Name: Structure and Coordination Determination of Peptide-metal Complexes Using 1D and 2D 1H NMR (Video) | JoVE Journal
Uploaded: 2013-12-16T13:00:00.000+00:00
Duration: 14 min 44 s
Description: Learn NMR spectroscopy methods for determining peptide-metal complex structures using 1D and 2D 1H NMR techniques. This protocol enables structural analysis of copper-bound metallochaperone model peptides in oxygen-free environments.

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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>

<ol><li>Robinson, J. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Protein+epitope+mimetics+as+anti-infectives%5BTitle%5D)+AND+%22Curr.+Opin.+Chem.+Biol%22%5BJournal%5D)">Protein epitope mimetics as anti-infectives.</a> Curr. Opin. Chem. Biol. 15, 379-386 (2011).</li>
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<li>Rubino, J. T., Franz, K. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Coordination+chemistry+of+copper+proteins%3A+How+nature+handles+a+toxic+cargo+for+essential+function%5BTitle%5D)+AND+%22J.+Inorg.+Biochem%22%5BJournal%5D)">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. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Structural+basis+for+copper+transfer+by+the+metallochaperone+for+the+Menkes%2FWilson+disease+proteins%5BTitle%5D)+AND+%22Nat.+Struct.+Biol%22%5BJournal%5D)">Structural basis for copper transfer by the metallochaperone for the Menkes/Wilson disease proteins.</a> Nat. Struct. Biol. 7, 766-771 (2000).</li>
<li>Singleton, C., Hearnshaw, S., Zhou, L., Le Brun, N. E., Hemmings, A. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Mechanistic+insights+into+Cu%28I%29+cluster+transfer+between+the+chaperone+CopZ+and+its+cognate+Cu%28I%29-transporting+P-type+ATPase%2C+CopA%5BTitle%5D)+AND+%22Biochem.+J%22%5BJournal%5D)">Mechanistic insights into Cu(I) cluster transfer between the chaperone CopZ and its cognate Cu(I)-transporting P-type ATPase, CopA.</a> Biochem. J. 424, 347-356 (2009).</li>
<li>Hearnshaw, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((A+Tetranuclear+Cu%28I%29+Cluster+in+the+Metallochaperone+Protein+CopZ%5BTitle%5D)+AND+%22Biochem%22%5BJournal%5D)">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/pubmed?term=((The+MXCXXC+class+of+metallochaperone+proteins%3A+model+studies%5BTitle%5D)+AND+%22Chem.+Soc.+Rev%22%5BJournal%5D)">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/pubmed?term=((NMR+characterization+of+a+Cu%28I%29-bound+peptide+model+of+copper+metallochaperones%3A+Insights+on+the+role+of+methionine%5BTitle%5D)+AND+%22Chem.+Comm%22%5BJournal%5D)">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/pubmed?term=((Conformation+of+different+S-deoxo-Xaa%283%29-amaninamide+analogues+in+DMSO+solution+as+determined+by+NMR+spectroscopy.+Strong+CD+effects+induced+by+beta+I%2C+beta+II+conformational+change%5BTitle%5D)+AND+%22J.+Am.+Chem.+Soc%22%5BJournal%5D)">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/pubmed?term=((Structure-activity+relationship+of+the+ring+portion+in+backbone-cyclic+C-terminal+hexapeptide+analogs+of+substance+P+-+NMR+and+molecular+dynamics%5BTitle%5D)+AND+%22Int.+J.+Peptide+and+Protein+Res%22%5BJournal%5D)">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>Overview TopSpin NMR - Software for NMR Data Analysis and NMR Spectra Data Procession | Bruker Corporation [Internet]. , Bruker Corporation. Available from: 
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<li>Aue, W. P., Bartholdi, E., Ernst, R. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((2-Dimensionsl+spectroscopy-+application+to+nuclear+magnetic+resonance%5BTitle%5D)+AND+%22J.+Chem.+Phys%22%5BJournal%5D)">2-Dimensionsl spectroscopy- application to nuclear magnetic resonance.</a> J. Chem. Phys. 64, 2229-2246 (1976).</li>
<li>Bax, A., Davis, D. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((MLEV-17-based+two-dimensional+homonuclear+magnetization+transfer+spectroscopy%5BTitle%5D)+AND+%22J.+Magn.+Reson%22%5BJournal%5D)">MLEV-17-based two-dimensional homonuclear magnetization transfer spectroscopy.</a> J. Magn. Reson. 65, 355-360 (1985).</li>
<li>Kumar, A., Ernst, R. R., Wüthrich, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((A+two-dimensional+nuclear+overhauser+enhancement+%282D+NO%29+experiment+for+the+elucidation+of+complete+proton-proton+cross-relaxation+networks+in+biological+macromolecules%5BTitle%5D)+AND+%22Biochem.+Biophys.+Res.+Comm%22%5BJournal%5D)">A two-dimensional nuclear overhauser enhancement (2D NO) experiment for the elucidation of complete proton-proton cross-relaxation networks in biological macromolecules.</a> Biochem. Biophys. Res. Comm. 95, 1-6 (1980).</li>
<li>Bax, A., Davis, D. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Practical+aspects+of+two-dimensional+transverse+NOE+spectroscopy%5BTitle%5D)+AND+%22J.+Magn.+Reson%22%5BJournal%5D)">Practical aspects of two-dimensional transverse NOE spectroscopy.</a> J. Magn. Reson. 63, 207-213 (1985).</li>
<li>Williamson, M. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Chapter+3+Applications+of+the+NOE+in+Molecular+Biology%5BTitle%5D)+AND+%22Annu.+Reports+on+NMR+Spectroscopy%22%5BJournal%5D)">Chapter 3 Applications of the NOE in Molecular Biology.</a> Annu. Reports on NMR Spectroscopy. 65, 77-109 (2009).</li>
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<li>Wüthrich, K. <a target="_blank" href="http://scholar.google.com/scholar?hl=en&safe=off&q=author%3aW%C3%BCthrich%2C+K+%22NMR+of+proteins+and+nucleic+acids%22">NMR of proteins and nucleic acids</a>. , J. Wiley & Sons Inc. (1986).</li>
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<li>Pettersen, E. F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((UCSF+chimera+-+A+visualization+system+for+exploratory+research+and+analysis%5BTitle%5D)+AND+%22J.+Computational+Chem%22%5BJournal%5D)">UCSF chimera - A visualization system for exploratory research and analysis.</a> J. Computational Chem. 25, 1605-1612 (2004).</li>
<li>Pearlmen, D. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((AMBER%2C+a+package+of+computer+programs+for+applying+molecular+mechanics%2C+normal+mode+analysis%2C+molecular+dynamics+and+free+energy+calculations+to+simulate+the+structural+and+energetic+properties+of+molecules%5BTitle%5D)+AND+%22Comp.+Phys%22%5BJournal%5D)">AMBER, a package of computer programs for applying molecular mechanics, normal mode analysis, molecular dynamics and free energy calculations to simulate the structural and energetic properties of molecules.</a> Comp. Phys. 91, 1-41 (1995).</li>
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</ol>

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><tbody><tr><td>Avance DMX 600 MHz Spectrometer</td><td>Bruker</td><td></td><td></td></tr><tr><td>NMR sample tubes&amp;nbsp;</td><td>Wilmad</td><td>535-PP</td><td></td></tr><tr><td>Glove box</td><td>MBraun</td><td>LM05-019</td><td></td></tr><tr><td>Lyophilizer&amp;nbsp;&amp;nbsp;</td><td>VirTis</td><td>benchtopK</td><td></td></tr><tr><td>Peptide</td><td>BioChemia</td><td>Custom made</td><td>&gt;95% purity</td></tr><tr><td>Copper (1) chloride</td><td>Aldrich</td><td>224332</td><td></td></tr><tr><td>Hydrochloric acid</td><td>BioLab</td><td>231-595-7</td><td></td></tr><tr><td>Sodium hydroxide</td><td>Gadot</td><td>1310-73-2</td><td></td></tr><tr><td>d&lt;sub&gt;6&lt;/sub&gt;-Dimethylsulfoxide</td><td>Aldrich</td><td>236926</td><td></td></tr><tr><td>Deuterium oxide</td><td>Aldrich</td><td>151882</td><td></td></tr></tbody></table>

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

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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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.

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

The overall goal of this procedure is to determine the structure of a Metallo chaperone protein mimetic peptide complexed with copper. This is accomplished by first preparing the sample in an oxygen free environment. The second step is to acquire the nuclear magnetic resonance or NMR spectroscopy data showing interactions among hydrogen atoms.Next, the spatial interactions are mapped onto a linear peptide template. The final step is to find a representative low energy structure that fits the data. Ultimately, NMR derived structures are used to determine the mode of binding and to perform structural analysis on the copper bound complex.The main advantage of this technique over existing techniques such as x-ray crystallography, is that you can use it to look at weekly binding complexes and also at molecules and complexes that don't crystallize. Though this method can provide insight into copper binding proteins. It can also be applied to other systems such as other metal chaps to study how proteins enable safe delivery of essential, yet potentially toxic metal ions in the cell line environment.To begin prepare samples in an oxygen free environment to prevent the copper from oxidizing to prepare the APO sample dissolve approximately one to two milligrams of the peptide in 450 to 500 microliters of Deuterated NMR grade solvent for the copper reacted sample dissolve the same amount as the APO peptide with an EQU molar amount of metal salt in 450 to 500. Microliters of the NMR solvent filter each solution using a center glass filtration paper or any other technique that suits the compounds under investigation and does not absorb them. This is essential to remove any metallic particles, which will affect the homogeneity.Transfer the solutions to NMR tubes and close the samples in the tubes. Before leaving the glove box, take the samples out of the glove box and seal them. Record the one dimensional proton spectra of the APO and copper reacted samples in the NMR machine and compare.The APO peptide is flexible and shows an average of confirmations, but upon reacting with copper, the bound peptide amides have a more rigid structure. Therefore, the copper containing peptide spectrum should show a significant change in the chemical shift in the amide region, and the peaks may become resolved. Set up optimized, cozy tox, nosy or rosy NMR experiments under identical conditions as described in the text protocol and run in sequence.Run one dimensional experiments in between each experiment to make sure that the sample composition remains constant throughout data acquisition. After processing the data as discussed in the text protocol, prepare a set of cozy and to spectra overlaid on the noea and rosy spectrum. To assign all NOE peaks in the spectrum.Start with assigning peaks that overlap toxis signals in the fingerprint region. As this will facilitate subsequent peak assignment entries with the Sparky program record the assigned peaks translate H alpha to amide protein coupling values into dedal angles. Also translate peaks into distance constraints by integrating the peaks from within the program and translating them using an interaction of known distance.If the peaks overlap or automatic integration methods cannot be used, the peaks can be labeled as strong, medium, weak, or very weak by visual estimation, and these designations can be translated into distances up to 2.5, 3.5, 4.5, and 5.5 angstroms respectively. In import the distance constraints and dedal angles with the correct format for explore. Explore will search confirmational space to find structures that adhere to canonical chemical geometry.In addition to the experimentally found distance constraints to generate an ensemble in which none of these parameters are violated. This will constitute the starting ensemble. Perform the first structure determination run without using any constraints to the metal to find which residues participate in metal binding without any bias.Introduce the constraints gradually to facilitate identifying mistakes in assignment as well as NOE energy and simulated kneeling parameters as described in the text protocol before minimizing the structures using conjugate gradient energy minimization for 4, 000 iterations, create a final ensemble of usually 50 members performing introduction of constraints in an iterative fashion on the entire ensemble report the number of each type of NOE interaction found. Finally, create an ensemble of structures that adhere to canonical chemical geometry and the empiric NMR derived constraints Report. The total number of confirmations, the number of these that have violations of the NM Rived constraints and the RMSD of the entire ensemble, including both backbone and all heavy atom RMSD values.Analyze the low energy ensemble and determine which residue side chains are in correct proximity to each other to be able to bind the metal ion. Once these have been determined, repeat the analysis, including the copper binding data. In addition to the NMR derived distance constraints, now add metal binding constraints to the residues determined.Add appropriate parameters to describe the metal ion and its topology. Input the appropriate physical information such as mass bond lengths with other atoms, angles, and non bonding repulsion parameters into the parameter file. Add the binding information to the topology file.This information includes which bonds are formed and broken, and which formal charges are changed as a result of binding. Finally, acquire an ensemble of structures as before the solved ensemble represents the confirmational space adopted by the peptide. During the NMR measurement, import all confirmations of the structure to the Mal Mall program to create a starting ensemble.Examine the ensemble to determine the local stability of the molecule. Determine the backbone and side chain 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, determine which regions of the molecule show local stability by plotting the local RMSD as a function of sequence, overlay the ensemble along this region of the molecule and use this ensemble for further analysis. Choose low energy confirmations that adhere to the NMR derived constraints.These will form the low energy ensemble record and report the number of confirmations in the ensemble, the criteria for choosing them and the RMSD values. If the metal binding mode has not yet been determined, analyze the low energy ensemble and determine which residue side chains are incorrect. Proximity to each other to be able to bind the metal ion.Use KYMERA to determine intramolecular distances between atoms suspected for metal binding. Calculate the average distances in the ensemble once these have been determined. Repeat the analysis including the copper binding data.Examine the ensemble and determine local secondary structure within the molecule using the default search parameters of the MAL mall program. Next, import the ensemble into kymera. Secondary structures are held by hydrogen bonding and indicate stable regions of the molecule.Determine hydrogen binding using the kymera tool. Continue structural analysis as detailed in the text protocol. Then sum up all the structural findings to reveal how they reinforce each other To study copper binding protein models, the structure of the conserved binding sequence of a protein within the derived linear peptide was determined by solution state NMR, the amide region of the peptide from 6.7 to 8.5.PP M showed an expansion upon reaction with copper to 6.6 to 9.0 PP M.Line broadening due to slight copper oxidation is evident in the baseline. Shown here is an overlay of the fingerprint regions of Roy Toxi and cozy spectra of the copper bound peptide. The sample was stable with time and the spectra were well resolved and gave 81 NOE interactions that were acquired by a rosy experiment.Since the molecule gave near zero NOE interactions in the NO C experiment, the ensemble of the peptide derived for the reacted sample, but using no constraints to the metal gave 47 out of 50 non structures with an RMSD value of 1.44 and 2.07 angstroms on the backbone and heavy atoms respectively. Of these 13 low energy conformers were chosen for further analysis with RMSD values of 0.25 and 0.61 angstroms on the backbone and heavy atoms respectively. The local RMSD plot showed a region of stability between residues three and seven In addition to the rigid C terminal region, including a prolene residue, this region is found in a bend confirmation between residues four and seven in all confirmations.The bend confirmation is stabilized by hydrogen bonding between backbone donors and acceptors glycine five and three anine two, as well as cysteine six and cysteine three. This bend is also evident in cystine three and sine seven by the reduced coupling values in this region. The confirmations were superimposed over this region and analyzed for possible binding residues when considering cystine three, cystine six and methionine one as potential binding residues.The shortest sulfur to sulfur atom distance was that between the folate groups of cysteine three and cysteine six, copper binding was introduced and the calculation was repeated to give the ensemble used for analysis. The low energy ensemble of the copper bound peptide shows that the end terminal amine is proximate to the bound copper. Shown here is the electrostatic potential distribution isosurface with positive potential shown in blue and negative potential shown in red.The arginine residue extends from the backbone of the peptide forming a positive lobe of electrostatic potential, whereas the backbone carbon yields are arranged in a line forming a less prominent negative electrostatic potential Once mastered, a structural determination can be done in about a week of NMR time and another few days of workup in order to obtain an ensemble of confirmations that can be used for structural analysis. Following this procedure, other peptide mutans and different conditions can be analyzed in order to answer additional questions that address the conditions required for different degrees of binding and release of the copper ion.

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Learn NMR spectroscopy methods for determining peptide-metal complex structures using 1D and 2D 1H NMR techniques. This protocol enables structural analysis of copper-bound metallochaperone model peptides in oxygen-free environments.

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

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