We thank the Human Frontier Science Program (Young investigator grant (RGY)0068-2006) for financial support.

1. Sample Preparation
<ol>
	<li>Apo-sample: Dissolve approximately 1-2 mg of the peptide in 450-500 &#181;l&#160;of deuterated NMR grade solvent (the preferable solutions for biological samples are 10% D2O in water or d6-DMSO11-12 if the sample does not dissolve in water or reacts with it).</li>
	<li>Copper-reacted sample: Dissolve approximately 1-2 mg of the peptide with an equimolar amount of metal salt in 450-500 &#181;l&#160;of the NMR solvent.</li>
	<li>Filter the solution using a Sinter glass, filtration paper or any other technique that suits the compounds under investigation and does not adsorb them. This is essential to remove any metallic particles, which will affect the homogeneity.</li>
	<li>Transfer the solution to an NMR tube and close it. Make sure that the tube quality fits the magnet strength used (for more details see equipment table).</li>
	<li>If the sample is sensitive to oxygen, these steps must be done under an inert environment and the tube sealed to prevent oxidation.</li>
</ol>
2. NMR Data Collection and Processing13
<ol>
	<li>Record 1D&#160;1H spectra of the apo- and copper-reacted samples and compare. The copper-containing peptide spectrum should show a significant change of chemical shift in the amide region and the peaks became resolved since the apo-peptide is flexible and shows an average of conformations, but upon reacting with copper, the bound-peptide amides have a single structure (Figure 2).
	<ol>
		<li>If the spectrum is unchanged, the reaction is assumed to have failed.</li>
		<li>If the sample turns green, the copper will have oxidized in the atmosphere, which may change its binding properties.</li>
		<li>In both these cases, the sample will need to be remade.</li>
	</ol>
	</li>
	<li>Find optimal temperature conditions for the NMR measurements that give minimal overlap of the amide residues with narrow line-widths.</li>
	<li>Set up COSY14, TOCSY15 and NOESY16, or ROESY17 NMR experiments under identical conditions (temperature, pH, etc.) and run in sequence.
	<ol>
		<li>COSY (Figure 3) and TOCSY (Figure 4) experiments will detect through-bond interactions of adjacent and longer range neighboring proton-proton interactions, respectively. COSY spectrum gives information on HN-H&#945; correlations while TOCSY spectrum gives, in addition information on HN and other H aliphatic protons of correlated residues.</li>
		<li>NOESY and ROESY (Figure 5) experiments detect through-space proximity with no dependence on bonds to give structural information. The choice between the two is according to the effective size of the compound and the field strength. Some such combinations give theoretical zero signals (Figure 6) and a ROESY experiment will have to be run to detect NOE interactions10,18.</li>
		<li>If the sample is in water, the experiments need to have a component of water suppression. This is most efficiently accomplished using gradients19. In this case, it is advantageous to rerun the sample, once assigned, in pure D2O to obtain interactions to and among the H&#945; hydrogens.</li>
		<li>Optimize the duration of the TOCSY and NOESY or ROESY mixing times by running a number of short experiments to find maximal signal build-up with minimal loss to spin diffusion. Make sure that this is the linear region of the buildup curve. Values common for peptides at 600 MHz fields include mixing times of around 100 msec for TOCSY and 150 msec for NOESY or ROESY experiments.</li>
		<li>Run 1D experiments in between each experiment to make sure that the sample composition remains constant throughout data acquisition (Figure 7).</li>
	</ol>
	</li>
	<li>Process the spectra using appropriate apodization functions to obtain maximal resolution with minimal loss of signal strength, adding zero filling in the t1 dimension.
	<ol>
		<li>Further correct the baseline in the F2 then F1 dimension with a quadratic polynomial function.</li>
		<li>Calibrate the chemical shift of the spectra carefully according to the residual water or DMSO peaks in the respective solvents according to their shift from known standards (TMSP or TMS, respectively).</li>
	</ol>
	</li>
</ol>
3. Peak Assignment and Integration Using SPARKY20
<ol>
	<li>Prepare a set of COSY and TOCSY spectra overlaid on the NOESY or ROESY spectrum (Figure 8).</li>
	<li>Assign all NOE peaks in the spectrum according to the sequential assignment methodology developed by W&#252;thrich21.
	<ol>
		<li>Start with assigning peaks that overlap TOCSY signals in the fingerprint region, as this will facilitate subsequent peak assignment entries with the SPARKY program (Figure 9). Register the assignment chemical shift (Figure 10), and 3JHNH&#945; values (Figure 11).</li>
	</ol>
	</li>
	<li>Translate peaks into distance constraints and 3JHNH&#945; values into dihedral angles.
	<ol>
		<li>This can be done by integrating the peaks from within the program and translating them into distance constraints using an interaction of known distance (such as the distance between two protons of methylene group or aromatic hydrogen atoms of an aromatic amino acid).</li>
		<li>If the peaks overlap, and integration methods cannot be used, they can be labeled as strong-medium-weak-very weak by visual estimation, and these designations can be translated into distances up to 2.5, 3.5, 4.5, and 5.5 &#197;, respectively. This to be most effective in work with peptides.</li>
		<li>3JHNH&#945; values are indicative of dihedral angles according to the Karplus equation where most given coupling values can result from more than one dihedral angle. These can be indicative of secondary structure (helices or sheets), random coil or conformational averages thereof. Therefore, it is important to use the constraints carefully, or to use them as confirmation of conformational results.</li>
	</ol>
	</li>
</ol>
4. Molecular Mechanics Calculations to Generate Structure Ensemble using XPLOR22
<ol>
	<li>Import the distance constraints and dihedral angles with the correct format for XPLOR. (Figure 12,&#160;inter-residual constraints only). XPLOR will search conformational space to find structures that adhere to canonical geometric chemical constraints, such as bond lengths, angles, chirality, etc.&#160;in addition to the experimentally found distance constraints, to generate an ensemble in which none of the above parameters are violated. This will constitute the starting ensemble.</li>
	<li>The first structure determination run will be without using any constraints to the metal. This will show which residues participate in metal binding without any bias. Skip to step 4.4.</li>
	<li>In addition to the NMR-derived distance constraints, add metal binding constraints to the residues determined.
	<ol>
		<li>Add appropriate parameters to describe the metal ion and its topology.</li>
		<li>The appropriate physical information (mass, bond lengths with other atoms, angles, and nonbonding repulsion parameters) must be put into the parameter file.</li>
		<li>Add the binding information to the topology file: Which bonds are formed and broken&#160;and which formal charges are changed as a result of binding.</li>
	</ol>
	</li>
	<li>Create a small ensemble of usually 10 members.
	<ol>
		<li>Introduce the constraints gradually, starting with backbone-to-backbone interactions, then backbone-to-sidechain, then sidechain-to-sidechain interactions, and going from intra-residual, sequential to increasingly longer range interactions. This facilitates identifying mistakes in assignment.</li>
		<li>Introduce the NOE energy as a square-well potential with a constant force constant of 50 kcal/mol&#8226;&#197;2. Simulated annealing should be done with 1,500 3-fsec steps at 1,500 K and 3,000 1-fsec steps during cooling to 500 K. Finally, minimize the structures using conjugate gradient energy minimization for 4,000 iterations; these are variables that can be changed within XPLOR.</li>
	</ol>
	</li>
	<li>Create a final ensemble of usually 50 members. Perform steps from step 4.4 on the entire ensemble.
	<ol>
		<li>Report the number of each type of NOE interaction that were found, as shown in Figure 13.</li>
	</ol>
	</li>
	<li>Create an ensemble of structures that adhere to canonical chemical geometry and the empiric NMR-derived constraints.
	<ol>
		<li>Report the total number of conformations, the number of these that have violations of the NMR-derived constraints, and the RMSD of the entire ensemble,&#160;both backbone, and all heavy atom RMSD values.</li>
	</ol>
	</li>
</ol>
5. Structure Analysis
<ol>
	<li>The solved ensemble represents the conformational space adopted by the peptide during the NMR measurement. The local flexibility may change in different regions of the molecule and this can be ascribed to structural or functional reasons (the purpose of structural analysis is to determine the structural basis for the stability and mechanism of action).
	<ol>
		<li>Import all conformations of the structure to the MolMol program23 to create a starting ensemble (Figure 14).</li>
	</ol>
	</li>
	<li>Examine the ensemble to determine the local stability of the molecule.
	<ol>
		<li>Determine the backbone and sidechain RMSD values by selecting subsequent four-residue regions along the sequence and having the program calculate the RMSD to the lowest energy structure or the mean.</li>
		<li>Determine which regions of the molecule show local stability (Figure 15) by plotting the local RMSD as a function of sequence.</li>
		<li>Overlay the ensemble along this region of the molecule and use this ensemble for further analysis (Figure 16).</li>
	</ol>
	</li>
	<li>Choose low-energy conformations that adhere to the NMR-derived constraints (nonviolated). These will form the &#34;low energy ensemble&#34;.
	<ol>
		<li>Report the number of conformations in the ensemble, the criteria for choosing them and the RMSD values as defined in step &#8206;4.6.1.</li>
		<li>If the metal binding mode was already determined, continue to the next step. Otherwise: Analyze the low energy ensemble and determine which residue sidechains are in correct proximity of each other to be able to bind the metal ion. Once these have been determined, go back to step 3.3 and redo the analysis including the copper-binding data (Figure 17 for the ensemble and Figure 18 for the low energy conformer).</li>
	</ol>
	</li>
	<li>Examine the ensemble and determine local secondary structure within the molecule using the default search parameters of the MolMol program. Secondary structures are held by hydrogen-bonding and indicate stable regions of the molecule.
	<ol>
		<li>Determine the secondary structure of each conformer (Figure 19).
		<ol>
			<li>Create a table of the percentage of conformers of the ensemble that show each secondary structure.</li>
			<li>Determine whether the regions of secondary structure overlap the regions that were determined to be the stable regions by local-RMSD. This is often the case.</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>Determine distances and hydrogen bonding within the molecule.
	<ol>
		<li>Import the ensemble into Chimera24.</li>
		<li>Use Chimera to determine intramolecular distances between atoms suspected for metal binding. Calculate the average distances in the ensemble.</li>
		<li>Use Chimera to determine intramolecular hydrogen bonds in each conformer of the ensemble (Figure 20), using the default relaxed hydrogen-bond parameters (by 20%) of the program.</li>
		<li>Create a table of the percentage of conformers of the ensemble that show each hydrogen-bond. Hydrogen bonds that recur in a majority of the conformations indicate a stable bond that adds to the stability of the structure.</li>
	</ol>
	</li>
	<li>Determine electrostatic interactions within the molecule.
	<ol>
		<li>Identify interactions between charged sidechains.</li>
		<li>Create a table of the percentage of conformers of the ensemble that show each electrostatic interaction.</li>
	</ol>
	</li>
	<li>Calculate the electrostatic potential distribution using the Amber25 force field within the Delphi26 program.
	<ol>
		<li>Choose a single representative conformation from the ensemble on which to perform the electrostatic potential calculations.</li>
		<li>Derive electrostatic potential using the Poisson-Boltzman equation and a full Coulombic calculation. Required parameters include the ionic strength of the solution, the dielectric values of the solution (80 for water; 40 for DMSO); the internal peptide (usually around 5.0); the size of the grid (usually 65&#180;65&#180;65 points); and the minimal distance between the peptide and the edge of the grid (10 &#197;). The results are usually quite robust with respect to these values as the main result is governed by the peptide itself (Figure 21).</li>
		<li>Examine the electrostatic potential mapped onto the Van der Waals surface of the peptide (Figure 22).</li>
		<li>Examine the electrostatic potential iso-surfaces, which describe positions having the same potential. Find iso-surfaces that suggest biological relevance, such as extended positive or negative surfaces that might attract or repel other proteins or ligands, or distributions that indicate significance, such as amphipathic distribution or patches of differing properties (Figure 23).</li>
	</ol>
	</li>
	<li>Sum up all the structural findings to see how they reinforce each other.</li>
	<li>Repeat steps 4.3-5.7.4 where relevant.</li>
</ol>

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	<li>Robinson, J. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Protein+epitope+mimetics+as+anti-infectives.">Protein epitope mimetics as anti-infectives.</a> Curr. Opin. Chem. Biol. 15, 379-386 (2011).</li><li>Huffman, D. L., Function O'Halloran, T. V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=structure,+and+mechanism+of+intracellular+copper+trafficking+proteins.">structure, and mechanism of intracellular copper trafficking proteins.</a> Annu. Rev. Biochem. 70, 677-701 (2001).</li><li>Tapiero, H., Townsend, D. M., Tew, K. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Trace+elements+in+human+physiology+and+pathology.">Trace elements in human physiology and pathology.</a> Copper. Biomed., &amp; Pharmacotherapy. 57, 386-398 (2003).</li><li>Boal, A. K., Rosenzweig, A. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Structural+Biology+of+Copper+Trafficking.">Structural Biology of Copper Trafficking.</a> Chem. Rev. 109, 4760-4779 (2009).</li><li>Rubino, J. T., Franz, K. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Coordination+chemistry+of+copper+proteins:+How+nature+handles+a+toxic+cargo+for+essential+function.">Coordination chemistry of copper proteins: How nature handles a toxic cargo for essential function.</a> J. Inorg. Biochem. 107, 129-143 (2012).</li><li>Wernimont, A. K., Huffman, D. L., Lamb, A. L., O'Halloran, T. V., Rosenzweig, A. 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J. 424, 347-356 (2009).</li><li>Hearnshaw, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+Tetranuclear+Cu(I)+Cluster+in+the+Metallochaperone+Protein+CopZ.">A Tetranuclear Cu(I) Cluster in the Metallochaperone Protein CopZ.</a> Biochem. 48, 9324-9326 (2009).</li><li>Shoshan, M. S., Tshuva, E. Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+MXCXXC+class+of+metallochaperone+proteins:+model+studies.">The MXCXXC class of metallochaperone proteins: model studies.</a> Chem. Soc. Rev. 40, 5282-5292 (2011).</li><li>Shoshan, M. S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=NMR+characterization+of+a+Cu(I)-bound+peptide+model+of+copper+metallochaperones:+Insights+on+the+role+of+methionine.">NMR characterization of a Cu(I)-bound peptide model of copper metallochaperones: Insights on the role of methionine.</a> Chem. Comm. 47, 6407-6409 (2011).</li><li>Schmitt, W., Zanotti, G., Wieland, T., Kessler, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Conformation+of+different+S-deoxo-Xaa(3)-amaninamide+analogues+in+DMSO+solution+as+determined+by+NMR+spectroscopy.+Strong+CD+effects+induced+by+beta+I,+beta+II+conformational+change.">Conformation of different S-deoxo-Xaa(3)-amaninamide analogues in DMSO solution as determined by NMR spectroscopy. Strong CD effects induced by beta I, beta II conformational change.</a> J. Am. Chem. Soc. 118 (3), 4380-4387 (1996).</li><li>Behrens, S., Matha, B., Bitan, G., Gilon, C., Kessler, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Structure-activity+relationship+of+the+ring+portion+in+backbone-cyclic+C-terminal+hexapeptide+analogs+of+substance+P+-+NMR+and+molecular+dynamics.">Structure-activity relationship of the ring portion in backbone-cyclic C-terminal hexapeptide analogs of substance P - NMR and molecular dynamics.</a> Int. J. Peptide and Protein Res. 48, 569-579 (1996).</li><li>Aue, W. P., Bartholdi, E., Ernst, R. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=2-Dimensionsl+spectroscopy-+application+to+nuclear+magnetic+resonance.">2-Dimensionsl spectroscopy- application to nuclear magnetic resonance.</a> J. Chem. Phys. 64, 2229-2246 (1976).</li><li>Bax, A., Davis, D. 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Reports on NMR Spectroscopy. 65, 77-109 (2009).</li><li>Piotto, M., Saudek, V., Sklenar, V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Gradient-tailored+excitation+for+single-quantum+NMR-spectroscopy+of+aqueous+solutions.">Gradient-tailored excitation for single-quantum NMR-spectroscopy of aqueous solutions.</a> J. Biomol. NMR. 2, 661-665 (1992).</li><li>W&#252;thrich, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> NMR of proteins and nucleic acids. , (1986).</li><li>Nilges, M., Kuszewski, J., Br&#252;nger, A. T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Comp. aspects study biol. macromol. by NMR. , (1991).</li><li>Koradi, R., Billeter, M., W&#252;thrich, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MOLMOL:+A+program+for+display+and+analysis+of+macromolecular+structures.">MOLMOL: A program for display and analysis of macromolecular structures.</a> J. Molecular Graphics. 14, 51 (1996).</li><li>Pettersen, E. F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=UCSF+chimera+-+A+visualization+system+for+exploratory+research+and+analysis.">UCSF chimera - A visualization system for exploratory research and analysis.</a> J. Computational Chem. 25, 1605-1612 (2004).</li><li>Pearlmen, D. 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The authors declare they have no competing financial interests.

The contribution of structural information to understand binding mechanisms is well-accepted. Peptides are useful as models for protein binding and interactions; however they are not amenable to the main method for structure determination, X-ray crystallography. NMR is particularly useful for these systems, since the structures can be readily solved in solution. This is especially for the case of metallochaperone-mimetics that additionally require structure determination under an inert environment to prevent oxidation of...

Peptides are widely used as protein models, potential drug leads and therapeutic agents in their own right. However, their small size and high degree of flexibility often precludes structure determination by X-ray due to difficulties in crystallization.
Nuclear magnetic resonance (NMR) can be used to determine peptide structures and interactions. The method can give information regarding local and overall structure, binding and lower affinity interactions, and is applicable to difficult samples since it can be done in the solution state.
Copper transport in biological systems is achieved by intracellular copper metallochaperone proteins that specifically bind Cu (I) ions and deliver them to their target proteins through a series of protein-protein interactions, to protect the ions from oxidation and prevent the release of toxic copper2-5. The binding site is characterized by the conserved sequence, MXH/TCXanyXanyC, which has been shown both by NMR and crystallography to bind the Cu (I) by the soft thiolato ligands of the two cysteine residues, although an additional external ligand has also been proposed6-8. The structure-function relationship of these proteins has been a subject of intensive research9.
In the study presented here, a peptide model that includes the conserved sequence of copper metallochaperones was synthesized and reacted with Cu (I) under an inert environment. The presented protocol describes the steps of structure determination by NMR, including sample preparation, data collection, data processing, structure generation and structural analysis. The analysis was done in two steps: First structures were generated with no information regarding the mode of binding of the peptide to the copper ion. Once the binding mode was established empirically, these constraints were introduced to provide a high resolution structure. The mode of binding is the essential point in the model and was thus determined in an unbiased manner.
The NMR structural determination of model peptides is an extremely valuable technique that is often used by chemists and biologists. It may be applied relatively easily to different peptides under different conditions, and thus may shed light on relevant mechanisms10. Understanding the structure elucidation process provide a better understanding of the strengths and weaknesses of the proposed structures.

<table border="0" cellpadding="0" cellspacing="0">
	<colgroup>
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		<col />
		<col />
		<col />
	</colgroup>
	<tbody>
		<tr height="40">
			<td height="40" style="height:40px;width:167px;">Avance DMX 600 MHz Spectrometer</td>
			<td style="width:108px;">Bruker</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;width:167px;">NMR sample tubes&#160;</td>
			<td style="width:108px;">Wilmad</td>
			<td style="width:141px;">535-PP</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;width:167px;">Glove box</td>
			<td style="width:108px;">MBraun</td>
			<td style="width:141px;">LM05-019</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:167px;">Lyophilizer&#160;&#160;</td>
			<td style="width:108px;">VirTis</td>
			<td style="width:141px;">benchtopK</td>
			<td></td>
		</tr>
		<tr height="40">
			<td height="40" style="height:40px;width:136px;">Peptide</td>
			<td style="width:91px;">BioChemia</td>
			<td style="width:88px;">Custom made&#160;</td>
			<td style="width:87px;">&#62;95% purity</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;width:136px;">Copper (1) chloride</td>
			<td style="width:91px;">Aldrich</td>
			<td style="width:88px;">224332</td>
			<td style="width:87px;"></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;width:136px;">Hydrochloric acid</td>
			<td style="width:91px;">BioLab</td>
			<td style="width:88px;">231-595-7</td>
			<td style="width:87px;"></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;width:136px;">Sodium hydroxide</td>
			<td style="width:91px;">Gadot</td>
			<td style="width:88px;">1310-73-2</td>
			<td style="width:87px;"></td>
		</tr>
		<tr height="46">
			<td height="46" style="height:46px;width:136px;">d6-Dimethylsulfoxide</td>
			<td style="width:91px;">Aldrich</td>
			<td style="width:88px;">236926</td>
			<td style="width:87px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:136px;">Deuterium oxide</td>
			<td style="width:91px;">Aldrich</td>
			<td style="width:88px;">151882</td>
			<td style="width:87px;"></td>
		</tr>
	</tbody>
</table>

structure and coordination determination of peptide-metal complexes using 1d and 2d 1h nmr

Copper (I) binding by metallochaperone transport proteins prevents copper oxidation and release of the toxic ions that may participate in harmful redox reactions. The Cu (I) complex of the peptide model of a Cu (I) binding metallochaperone protein, which includes the sequence MTCSGCSRPG (underlined is conserved), was determined in solution under inert conditions by NMR spectroscopy.
NMR is a widely accepted technique for the determination of solution structures of proteins and peptides. Due to difficulty in crystallization to provide single crystals suitable for X-ray crystallography, the NMR technique is extremely valuable, especially as it provides information on the solution state rather than the solid state. Herein we describe all steps that are required for full three-dimensional structure determinations by NMR. The protocol includes sample preparation in an NMR tube, 1D and 2D data collection and processing, peak assignment and integration, molecular mechanics calculations, and structure analysis. Importantly, the analysis was first conducted without any preset metal-ligand bonds, to assure a reliable structure determination in an unbiased manner.

As part of an ongoing study of copper-binding protein models, the structure of the conserved sequence MT/HCXXC within the linear peptide MTCSGCSRPG was determined by solution state NMR. The peptide was reacted with CuCl under inert environment and the pH was measured as ~3.0 by a universal stick. The amide region of the peptide showed an expansion upon reaction with copper, from 6.7-8.5 to 6.6-9.0 ppm (Figure 2). Line broadening due to slight copper oxidation is evident in the baseline.
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Watch this Scientific Journal Video about Structure and Coordination Determination of Peptide-metal Complexes Using 1D and 2D 1H NMR at JoVE.com

Structure and Coordination Determination of Peptide-metal Complexes Using 1D and 2D 1H NMR

The NMR-solution structure of a metallochaperone model peptide with Cu (I) was determined, and a detailed protocol from sample preparation and 1D and 2D data collection to a three-dimensional structure is described.

Structure and Coordination Determination of Peptide-metal Complexes Using 1D and 2D 1H NMR

Copper (I) binding by metallochaperone transport proteins prevents copper oxidation and release of the toxic ions that may participate in harmful redox ...

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9.5K vues.  The Hebrew University of Jerusalem. The NMR-solution structure of a metallochaperone model peptide with Cu (I) was determined, and a detailed protocol from sample preparation and 1D and 2D data collection to a three-dimensional structure is described.

Vidéo: Structure and Coordination Determination of Peptide-metal Complexes Using 1D and 2D 1H NMR

The Synthesis, Characterization and Reactivity of a Series of Ruthenium N-triphosPh Complexes

Herein we report the synthesis of a tridentate phosphine ligand N(CH2PPh2)3 (N-triphosPh) (1) via a phosphorus based Mannich reaction of the hydroxylmethylene phosphine precursor with ammonia in methanol under a nitrogen atmosphere. The N-triphosPh ligand precipitates from the solution after approximately 1 hr of reflux and can be isolated analytically pure via simple cannula filtration procedure under nitrogen. Reaction of the N-triphosPh ligand with [Ru3(CO)12] under reflux affords a deep red solution that show evolution of CO gas on ligand complexation. Orange crystals of the complex [Ru(CO)2{N(CH2PPh2)3}-&#954;3P] (2) were isolated on cooling to RT. The 31P{1H} NMR spectrum showed a characteristic single peak at lower frequency compared to the free ligand. Reaction of a toluene solution of complex 2 with oxygen resulted in the instantaneous precipitation of the carbonate complex [Ru(CO3)(CO){N(CH2PPh2)3}-&#954;3P] (3) as an air stable orange solid. Subsequent hydrogenation of 3 under 15 bar of hydrogen in a high-pressure reactor gave the dihydride complex [RuH2(CO){N(CH2PPh2)3}-&#954;3P] (4), which was fully characterized by X-ray crystallography and NMR spectroscopy. Complexes 3 and 4 are potentially useful catalyst precursors for a range of hydrogenation reactions, including biomass-derived products such as levulinic acid (LA). Complex 4 was found to cleanly react with LA in the presence of the proton source additive NH4PF6 to give [Ru(CO){N(CH2PPh2)3}-&#954;3P{CH3CO(CH2)2CO2H}-&#954;2O](PF6) (6).

The Synthesis, Characterization and Reactivity of a Series of Ruthenium N-triphosPh Complexes

Ruthenium phosphine complexes are widely used for homogeneous catalytic reactions such as hydrogenations. The synthesis of a series of novel tridentate ruthenium complexes bearing the N-triphos ligand N(CH2PPh2)3 is reported. Additionally, the stoichiometric reaction of a dihydride Ru&#8211;N-triphos complex with levulinic acid is described.

La synthèse, la caractérisation et la réactivité d&#39;une série de ruthénium<em&gt; N</em&gt; -triphos<sup&gt; Ph</sup&gt; Complexes

Herein we report the synthesis of a tridentate phosphine ligand N(CH2PPh2)3 (N-triphosPh) (1) via a phosphorus based Mannich reaction of the ...

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From Constructs to Crystals &#8211; Towards Structure Determination of &#946;-barrel Outer Membrane Proteins

Membrane proteins serve important functions in cells such as nutrient transport, motility, signaling, survival and virulence, yet constitute only ~1% percent of known structures. There are two types of membrane proteins, &#945;-helical and &#946;-barrel. While &#945;-helical membrane proteins can be found in nearly all cellular membranes, &#946;-barrel membrane proteins can only be found in the outer membranes of mitochondria, chloroplasts, and Gram-negative bacteria. One common bottleneck in structural studies of membrane proteins in general is getting enough pure sample for analysis. In hopes of assisting those interested in solving the structure of their favorite &#946;-barrel outer membrane protein (OMP), general protocols are presented for the production of target &#946;-barrel OMPs at levels useful for structure determination by either X-ray crystallography and/or NMR spectroscopy. Here, we outline construct design for both native expression and for expression into inclusion bodies, purification using an affinity tag, and crystallization using detergent screening, bicelle, and lipidic cubic phase techniques. These protocols have been tested and found to work for most OMPs from Gram-negative bacteria; however, there are some targets, particularly for mitochondria and chloroplasts that may require other methods for expression and purification. As such, the methods here should be applicable for most projects that involve OMPs from Gram-negative bacteria, yet the expression levels and amount of purified sample will vary depending on the target OMP.

From Constructs to Crystals &amp;#8211; Towards Structure Determination of &amp;#946;-barrel Outer Membrane Proteins

&#946;-barrel outer membrane proteins (OMPs) serve many functions within the outer membranes of Gram-negative bacteria, mitochondria, and chloroplasts. Here, we hope to alleviate a known bottleneck in structural studies by presenting protocols for the production of &#946;-barrel OMPs in sufficient quantities for structure determination by X-ray crystallography or NMR spectroscopy.

De Constructs à cristaux - Vers Structure Détermination de β-cylindre externe protéines membranaires

Membrane proteins serve important functions in cells such as nutrient transport, motility, signaling, survival and virulence, yet constitute only ~1% ...

X-ray Powder Diffraction in Conservation Science: Towards Routine Crystal Structure Determination of Corrosion Products on Heritage Art Objects

The crystal structure determination and refinement process of corrosion products on historic art objects using laboratory high-resolution X-ray powder diffraction (XRPD) is presented in detail via two case studies.
The first material under investigation was sodium copper formate hydroxide oxide hydrate, Cu4Na4O(HCOO)8(OH)2&#8729;4H2O (sample 1) which forms on soda glass/copper alloy composite historic objects (e.g., enamels) in museum collections, exposed to formaldehyde and formic acid emitted from wooden storage cabinets, adhesives, etc. This degradation phenomenon has recently been characterized as &#34;glass induced metal corrosion&#34;.
For the second case study, thecotrichite, Ca3(CH3COO)3Cl(NO3)2&#8729;6H2O (sample 2), was chosen, which is an efflorescent salt forming needlelike crystallites on tiles and limestone objects which are stored in wooden cabinets and display cases. In this case, the wood acts as source for acetic acid which reacts with soluble chloride and nitrate salts from the artifact or its environment.
The knowledge of the geometrical structure helps conservation science to better understand production and decay reactions and to allow for full quantitative analysis in the frequent case of mixtures.

Modern high resolution X-ray powder diffraction (XRPD) in the laboratory is used as an efficient tool to determine crystal structures of long-known corrosion products on historic objects.

X-ray Powder Diffraction en science de la conservation: Vers Routine structure cristalline Détermination des produits de corrosion sur l&#39;art du patrimoine Objets

The crystal structure determination and refinement process of corrosion products on historic art objects using laboratory high-resolution X-ray powder ...

Application and Methodology of the Non-destructive 19F Time-domain NMR Technique to Measure the Content in Fluorine-containing Drug Products

Here, we describe a protocol developed by our group that uses low-field fluorine-19 (19F) time-domain (TD) nuclear magnetic resonance (NMR) to measure the average content of fluorinated drugs in their formulated drug product forms: tablets or capsules. This method is specific to fluorinated drugs because it detects only the content of fluorine, avoiding interference from the excipients that lack fluorine. The advantages of measuring the active content of fluorinated drugs using low-field 19F TD-NMR versus high-field 19F solid-state (SS) NMR are the simplicity of the method; the low cost; and the non-destructive nature of the technique, with all samples recoverable in intact forms (e.g., powders, tablets, and capsules), making this technique affordable for any laboratory.
We have tested the method with three fluorinated drug products available on the market - cinacalcet, lansoprazole, and ciprofloxacin - with doses ranging from 15 to 500 mg. The results of the analyses, measured by low-field 19F TD-NMR, supported the reported label claims for the average drug content.
Based on the simplicity and reproducibility of the analysis, we envision this methodology being implemented in any laboratory, including manufacturing plants, as a process analytical technology (PAT) tool in the pharmaceutical industry.

Application and Methodology of the Non-destructive 19F Time-domain NMR Technique to Measure the Content in Fluorine-containing Drug Products

A simple and non-destructive technique that measures the average content of drug substances in formulated drug products containing fluorine using low-field fluorine-19 (19F) time-domain (TD) nuclear magnetic resonance (NMR) is presented here. The technique can be applied to the development and manufacturing of drugs in the pharmaceutical industry.

Application et la méthodologie de la Technique de RMN Non destructifs 19F domaine temporel pour mesurer le contenu dans les produits contenant du fluor

Here, we describe a protocol developed by our group that uses low-field fluorine-19 (19F) time-domain (TD) nuclear magnetic resonance (NMR) to measure the ...

Determination of Thermodynamic Properties of Alkaline Earth-liquid Metal Alloys Using the Electromotive Force Technique

A novel electrochemical cell based on a CaF2 solid-state electrolyte has been developed to measure the electromotive force (emf) of binary alkaline earth-liquid metal alloys as functions of both composition and temperature in order to acquire thermodynamic data. The cell consists of a chemically stable solid-state CaF2-AF2 electrolyte (where A is the alkaline-earth element such as Ca, Sr, or Ba), with binary A-B alloy (where B is the liquid metal such as Bi or Sb) working electrodes, and a pure A metal reference electrode. Emf data are collected over a temperature range of 723 K to 1,123 K in 25 K increments for multiple alloy compositions per experiment and the results are analyzed to yield activity values, phase transition temperatures, and partial molar entropies/enthalpies for each composition.

This protocol describes the measurement of the electromotive force of alkaline-earth elements in liquid metal alloys at high temperatures (723-1,123 K) to determine their thermodynamic properties, including activity, partial molar entropy, partial molar enthalpy, and phase transition temperatures, over a wide composition range.

Détermination des propriétés thermodynamiques des alliages de métaux alcalino-terreux-liquide en utilisant la Technique de Force électromotrice

A novel electrochemical cell based on a CaF2 solid-state electrolyte has been developed to measure the electromotive force (emf) of binary alkaline ...

Fabricating High-viscosity Droplets using Microfluidic Capillary Device with Phase-inversion Co-flow Structure

The generation of monodisperse droplets with high viscosity has always been a challenge in droplet microfluidics. Here, we demonstrate a phase-inversion co-flow device to generate uniform high-viscosity droplets in a low-viscosity fluid. The microfluidic capillary device has a common co-flow structure with its exit connecting to a wider tube. Elongated droplets of the low-viscosity fluid are first encapsulated by the high-viscosity fluid in the co-flow structure. As the elongated low-viscosity droplets flow through the exit, which is treated to be wetted by the low-viscosity fluid, phase inversion is then induced by the adhesion of the low viscosity droplets to the tip of the exit, which results in the subsequent inverse encapsulation of the high-viscosity fluid. The size of the resultant high-viscosity droplets can be adjusted by changing the flow rate ratio of the low-viscosity fluid to the high-viscosity fluid. We demonstrate several typical examples of the generation of high-viscosity droplets with a viscosity up to 11.9 Pas, such as glycerol, honey, starch, and polymer solution. The method provides a simple and straightforward approach to generate monodisperse high-viscosity droplets, which may be used in a variety of droplet-based applications, such as materials synthesis, drug delivery, cell assay, bioengineering, and food engineering.

A phase-inversion co-flow device is demonstrated to generate monodisperse high-viscosity droplets above 1 Pas, which is difficult to realize in droplet microfluidics.

Fabrication des gouttelettes de haute viscosité à l’aide de dispositif microfluidique à capillaire avec Structure de flux de co-inversion de Phase

The generation of monodisperse droplets with high viscosity has always been a challenge in droplet microfluidics. Here, we demonstrate a phase-inversion ...

Synthesis and Structure Determination of &#181;-Conotoxin PIIIA Isomers with Different Disulfide Connectivities

Peptides with a high number of cysteines are usually influenced regarding the three-dimensional structure by their disulfide connectivity. It is thus highly important to avoid undesired disulfide bond formation during peptide synthesis, because it may result in a completely different peptide structure, and consequently altered bioactivity. However, the correct formation of multiple disulfide bonds in a peptide is difficult to obtain by using standard self-folding methods such as conventional buffer oxidation protocols, because several disulfide connectivities can be formed. This protocol represents an advanced strategy required for the targeted synthesis of multiple disulfide-bridged peptides which cannot be synthesized via buffer oxidation in high quality and quantity. The study demonstrates the application of a distinct protecting group strategy for the synthesis of all possible 3-disulfide-bonded peptide isomers of &#181;-conotoxin PIIIA in a targeted way. The peptides are prepared by Fmoc-based solid phase peptide synthesis using a protecting group strategy for defined disulfide bond formation. The respective pairs of cysteines are protected with trityl (Trt), acetamidomethyl (Acm), and tert-butyl (tBu) protecting groups to make sure that during every oxidation step only the required cysteines are deprotected and linked. In addition to the targeted synthesis, a combination of several analytical methods is used to clarify the correct folding and generation of the desired peptide structures. The comparison of the different 3-disulfide-bonded isomers indicates the importance of accurate determination and knowledge of the disulfide connectivity for the calculation of the three-dimensional structure and for interpretation of the biological activity of the peptide isomers. The analytical characterization includes the exact disulfide bond elucidation via tandem mass spectrometry (MS/MS) analysis which is performed with partially reduced and alkylated derivatives of the intact peptide isomer produced by an adapted protocol. Furthermore, the peptide structures are determined using 2D nuclear magnetic resonance (NMR) experiments and the knowledge obtained from MS/MS analysis.

Synthesis and Structure Determination of &amp;#181;-Conotoxin PIIIA Isomers with Different Disulfide Connectivities

Cysteine-rich peptides fold into distinct three-dimensional structures depending on their disulfide connectivity. Targeted synthesis of individual disulfide isomers is required when buffer oxidation does not lead to the desired disulfide connectivity. The protocol deals with the selective synthesis of 3-disulfide-bonded peptides and their structural analysis using NMR and MS/MS studies.

Synthèse et détermination de Structure des isomères PIIIA µ-conotoxine avec disulfure différentes connectivités

Peptides with a high number of cysteines are usually influenced regarding the three-dimensional structure by their disulfide connectivity. It is thus ...

Stable DNA Motifs, 1D and 2D Nanostructures Constructed from Small Circular DNA Molecules

This article presents a detailed protocol for synthesis of small circular DNA molecules, annealing of circular DNA motifs, and construction of 1D and 2D DNA nanostructures. Over decades, the rapid development of DNA nanotechnology is attributed to the use of linear DNAs as the source materials. For example, the DAO (double crossover, antiparallel, odd half-turns) tile is well-known as a building block for construction of 2D DNA lattices; the core structure of DAO is made from two linear single-stranded (ss) oligonucleotides, like two ropes making a right hand granny&#160;knot. Herein, a new type of DNA tiles called cDAO (coupled DAO) are built using a small circular ss-DNA of c64nt or c84nt (circular 64 or 84 nucleotides) as the scaffold strand and several linear ss-DNAs as the staple strands. Perfect 1D and 2D nanostructures are assembled from cDAO tiles: infinite nanowires, nanospirals, nanotubes, nanoribbons; and finite nano-rectangles. Detailed protocols are described: 1) preparation by T4 ligase and purification by denaturing PAGE (polyacrylamide gel electrophoresis) of small circular oligonucleotides, 2) annealing of stable circular tiles, followed by native PAGE analysis, 3) assembling of infinite 1D nanowires, nanorings, nanospirals, infinite 2D lattices of nanotubes and nanoribbons, and finite 2D nano-rectangles, followed by AFM (Atomic Force Microscopy) imaging. The method is simple, robust, and affordable for most labs.

This article presents a detailed protocol for T4 ligation and denaturing PAGE purification of small circular DNA molecules, annealing and native PAGE analysis of circular tiles, assembling and AFM imaging of 1D and 2D DNA nanostructures, as well as agarose gel electrophoresis and centrifugation purification of finite DNA nanostructures.

Motifs d’ADN stable, 1D et 2D Nanostructures construit à partir de molécules d’ADN circulaire petit

This article presents a detailed protocol for synthesis of small circular DNA molecules, annealing of circular DNA motifs, and construction of 1D and 2D ...

Microwave-Assisted Preparation of 1-Aryl-1H-pyrazole-5-amines

A synthetic process for the preparation of a variety of 1-aryl-1H-pyrazole-5-amines was developed. The microwave-mediated nature of this method makes it efficient in both time and resources and utilizes water as the solvent. 3-Aminocrotononitrile or an appropriate &#945;-cyanoketone is combined with an aryl hydrazine and dissolved in 1 M HCl. The mixture is then heated in a microwave reactor at 150 &#176;C, typically for 10-15 min. The product can be readily obtained by basifying the solution with 10% NaOH and isolating the desired compound with a simple vacuum filtration. The use of water as a solvent in this reaction lends to its ease and utility in production, and this method is easily reproducible with a variety of functional groups. Typical isolated yields range from 70-90%, and reactions can be performed on the milligram to gram scale with little to no change in observed yields. Some of the applications of these molecules and their derivatives include pesticides, anti-malarials, and chemotherapeutics, among many others.

Microwave-Assisted Preparation of 1-Aryl-1H-pyrazole-5-amines

1-Aryl-1H-pyrazole-5-amines are prepared from aryl hydrazines combined with either 3-aminocrotononitrile or an &#945;-cyanoketone in a 1 M HCl solution using a microwave reactor. Most reactions are done in 10-15 minutes and pure product can be obtained via vacuum filtration with typical isolated yields of 70-90%.

Préparation assistée par micro-ondes de 1-Aryl-1H-pyrazole-5-amines

A synthetic process for the preparation of a variety of 1-aryl-1H-pyrazole-5-amines was developed. The microwave-mediated nature of this method makes it ...

Quantitative 31P NMR Analysis of Lignins and Tannins

The development of sustainable biorefinery products is confronted, among others, with the challenge of lignin and tannin valorization. These abundant, renewable aromatic biopolymers have not been widely exploited due to their inherent structural complexity and high degrees of variability and species diversity. The lack of a defined primary structure for these polyphenols is further compounded with complex chemical alterations induced during processing, eventually imparting a large variety of structural features of extreme significance for any further utilization efforts.
Consequently, a protocol for the rapid, simple, and unequivocal identification and quantification of the various functional groups present in natural polyphenols, is a fundamental prerequisite for understanding and accordingly tailor their reactivity and eventual utility.
Quantitative 31P NMR offers the opportunity to rapidly and reliably identify unsubstituted, o-mono substituted, and o-disubstituted phenols, aliphatic OHs, and carboxylic acid moieties in lignins and tannins with broad application potential.
The methodology consists of an in situ quantitative lignin or tannin labeling procedure using a suitable 31P containing probe, followed by the acquisition of a quantitative 31P NMR spectrum in the presence of an internal standard. The high natural abundance of the 31P nucleus allows for small amounts of the sample (~30 mg) and short NMR acquisition times (~30-120 min) with well-resolved 31P signals that are highly dependent on the surrounding chemical environment of the labeled OH groups.

Quantitative 31P NMR Analysis of Lignins and Tannins

31P NMR is a powerful tool for the structural elucidation of polyphenols. This fast, easy, precise, quantitative, and highly reproducible analytical procedure, that allows for the quantification and differentiation of the different types of hydroxy, phenolic, and carboxylic groups in lignins and tannins has now become a routine analytical tool.

Analyse RMN quantitative 31P des lignines et des tanins

The development of sustainable biorefinery products is confronted, among others, with the challenge of lignin and tannin valorization. These abundant, ...