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NMR processing:
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MARS
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PINE
Side-chains:
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NOEs:
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UNIO Candid
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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Rosetta-NMR (Robetta)
Template-based:
GeNMR
I-TASSER
Refinement:
Amber
Structure from chemical shifts:
Fragment-based:
WeNMR CS-Rosetta
BMRB CS-Rosetta
Homology-based:
CS23D
Simshift
Torsion angles from chemical shifts:
Preditor
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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:
Shiftcor
UNIO Shiftinspector
LACS
CheckShift
RefDB
NMR model quality:
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Chemical shifts:
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iCing
RDCs:
DC
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Pseudocontact shifts:
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Protein geomtery:
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What-If
iCing
PSVS
MolProbity
SAVES2 or SAVES4
Vadar
Prosa
ProQ
MetaMQAPII
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STAN
Ramachandran Plot
Rampage
ERRAT
Verify_3D
Harmony
Quality Control Check
NMR spectrum prediction:
FANDAS
MestReS
V-NMR
Flexibility from structure:
Backbone S2
Methyl S2
B-factor
Molecular dynamics:
Gromacs
Amber
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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:
camLILA
ccSOL
Camfold
camGroEL
Zyggregator
Isotope labeling:
UPLABEL
Solid-state NMR:
sedNMR


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Old 02-21-2018, 12:45 AM
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Default HTS by NMR for the Identification of Potent and Selective Inhibitors of Metalloenzymes.

HTS by NMR for the Identification of Potent and Selective Inhibitors of Metalloenzymes.

Related Articles HTS by NMR for the Identification of Potent and Selective Inhibitors of Metalloenzymes.

ACS Med Chem Lett. 2018 Feb 08;9(2):137-142

Authors: Baggio C, Cerofolini L, Fragai M, Luchinat C, Pellecchia M

Abstract
We have recently proposed a novel drug discovery approach based on biophysical screening of focused positional scanning libraries in which each element of the library contained a common binding moiety for the given target or class of targets. In this Letter, we report on the implementation of this approach to target metal containing proteins. In our implementation, we first derived a focused positional scanning combinatorial library of peptide mimetics (of approximately 100,000 compounds) in which each element of the library contained the metal-chelating moiety hydroxamic acid at the C-terminal. Screening of this library by nuclear magnetic resonance spectroscopy in solution allowed the identification of a novel and selective compound series targeting MMP-12. The data supported that our general approach, perhaps applied using other metal chelating agents or other initial binding fragments, may result very effective in deriving novel and selective agents against metalloenzyme.


PMID: 29456802 [PubMed]



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