CÎ±, and 13Câ?²), six types of J couplings (3JHNHÎ±, 3JCâ?²Câ?², 3JCâ?²HÎ±, 1JHÎ±CÎ±, 2JCÎ±N and 1JCÎ±N), as well as the 15N-relaxation derived J(0) spectral density. The Ramachandran map distributions are reported in terms of populations of their 15Â°Â*Ã?Â*15Â° voxels, and an adjustable maximum entropy weight factor is available to ensure that the obtained distributions will not deviate more from a newly derived coil library distribution than required to account for the experimental data. MERA output includes the agreement between each input parameter and its distribution-derived value. As an application, we demonstrate performance of the program for several residues in the intrinsically disordered protein Î±-synuclein, as well as for several static and dynamic residues in the folded protein GB3.

Source: Journal of Biomolecular NMR

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