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NMR processing:
MDD
NMR assignment:
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MARS
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PINE
Side-chains:
UNIO ATNOS-Ascan
NOEs:
UNIO ATNOS-Candid
UNIO Candid
ASDP
Structure from NMR restraints:
Ab initio:
GeNMR
Cyana
XPLOR-NIH
ASDP
UNIO ATNOS-Candid
UNIO Candid
Fragment-based:
BMRB CS-Rosetta
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
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:
Shiftcor
UNIO Shiftinspector
LACS
CheckShift
RefDB
NMR model quality:
NOEs, other restraints:
PROSESS
PSVS
RPF scores
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Chemical shifts:
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CheShift2
Vasco
iCing
RDCs:
DC
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Pseudocontact shifts:
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Protein geomtery:
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PROSESS
What-If
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PSVS
MolProbity
SAVES2 or SAVES4
Vadar
Prosa
ProQ
MetaMQAPII
PSQS
Eval123D
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Ramachandran Plot
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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
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:
camLILA
ccSOL
Camfold
camGroEL
Zyggregator
Isotope labeling:
UPLABEL
Solid-state NMR:
sedNMR


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Default Synthesis and conformational analysis by 1H NMR and restrained molecular dynamics sim

Synthesis and conformational analysis by 1H NMR and restrained molecular dynamics simulations of the cyclic decapeptide [Ser-Tyr-Ser-Met-Glu-His-Phe-Arg-Trp-Gly]

Related Articles Synthesis and conformational analysis by 1H NMR and restrained molecular dynamics simulations of the cyclic decapeptide [Ser-Tyr-Ser-Met-Glu-His-Phe-Arg-Trp-Gly]

J Comput Aided Mol Des. 1996 Jun;10(3):213-32

Authors: Buono RA, Kucharczyk N, Neuenschwander M, Kemmink J, Hwang LY, Fauchère JL, Venanzi CA

The design of enzyme mimics with therapeutic and industrial applications has interested both experimental and computational chemists for several decades. Recent advances in the computational methodology of restrained molecular dynamics, used in conjunction with data obtained from two-dimensional 1H NMR spectroscopy, make it a promising method to study peptide and protein structure and function. Several issues, however, need to be addressed in order to assess the validity of this method for its explanatory and predictive value. Among the issues addressed in this study are: the accuracy and generizability of the GROMOS peptide molecular mechanics force field; the effect of inclusion of solvent on the simulations; and the effect of different types of restraining algorithms on the computational results. The decapeptide Ser-Tyr-Ser-Met-Glu-His-Phe-Arg-Trp-Gly, which corresponds to the sequence of ACTH1-10, has been synthesized, cyclized, and studied by two-dimensional 1H NMR spectroscopy. Restrained molecular dynamics (RMD) and time-averaged restrained molecular dynamics (TARMD) simulations were carried out on four different distance-geometry starting structures in order to determine and contrast the behavior of cyclic ACTH1-10 in vacuum and in solution. For the RMD simulations, the structures did not fit the NOE data well, even at high values of the restraining potential. The TARMD simulation method, however, was able to give structures that fit the NOE data at high values of the restraining potential. In both cases, inclusion of explicit solvent molecules in the simulation had little effect on the quality of the fit, although it was found to dampen the motion of the cyclic peptide. For both simulation techniques, the number and size of the NOE violations increased as the restraining potential approached zero. This is due, presumably, to inadequacies in the force field. Additional TARMD vacuum-phase simulations, run with a larger memory length or with a larger sampling size (16 additional distance-geometry structures), yielded no significantly different results. The computed data were then analyzed to help explain the sparse NOE data and poor chymotryptic activity of the cyclic peptide. Cyclic ACTH1-10, which contains the functional moieties of the catalytic triad of chymotrypsin, was evaluated as a potential mimic of chymotrypsin by measurement of the rate of hydrolysis of esters of L- and D-phenylalanine. The poor rate of hydrolysis is attributed to the flexibility of the decapeptide, the motion of the side chains, which result in the absence of long-range NOEs, the small size of the macrocycle relative to that of the substrate, and the inappropriate orientation of the Gly, His, and Ser residues. The results demonstrate the utility of this method in computer-aided molecular design of cyclic peptides and suggest structural modifications for future work based on a larger and more rigid peptide framework.

PMID: 8808738 [PubMed - indexed for MEDLINE]



Source: PubMed
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