R. W. H. V was supported by the McGill Natural Sciences and Engineering Research Council of Canada (NSERC) Training Program in Bionanomachines. A. K. M. and P. E. J. were supported by NSERC grants 327028-09 (A. K. M) and 238562 (P. E. J.).

1. Sample Preparation
<ol>
	<li>Purify the desired biomolecule13. 
	NOTE: This protocol uses purchased cocaine-binding DNA aptamer MN4 after exchanging against 2 M NaCl three times followed by three rounds of deionized water using a centrifugal filter with a 3 kDa molecular weight cut-off membrane.</li>
	<li>Synthesize and purify, or purchase the desired thermolabile ligand13. 
	NOTE: MN4 binds the thermolabile ligand cocaine. MN4 also binds quinine, which is used as a negative control for ligand thermolability at these experimental temperatures.</li>
	<li>Prepare buffers for dialysis of the purified biomolecule and dissolution of ligands (20 mM sodium phosphate and 140 mM NaCl buffer, pH 7.4, for MN4 and the ligands used here).</li>
	<li>Dialyze the biomolecule against at least 2 L of buffer using dialysis tubing with 0.5 - 1.0 kDa cut-off.</li>
	<li>Filter the final buffer (referred to as working buffer) through a 0.2 &#181;m filter that has been thoroughly equilibrated with buffer.</li>
	<li>Weigh out the desired masses of the ligands and dissolve them in filtered working buffer. If the desired ligand concentrations require masses that are too small to accurately weigh, make a concentrated ligand stock solution (10x for example). 
	NOTE: It is crucial that all DSC experiments utilize the same working buffer for the sample and ligand, i.e., never perform an experiment where the ligand is dissolved in a different batch of working buffer than the biomolecule as this will cause buffer mismatch artifacts in the data.</li>
	<li>Filter the biomolecule stock solution through a 0.2 &#181;m filter that has been thoroughly equilibrated with working buffer.</li>
	<li>Determine the biomolecule concentration by absorbance measurements (260 nm for nucleic acids like MN4 and 280 nm for proteins).</li>
	<li>Store the prepared biomolecule and ligand in a 4 &#176;C refrigerator (suitable for MN4 and the ligands used here), or at -20 or -80 &#176;C if the biomolecule and ligands tolerate freezing and long-term storage is required. Degas the buffer, biomolecule, and ligand solutions in a table top degasser (see Table of Materials) prior to loading into the DSC. 
	NOTE: Degassing helps to prevent bubble formation in the DSC at higher temperatures. Bubbles cause signal artifacts that obscure DSC peak shapes and baselines.</li>
</ol>
2. DSC Preparation
<ol>
	<li>Unscrew the pressure handle from the DSC (see Table of Materials).</li>
	<li>Run silicon tubing from the working buffer and attach it to the front flange (metal opening) of the reference capillary.</li>
	<li>Create a bridge between the reference and sample capillaries by connecting the rear reference flange to the front sample flange.</li>
	<li>Attach a piece of silicon tubing to the rear sample flange that runs to a waste flask with a vacuum line attached.</li>
	<li>Turn on the vacuum line to flush the DSC with 200 mL of working buffer.</li>
	<li>Load the reference capillary of the DSC with working buffer. Attach roughly 3 - 5 cm sections of silicon tubing to the reference capillary flanges.</li>
	<li>Insert a 1 mL pipette tip into the rear flange&#39;s silicon tubing. Draw 0.8 mL of working buffer with a pipette and insert the pipette tip with buffer into the front reference flange&#39;s silicon tubing.</li>
	<li>Gently press the pipette plunger down to pass the working buffer through the front silicon tubing into the reference capillary and up into the rear flange&#39;s attached pipette tip. Press down the pipette plunger until the working buffer level reaches just above the front silicon tubing, then release the pipette plunger until the working buffer level reaches just above the rear silicon tubing.
	<ol>
		<li>Repeat passing the working buffer back and forth to purge the volume in the reference capillary of bubbles. 
		NOTE: Usually, 10 passes of the solution back and forth are sufficient to clear any bubbles.</li>
	</ol>
	</li>
	<li>Cap the rear pipette tip with the thumb and gently pull up on the rear pipette tip and front pipette to remove them from the reference flanges with the silicon tubing attached.</li>
	<li>Load the sample capillary with working buffer as in steps 2.6 - 2.9. Place a black plastic cap on the rear reference and sample flanges, leaving the front flanges uncovered.</li>
	<li>Attach the pressure handle.</li>
	<li>Open the DSC software (see Table of Materials) and pressurize the instrument by clicking the red up arrow at the top of the interface once the power reading has stabilized; the DSC power is indicated in a box at the top right of the interface along with the instrument temperature and pressure reading. 
	NOTE: Monitor the power reading as the DSC pressurizes. Changes in power of more than ~ 10 &#181;W indicate bubble formation in the capillaries, which can cause artifacts in the data. The solutions must be removed and degassed further before continuing.</li>
	<li>Equilibrate the DSC with working buffer by performing a forward and reverse scan. In the &#34;Experimental Method&#34; tab on the left side of the screen, ensure that the &#34;Scanning&#34; option is selected to run the DSC in temperature scanning mode. 
	NOTE: Experimental parameters are the temperature scanning range, scan rate, low and high temperature equilibration time, and number of scans.
	<ol>
		<li>In the &#34;Temperature Parameters&#34; inset under the &#34;Experimental Method&#34; tab, click the button for &#34;Heating&#34;. Enter 1 and 100 &#176;C for the lower and upper experimental temperatures, 1 &#176;C/min for the scan rate, and 60 s for the equilibration period.</li>
		<li>Click the &#34;Add Series&#34; button under the input field for the equilibration period. Enter 2 into the &#34;Steps to add&#34; field in the popup window (for one heating and one cooling scan) and check the &#34;Alternate Heating/Cooling&#34; box. Click &#34;OK&#34;; the added scans appear in the lower portion of the interface. Check that the parameters for each scan are as desired.</li>
		<li>Start the experiment by clicking the green &#34;play&#34; button at the top of the interface. Navigate to the desired folder and input a file name for saving the experiment in the popup window. View the experiment progress by clicking the &#34;Data&#34; tab to the right of the &#34;Experiment Method&#34; tab.</li>
	</ol>
	</li>
</ol>
3. Collecting Thermolabile Ligand DSC Datasets
NOTE: The minimal procedure consists of five experiments: buffer reference experiments with and without ligand (used for baseline subtraction, see Discussion), sample experiments with the free biomolecule, the ligand-bound biomolecule, and the ligand-bound biomolecule with a longer high temperature equilibration period.
<ol>
	<li>Run reference experiments for baseline subtraction of the sample data. Reload the DSC with working buffer in both capillaries and collect multiple forward and reverse scans over a suitable temperature range at 1 &#176;C min-1 with an upper (high temperature) equilibration time of 120 s.
	<ol>
		<li>Delete the previous buffer equilibration scans from the lower portion of the interface by highlighting each individually and clicking the red X to the middle right of the interface. Add the new scans by clicking the &#34;Add Series&#34; button, entering 20 in the field for &#34;Steps to add&#34;, and checking the &#34;Alternate Heating/Cooling&#34; box. Click OK and run the experiment by clicking the green play button as above.</li>
		<li>Repeat steps 3.1 - 3.1.1 with working buffer containing the desired concentration of ligand in both capillaries to obtain the reference experiments for the ligand (collect two separate experiments using 120 s and 600 s high temperature equilibration times respectively, to be used in acquiring the rate constant for thermolabile ligand conversion). 
		NOTE: The scan rate used here ensures that the biomolecule in subsequent experiments is at thermal equilibrium in the forward and reverse scans (see Discussion). Scan rates &#60; 0.1 - 0.2 &#176;C min-1 lead to noisy thermograms and are not applicable in DSC experiments. The temperatures should extend from well below the melting temperature of the free biomolecule to well above the melting temperature of ligand-saturated biomolecule (~ 20 - 80 &#176;C for MN4). Verify reproducibility of the scans (for example, 10 forward and 10 reverse scans for 20 total is sufficient).</li>
		<li>If using multiple ligands (such as cocaine and quinine), flush the DSC with 200 mL of working buffer (repeat from&#160;step 2.5) between runs in order to remove ligand from the capillaries and prevent cross-contamination. 
		NOTE: It is helpful to perform a replicate experiment on the free biomolecule after a ligand-bound run in order to check if the previous ligand adsorbs strongly to the capillary walls and is not adequately removed with buffer flushing. If the thermograms for the free biomolecule appear to be shifted to a larger magnitude and higher denaturation temperature after the ligand-bound experiment, it is likely that the previous ligand is still present in the calorimeter after flushing. Remove the adsorbed ligand by incubating the capillaries with 20% Contrad-70 for 1 h at 60 &#176;C with the plastic caps and pressure handle off. In the DSC software, change the experimental mode to &#34;Isothermal&#34; under the Experimental Method tab. Choose 3,600 s for the duration and 60 &#176;C for the isothermal temperature, with zero entered for the equilibration time. Click &#34;Add to Experimental Method&#34;. The isothermal experiment appears in the lower part of the screen. After completion, flush the instrument with 2 L deionized water and repeat from step 2.5.</li>
	</ol>
	</li>
	<li>Run sample experiments using the same DSC loading procedure and experimental parameters as the reference scans. For the free biomolecule data set, ensure that the reference capillary contains the working buffer while the sample capillary contains the free biomolecule at the desired concentration in working buffer.
	<ol>
		<li>For the ligand-bound experiments, ensure that the ligand is in the working buffer in the reference capillary, and the biomolecule plus ligand are in working buffer in the sample capillary. Flush the system between additions of different ligands as in step 2.5.</li>
	</ol>
	</li>
	<li>Perform one additional experiment with the biomolecule bound to the thermolabile ligand where the high temperature equilibration period is increased to 600 s and all other experimental parameters are the same as step 3.2.1. 
	NOTE: The duration of the high temperature equilibration period for the second ligand-bound experiment is simply chosen to ensure that the ligand is more rapidly depleted than the short equilibration time experiment. If the ligand-bound peaks from the first experiment decay slowly as a function of scan number (e.g., the differences in successive peak maxima are &#8804; 0.5 &#176;C), estimate 10- to 20-fold increases in the high temperature equilibration period in order to adequately deplete the ligand during the second experiment. The accurate calculation of the rate constant for ligand conversion requires that the second experiment has swifter depletion of the ligand relative to the first. The ligand concentrations extracted from the global analysis of the two experiments will be similar and therefore unusable if the ligand depletion is not sufficiently accelerated in the second experiment.</li>
</ol>
4. Data Processing
<ol>
	<li>Open the DSC experiment files in the DSC data analysis software (see Table of Materials) and export the raw power data as spreadsheets.</li>
	<li>Import the spreadsheets containing the raw power data into software for data fitting.</li>
	<li>Baseline subtract the sample data by subtracting the buffer power data from the free and ligand-bound biomolecule experiments. 
	NOTE: For the thermolabile ligand experiment, the concentration of initial ligand is decreasing with each scan. Therefore, it is ideal to subtract the buffer scan 1 from sample scan 1, and so on. We have found that the buffer scans with cocaine do not change appreciably as the ligand conversion proceeds and therefore a single thermolabile ligand buffer scan can be used to subtract all of the thermolabile ligand-bound data.</li>
	<li>Convert the baseline-subtracted sample power data to heat capacity. 
	NOTE: The conversion requires the biomolecule&#39;s partial specific volume, which can be estimated14,15,16. The equation for converting power to heat capacity has been described previously17.</li>
</ol>
5. Data Analysis
<ol>
	<li>Globally fit the short equilibration time thermolabile ligand-bound heat capacity dataset with a single set of baseline, ligand concentration, folding, and ligand binding parameters as described previously4.</li>
	<li>Repeat the global fit for the long equilibration time dataset in order to calculate the rate constant for thermolabile ligand conversion as described previously4.</li>
</ol>

<ol>
	<li>Bruylants, G., Wouters, J., Michaux, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Differential+scanning+calorimetry+in+life+science:+thermodynamics,+stability,+molecular+recognition+and+application+in+drug+design.">Differential scanning calorimetry in life science: thermodynamics, stability, molecular recognition and application in drug design.</a> Curr Med Chem. 12 (17), 2011-2020 (2005).</li><li>Privalov, P. L., Dragan, A. I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Microcalorimetry+of+biological+macromolecules.">Microcalorimetry of biological macromolecules.</a> Biophys Chem. 126 (1-3), 16-24 (2007).</li><li>Brandts, J. F., Lin, L. N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Study+of+strong+to+ultratight+protein+interactions+using+differential+scanning+calorimetry.">Study of strong to ultratight protein interactions using differential scanning calorimetry.</a> Biochemistry. 29 (29), 6927-6940 (1990).</li><li>Harkness, R. W., Slavkovic, S., Johnson, P. E., Mittermaier, A. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Rapid+characterization+of+folding+and+binding+interactions+with+thermolabile+ligands+by+DSC.">Rapid characterization of folding and binding interactions with thermolabile ligands by DSC.</a> Chem Commun. 52 (92), 13471-13474 (2016).</li><li>Garbett, N. C., Chaires, J. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Thermodynamic+studies+for+drug+design+and+screening.">Thermodynamic studies for drug design and screening.</a> Expert Opin Drug Dis. 7 (4), 299-314 (2012).</li><li>Holdgate, G. A., Ward, W. H. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Measurements+of+binding+thermodynamics+in+drug+discovery.">Measurements of binding thermodynamics in drug discovery.</a> Drug Discov Today. 10 (22), 1543-1550 (2005).</li><li>Plotnikov, V., 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=An+autosampling+differential+scanning+calorimeter+instrument+for+studying+molecular+interactions.">An autosampling differential scanning calorimeter instrument for studying molecular interactions.</a> Assay Drug Dev Technol. 1 (1), 83-90 (2002).</li><li>Schon, A., Lam, S. Y., Freire, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Thermodynamics-based+drug+design:+strategies+for+inhibiting+protein-protein+interactions.">Thermodynamics-based drug design: strategies for inhibiting protein-protein interactions.</a> Future Med Chem. 3 (9), 1129-1137 (2011).</li><li>Peri&#225;nez Parraga, L., G-L, A., Gam&#243;n Runnenberg, I., Seco Melantuche, R., Delgado S&#225;nchez, O., Puigvent&#243;s Latorre, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Thermolabile+Drugs.+Operating+Procedure+In+the+Event+of+Cold+Chain+Failure.">Thermolabile Drugs. Operating Procedure In the Event of Cold Chain Failure.</a> Farmacia Hospitalaria. 35 (4), 1-28 (2011).</li><li>Murray, J. B., Alshora, H. I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Stability+of+Cocaine+in+Aqueous-Solution.">Stability of Cocaine in Aqueous-Solution.</a> J Clin Pharmacy. 3 (1), 1-6 (1978).</li><li>Waterman, K. C., 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=Hydrolysis+in+pharmaceutical+formulations.">Hydrolysis in pharmaceutical formulations.</a> Pharm. Dev. Technol. 7 (2), 113-146 (2002).</li><li>Mergny, J. L., Lacroix, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Analysis+of+thermal+melting+curves.">Analysis of thermal melting curves.</a> Oligonucleotides. 13 (6), 515-537 (2003).</li><li>Neves, M. A., Reinstein, O., Johnson, P. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Defining+a+stem+length-dependent+binding+mechanism+for+the+cocaine-binding+aptamer.+A+combined+NMR+and+calorimetry+study.">Defining a stem length-dependent binding mechanism for the cocaine-binding aptamer. A combined NMR and calorimetry study.</a> Biochemistry. 49 (39), 8478-8487 (2010).</li><li>Bonifacio, G. F., Brown, T., Conn, G. L., Lane, A. N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comparison+of+the+electrophoretic+and+hydrodynamic+properties+of+DNA+and+RNA+oligonucleotide+duplexes.">Comparison of the electrophoretic and hydrodynamic properties of DNA and RNA oligonucleotide duplexes.</a> Biophys J. 73 (3), 1532-1538 (1997).</li><li>Durchschlag, H., Hinz, H. -. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Chapter+3.">Chapter 3.</a> Thermodynamic Data for Biochemistry and Biotechnology. , 45-128 (1986).</li><li>Hellman, L. M., Rodgers, D. W., Fried, M. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Phenomenological+partial-specific+volumes+for+G-quadruplex+DNAs.">Phenomenological partial-specific volumes for G-quadruplex DNAs.</a> Eur Biophys J Biophy. 39 (3), 389-396 (2010).</li><li>Farber, P., Darmawan, H., Sprules, T., Mittermaier, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Analyzing+Protein+Folding+Cooperativity+by+Differential+Scanning+Calorimetry+and+NMR+Spectroscopy.">Analyzing Protein Folding Cooperativity by Differential Scanning Calorimetry and NMR Spectroscopy.</a> J Am Chem Soc. 132 (17), 6214-6222 (2010).</li><li>Reinstein, O., 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=Quinine+binding+by+the+cocaine-binding+aptamer.+Thermodynamic+and+hydrodynamic+analysis+of+high-affinity+binding+of+an+off-target+ligand.">Quinine binding by the cocaine-binding aptamer. Thermodynamic and hydrodynamic analysis of high-affinity binding of an off-target ligand.</a> Biochemistry. 52 (48), 8652-8662 (2013).</li><li>Tellinghuisen, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Statistical+error+propagation.">Statistical error propagation.</a> J Phys Chem. A. 105 (15), 3917-3921 (2001).</li><li>Drobnak, I., Vesnaver, G., Lah, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Model-based+thermodynamic+analysis+of+reversible+unfolding+processes.">Model-based thermodynamic analysis of reversible unfolding processes.</a> J Phys Chem B. 114 (26), 8713-8722 (2010).</li></ol>

The authors declare no conflicts of interest.

Modifications and troubleshooting
The details of the global fitting analysis used in Figure 1 and Figure 2 have been described previously4. Here, we outline practical aspects of performing and analyzing DSC binding experiments with thermolabile ligands. Note that a DSC baseline obtained for the thermolabile ligand alone is subtracted from the ligand + biomolecule dataset, effectively cancelling out the heat released or absorbed by the thermal conversion process itself. The standard thermolabile ligand global fitting analysis (Figure 1 and Figure 2) assumes that the system is at thermodynamic equilibrium throughout the temperature scan and that the thermolabile ligand concentration is constant throughout each thermogram, decreasing exclusively during the high temperature equilibration period. We have previously shown that this assumption applies to cocaine-bound MN4 and is expected to hold for any thermolabile ligand/biomolecule system with kinetics similar to these.
There are, however, some situations in which the system cannot be assumed to be at thermodynamic equilibrium and/or the concentration of ligand cannot be considered constant throughout a single scan. These include i) when the ligand thermally converts rapidly relative to the temperature scan rate, ii) when the biomolecule undergoes irreversible aggregation at high temperature, iii) when the folding/unfolding rates are slow compared to the scan rate, and iv) when the ligand association/dissociation rates are slow compared to the scan rate. In these cases, the system is under kinetic rather than thermodynamic control and the analysis given in reference 4 cannot strictly be applied. Data may be simulated quantitatively following Figure 3, as described in the Supplementary File 1. In principle, these kinetics-based calculations could be used to fit non-equilibrium DSC data, potentially yielding both kinetic and thermodynamic data, however this analysis is beyond the scope of this paper. Instead, we present some representative simulated DSC data to assist the reader in identifying non-equilibrium situations.
An ideal example of thermodynamic control is shown in Figure 4a, b. DSC thermograms of the free biomolecule are superimposable (Figure 4a) and scans with the thermolabile ligand do not show hysteresis, such that the melting temperature observed on the up-scan matches the folding temperature of the previous down-scan (Figure 4b). When the thermolabile ligand converts rapidly compared to the scan rate, large distortions appear in the thermogram and the thermodynamic equations do not account for the peak shape, as shown in Figure 4c, d. This can be alleviated somewhat by increasing the scan rate. When the biomolecule aggregates in a temperature-dependent manner, DSC traces for the free biomolecule show successive decreases in magnitude (Figure 4e), while addition of the thermolabile ligand produces a pattern of decreasing thermal upshifts similar to the ideal case, but scaled by the decreasing biomolecule concentration (Figure 4f). When folding/unfolding kinetics are slow compared to the scan rate, hysteresis is apparent in DSC traces of the free biomolecule such that the apparent denaturation temperature on the up-scan is higher than the apparent renaturation temperature on the down-scan (Figure 4g). Addition of a thermolabile ligand leads to the familiar pattern of decreasing thermal upshifts, particularly for the up-scans (Figure 4h). Finally, systems with rapid folding and slow binding produce hysteresis-free DSC thermograms for the free biomolecule (Figure 4i), however data with the thermolabile ligand show hysteresis where the apparent melting temperature of the up-scan is higher than the apparent folding temperature of the previous down-scan (Figure 4j). Nevertheless, the typical pattern of decreasing thermal upshifts are apparent in both up-scans and down-scans. Non-equilibrium behavior in the case of slow folding or binding kinetics can be alleviated somewhat by decreasing the scan rate, although this runs the risk of non-negligible ligand thermal conversion occurring throughout the scan. In practice, the scan rate and upper equilibration temperature can be adjusted manually to obtain data resembling Figure 4a, b.
Limitations of the technique
Our thermodynamic analysis for DSC binding experiments with thermolabile ligands requires that the folding and binding processes are relatively rapid and that thermolabile ligand conversion is slow prior to the high temperature portion of each scan. When the lifetime of the folded and/or bound state is greater than about 30 s (koff, ku &#60; 0.03 s-1), hysteresis becomes discernable in scans performed at 1 &#176;C min-1. Additionally, when the ligand conversion rate constant is above approximately kc = 10-4 s-1 before the denaturation transition, there can be significant depletion of the ligand during the course of a single scan. Application of our analysis is also inappropriate when irreversible aggregation occurs. In these cases, more advanced modelling could be applied to the data. No affinity information is available if ligand conversion is so rapid that it reaches completion prior to the first denaturation transition.
Significance with respect to existing methods
Our method for the first time allows DSC to be used to measure the binding thermodynamics of high affinity, thermolabile ligands. By performing a global simultaneous analysis of all scans, thermodynamic parameters are extracted with high accuracy20. An additional benefit is that the full dataset can be collected in as little as one experiment if the thermal conversion product has no affinity for the free biomolecule. In contrast, producing a typical experimental DSC series for a non-thermolabile ligand requires ~ 7-10 total experiments.
Future applications
This approach has direct applications to characterizing tight, thermolabile inhibitors in drug discovery campaigns. Several therapeutic compounds such as antibiotics and benzodiazepines are known to be thermolabile, undergoing rapid hydrolysis at or near physiological pH and temperatures of ~ 60-70 &#176;C11. This DSC method is well positioned to identify and characterize many more. As well, modification of the fitting protocol to account for systems under kinetic rather than thermodynamic control, as discussed above, has the potential to open the door to many more systems of biological relevance.
Critical steps within the protocol
One of the most important experimental procedures to consider is dialysis or exchange of the biomolecule and ligand into identical working buffer solutions (protocol steps 1.3-1.6). Buffer mismatch between the ligand and biomolecule solutions can lead to large artifacts in the baseline and sample scans which completely obscure the relevant folding data. Additionally, it is essential that the power reading stabilizes before the DSC is pressurized so that it can be monitored during pressurization (protocol step 2.3). If the power reading changes by more than ~ 10 &#181;W during pressurization, bubbles have likely formed in the capillaries and can cause large artifacts in the data. In this case, the solutions need to be degassed more thoroughly.
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/55959/55959fig3.jpg" /> 
Figure 3. Biomolecular Folding, Binding to a Thermolabile Ligand, and Irreversible Aggregation. The thermolabile ligand (L) converts to product (X) with a rate constant kc. X has no affinity for the biomolecule. The bound state (B) of the biomolecule exchanges with the free folded state (F) with rate constants koff and kon. F exchanges with the unfolded state (U) with rate constants ku and kf. U irreversibly converts to the aggregated state (A) with the rate constant kagg. <a href="//cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55959/55959fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/55959/55959fig4.jpg" /> 
Figure 4. Computer Simulation of Equilibrium and Kinetically-controlled DSC Experiments in the Absence and Presence of a Thermolabile Ligand. (a) Equilibrium biomolecular folding. (b) Equilibrium folding, thermolabile ligand binding, and slow thermolabile ligand conversion. (c) Equilibrium biomolecular folding. (d) Equilibrium folding, thermolabile ligand binding, and fast thermolabile ligand conversion. (e) Equilibrium biomolecular folding and slow irreversible aggregation. (f) Equilibrium folding, binding, slow thermolabile ligand conversion, and slow irreversible aggregation. (g) Slow biomolecular folding. (h) Slow folding, equilibrium binding, and slow thermolabile ligand conversion. (i) Equilibrium biomolecular folding. (j) Equilibrium folding, slow thermolabile ligand binding, and slow thermolabile ligand conversion. In all panels, the first and last simulated scans are dark red and dark blue, respectively. Panels that show only light and dark blue thermograms indicate that all simulated scans overlay, and only the last two are visible in the plot. DSC experiments were simulated with 20 scans (10 melting and 10 annealing) at 1 &#176;C min-1 scan rate, with a temperature range of 0-80 &#176;C. Certain panels display narrower temperature ranges to allow better visualization of the simulation trends. The biomolecule and ligand concentrations in the simulations were 200 &#181;M and 10 mM, respectively. Each experiment was simulated with a 600 s equilibration time at 0 &#176;C before scanning and a 60 s equilibration time between each of the subsequent scans. Arrhenius parameters for equilibrium binding and folding were Aon = 5 x 10-1 M-1 s-1, Aoff = 1 x 1019 s-1, Eaon = -20 kJ mol-1, Eaoff = 120 kJ mol-1, Afold = 1 x 10-14 s-1, Aunfold = 5 x 1018, Eafold = -80 kJ mol-1, and Eaunfold = 120 kJ mol-1. Arrhenius parameters for kinetically-controlled binding and folding were Aon = 5 x 10-3 M-1 s-1, Aoff = 1 x 1016 s-1, Eaon = -20 kJ mol-1, Eaoff = 120 kJ mol-1, Afold = 1 x 10-16 s-1, Aunfold = 5 x 1016, Eafold = -80 kJ mol-1, and Eaunfold = 120 kJ mol-1. Arrhenius parameters for slow and rapid thermolabile ligand conversion were Aslow = 7.509 x 1010 s-1, Easlow = 94.65 kJ mol-1, and Afast = 1 s-1, Eafast = 10 kJ mol-1. Arrhenius parameters for slow irreversible aggregation were Aagg. = 5 x 107 s-1 and Eaagg. = 80 kJ mol-1. Excess heat capacities were calculated with &#916;HUF (unfolding), &#916;HBF (binding), and &#916;HAF (aggregating) = 200, -140, and 50 kJ mol-1, respectively. The theoretical description of kinetically-controlled DSC experiments with thermolabile ligands and script for performing these simulations (and the necessary parameters) are available in Supplementary File 1. <a href="//cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55959/55959fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Differential scanning calorimetry (DSC) is a powerful method for quantitating biomolecular binding and folding interactions1,2,3. The strengths of DSC include its ability to elucidate binding and folding mechanisms, and to yield the corresponding thermodynamic parameters2,3. Furthermore, DSC can be performed in solution under near-physiological conditions and does not require labeling of the biomolecule or ligand, e.g., with fluorophores, spin-labels or nuclear isotopes4. The instrument scans in temperature, measuring the amount of heat required to denature the biomolecule in the presence and absence of ligand. The resulting thermograms are used to extract the thermodynamic parameters governing the ligand binding and folding processes. The information provided by DSC or other thermodynamic techniques is critical to guiding the design of drugs targeting biomolecules1,5,6,7,8. However, the repeated scanning to high temperatures (~ 60 - 100 &#176;C) can be problematic. For example, many pharmaceutically important compounds undergo rearrangement or decomposition upon sustained exposure to high temperatures9,10,11, i.e., they are thermolabile. Examination of binding interactions by DSC typically requires multiple forward and reverse scans in order to verify the reproducibility of the thermogram for thermodynamic analyses12. Thermal conversion of an initial ligand to a secondary form with altered binding characteristics leads to pronounced differences in the shape and position of successive thermograms, since the concentration of the initial ligand decreases with each scan while the thermal conversion products accumulate. These datasets are not amenable to traditional analyses.
We have recently developed a global fitting method for thermolabile ligand DSC datasets that yields the complete set of thermodynamic parameters governing the biomolecular folding and binding interactions from a single ligand-bound experiment referenced to the requisite thermogram for the free biomolecule4. The analysis reduces the experimental time and sample required by ~ 10-fold compared to standard DSC approaches. We have accounted for ligand thermal conversion by assuming this happens during the high temperature portion of each scan where the thermogram does not depend on ligand concentration. Therefore, the ligand concentration is a constant within the portion of the thermogram that is used to extract thermodynamic parameters. We additionally demonstrated how the rate constant for ligand thermal conversion can be obtained by performing one supplementary experiment with a longer high temperature equilibration period. For systems where ligand thermal conversion is less temperature-dependent (i.e., occurring appreciably at all temperatures), the analysis can be modified to include variable ligand concentrations. Here we demonstrate this procedure for the DNA aptamer MN4 in the presence of the thermolabile ligand cocaine, which rapidly converts to benzoylecgonine at high temperatures (&#62;60 &#176;C). Quinine is used as a negative control for ligand thermolability since it does not undergo conversion at these experimental temperatures and also binds to MN4. We describe the acquisition of thermolabile ligand DSC datasets and their analysis yielding thermodynamic and kinetic parameters of the folding, binding, and ligand conversion processes.

<table>
	<tbody>
		<tr>
			<td>Sodium chloride</td>
			<td>Chem Impex</td>
			<td>#00829</td>
			<td></td>
		</tr>
		<tr>
			<td>Sodium phosphate monobasic dihydrate</td>
			<td>Sigma Aldrich</td>
			<td>71502</td>
			<td></td>
		</tr>
		<tr>
			<td>Sodium phosphate dibasic</td>
			<td>Sigma Aldrich</td>
			<td>S9763</td>
			<td></td>
		</tr>
		<tr>
			<td>Deioinized water for molecular biology</td>
			<td>Millipore</td>
			<td>H20MB1001</td>
			<td></td>
		</tr>
		<tr>
			<td>0.2 micron sterile syringe filters</td>
			<td>VWR</td>
			<td>CA28145-477</td>
			<td></td>
		</tr>
		<tr>
			<td>3 kDa centrifugal filters</td>
			<td>Millipore</td>
			<td>UFC900324</td>
			<td></td>
		</tr>
		<tr>
			<td>Dialysis tubing 0.5-1.0 kDa cutoff</td>
			<td>Spectrum Laboratories</td>
			<td>131048</td>
			<td></td>
		</tr>
		<tr>
			<td>Silicon tubing</td>
			<td>VWR</td>
			<td>89068-474</td>
			<td></td>
		</tr>
		<tr>
			<td>Plastic DSC flange caps</td>
			<td>TA Instruments</td>
			<td>6111</td>
			<td></td>
		</tr>
		<tr>
			<td>DNA aptamer MN4</td>
			<td>Integrated DNA Technologies</td>
			<td>https://www.idtdna.com/site/order/menu</td>
			<td></td>
		</tr>
		<tr>
			<td>Cocaine</td>
			<td>Sigma Aldrich</td>
			<td>C008</td>
			<td></td>
		</tr>
		<tr>
			<td>Quinine</td>
			<td>Sigma Aldrich</td>
			<td>22620</td>
			<td></td>
		</tr>
		<tr>
			<td>NanoDSC-III microcalorimeter</td>
			<td>TA Instruments</td>
			<td>http://www.tainstruments.com/nanodsc/</td>
			<td></td>
		</tr>
		<tr>
			<td>DSCRun software</td>
			<td>TA Instruments</td>
			<td>http://www.tainstruments.com/support/software-downloads-support/instruments-by-software/</td>
			<td></td>
		</tr>
		<tr>
			<td>NanoAnalyze software</td>
			<td>TA Instruments</td>
			<td>http://www.tainstruments.com/support/software-downloads-support/instruments-by-software/</td>
			<td></td>
		</tr>
		<tr>
			<td>Contrad-70</td>
			<td>VWR</td>
			<td>89233-152</td>
			<td></td>
		</tr>
	</tbody>
</table>

measuring biomolecular dsc profiles with thermolabile ligands to rapidly characterize folding and binding interactions

Differential scanning calorimetry (DSC) is a powerful technique for quantifying thermodynamic parameters governing biomolecular folding and binding interactions. This information is critical in the design of new pharmaceutical compounds. However, many pharmaceutically relevant ligands are chemically unstable at the high temperatures used in DSC analyses. Thus, measuring binding interactions is challenging because the concentrations of ligands and thermally-converted products are constantly changing within the calorimeter cell. Here, we present a protocol using thermolabile ligands and DSC for rapidly obtaining thermodynamic and kinetic information on the folding, binding, and ligand conversion processes. We have applied our method to the DNA aptamer MN4 that binds to the thermolabile ligand cocaine. Using a new global fitting analysis that accounts for thermolabile ligand conversion, the complete set of folding and binding parameters are obtained from a pair of DSC experiments. In addition, we show that the rate constant for thermolabile ligand conversion may be obtained with only one supplementary DSC dataset. The guidelines for identifying and analyzing data from several more complicated scenarios are presented, including irreversible aggregation of the biomolecule, slow folding, slow binding, and rapid depletion of the thermolabile ligand.

Representative data for the thermolabile ligand DSC are shown in Figure 1. The position and height of the thermolabile ligand-bound peak successively shifts down towards that of the unbound biomolecule as the thermolabile ligand is depleted with each scan (Figure 1a). The free denaturation profile is used as a reference for the endpoint of thermolabile ligand conversion (Figure 1b). Data for MN4 bound to quinine are shown as a negative control for thermolabile ligand conversion (Figure 1b). The final thermolabile ligand scans have slightly higher transition midpoints and peak heights relative to the unbound MN4, indicating the thermolabile ligand conversion product (benzoylecgonine) has a weak affinity for MN4. The thermodynamic parameters resulting from global analysis of the datasets in Figure 1 are listed in Table 1. The folding parameters for MN4 in the presence of cocaine or quinine are identical within error, as expected since dilute small molecules are not expected to perturb the folding thermodynamics of the free biomolecule. The binding parameters are in good agreement with those from isothermal titration calorimetry (ITC)18 and reveal that MN4&#39;s preference for quinine over cocaine is driven by a more favorable binding enthalpy. In Figure 2, increasing the high temperature equilibration period yields more pronounced reductions of the thermolabile ligand concentration with each scan relative to the short equilibration period dataset. Using the optimized global fit concentration parameters from the two datasets, the rate constant for ligand conversion at the high equilibration temperature is calculated from the slope of the line in the Figure 2 inset.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/55959/55959fig1.jpg" /> 
Figure 1. Thermolabile ligand DSC. (a) Thermograms of MN4 (83 &#181;M) bound to cocaine (initial concentration 778 &#181;M). First and last scans of MN4 in the presence of ligand are shown as dark red and blue circles while the corresponding fits are shown as colored lines. (b) Thermograms of free MN4 (83 &#181;M, black circles) and successive scans bound to quinine (880 &#181;M, colored circles). Fits to the free and quinine-bound datasets are shown as black and colored lines, respectively. Reproduced from reference4 with permission from the Royal Society of Chemistry. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55959/55959fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/55959/55959fig2.jpg" /> 
Figure 2. Measuring the Rate Constant for Thermolabile Ligand Conversion. (a) Sets of thermograms for MN4 bound to cocaine with short (120 s, dark red) and long (600 s, dark blue) equilibration times at 80 &#176;C, respectively. (b) Concentrations of cocaine extracted from global analysis of the datasets in (a) as a function of scan number. Experimental points and exponential fits are shown as colored circles and lines respectively. The inset shows a linear fit to the previously described Supplementary Eq. 19 from Harkness et al. using the optimized global fit cocaine concentrations for the two datasets4. The rate constant for ligand thermal conversion at 80 &#176;C is calculated as the slope of the line. The error for the rate constant for thermolabile ligand conversion is given as &#177; two standard deviations. Reproduced from reference4 with permission from the Royal Society of Chemistry. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55959/55959fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Fit parameters</td>
			<td>Cocaine added</td>
			<td>Quinine added</td>
		</tr>
		<tr>
			<td>&#8710;HUF</td>
			<td>271.3&#177;1.8</td>
			<td>272.5&#177;4.0</td>
		</tr>
		<tr>
			<td>&#8710;SUF</td>
			<td>824.4&#177;5.1</td>
			<td>827.9&#177;10.9</td>
		</tr>
		<tr>
			<td>a&#8710;GUF</td>
			<td>21.6&#177;0.2</td>
			<td>21.6&#177;0.9</td>
		</tr>
		<tr>
			<td>a&#8710;HB1F</td>
			<td>-75.2&#177;1.6</td>
			<td>-101.0&#177;4.0</td>
		</tr>
		<tr>
			<td>a&#8710;SB1F</td>
			<td>-154.2&#177;5.0</td>
			<td>-213.7&#177;12.0</td>
		</tr>
		<tr>
			<td>&#8710;CpB1F</td>
			<td>-1.5&#177;0.1</td>
			<td>-1.2&#177;0.1</td>
		</tr>
		<tr>
			<td>a&#8710;GB1F</td>
			<td>-28.5&#177;0.2</td>
			<td>-36.2&#177;0.7</td>
		</tr>
		<tr>
			<td>a&#8710;HB2F</td>
			<td>-33.7&#177;1.8</td>
			<td>-</td>
		</tr>
		<tr>
			<td>a&#8710;SB2F</td>
			<td>-49.9&#177;5.2</td>
			<td>-</td>
		</tr>
		<tr>
			<td>&#8710;CpB2F</td>
			<td>-2.2&#177;0.1</td>
			<td>-</td>
		</tr>
		<tr>
			<td>a&#8710;GB2F</td>
			<td>-18.6&#177;0.3</td>
			<td>-</td>
		</tr>
	</tbody>
</table>
Table 1. Thermodynamic Parameters Extracted from Global Analysis of the MN4 DSC Datasets Using Cocaine and Quinine Ligands. Parameters were calculated at 30 &#176;C. B1F refers to cocaine- or quinine-bound folded states and B2F refers to the benzoylecgonine-bound folded state. &#916;H and &#916;G are expressed in kJ/mol, &#916;S is expressed in J/mol/K and &#916;Cp is expressed in kJ/mol/K. Errors were calculated according to the variance/co-variance method19.

Watch this Scientific Journal Video about Measuring Biomolecular DSC Profiles with Thermolabile Ligands to Rapidly Characterize Folding and Binding Interactions at JoVE.com

Measuring Biomolecular DSC Profiles with Thermolabile Ligands to Rapidly Characterize Folding and Binding Interactions

We present a protocol for rapid characterization of biomolecular folding and binding interactions with thermolabile ligands using differential scanning calorimetry.

Differential scanning calorimetry (DSC) is a powerful technique for quantifying thermodynamic parameters governing biomolecular folding and binding ...

measuring-biomolecular-dsc-profiles-with-thermolabile-ligands-to

Nanyang Technological University

Research

JoVE Journal

Biochemistry

8.2K Views.  McGill University. We present a protocol for rapid characterization of biomolecular folding and binding interactions with thermolabile ligands using differential scanning calorimetry.

Video: Measuring Biomolecular DSC Profiles with Thermolabile Ligands to Rapidly Characterize Folding and Binding Interactions

Time-resolved ElectroSpray Ionization Hydrogen-deuterium Exchange Mass Spectrometry for Studying Protein Structure and Dynamics

Intrinsically disordered proteins (IDPs) have long been a challenge to structural biologists due to their lack of stable secondary structure elements. Hydrogen-Deuterium Exchange (HDX) measured at rapid time scales is uniquely suited to detect structures and hydrogen bonding networks that are briefly populated, allowing for the characterization of transient conformers in native ensembles. Coupling of HDX to mass spectrometry offers several key advantages, including high sensitivity, low sample consumption and no restriction on protein size. This technique has advanced greatly in the last several decades, including the ability to monitor HDX labeling times on the millisecond time scale. In addition, by incorporating the HDX workflow onto a microfluidic platform housing an acidic protease microreactor, we are able to localize dynamic properties at the peptide level. In this study, Time-Resolved ElectroSpray Ionization Mass Spectrometry (TRESI-MS) coupled to HDX was used to provide a detailed picture of residual structure in the tau protein, as well as the conformational shifts induced upon hyperphosphorylation.

Conformational flexibility plays a critical role in protein function. Herein, we describe the use of time-resolved electrospray ionization mass spectrometry coupled to hydrogen-deuterium exchange for probing the rapid structural changes that drive function in ordered and disordered proteins.

Intrinsically disordered proteins (IDPs) have long been a challenge to structural biologists due to their lack of stable secondary structure elements. ...

Measuring G-protein-coupled Receptor Signaling via Radio-labeled GTP Binding

G-Protein-Coupled Receptors (GPCRs) are a large family of transmembrane receptors that play critical roles in normal cellular physiology and constitute a major pharmacological target for multiple indications, including analgesia, blood pressure regulation, and the treatment of psychiatric disease. Upon ligand binding, GPCRs catalyze the activation of intracellular G-proteins by stimulating the incorporation of guanosine triphosphate (GTP). Activated G-proteins then stimulate signaling pathways that elicit cellular responses. GPCR signaling can be monitored by measuring the incorporation of a radiolabeled and non-hydrolyzable form of GTP, [35S]guanosine-5&#39;-O-(3-thio)triphosphate ([35S]GTP&#947;S), into G-proteins. Unlike other methods that assess more downstream signaling processes, [35S]GTP&#947;S binding measures a proximal event in GPCR signaling and, importantly, can distinguish agonists, antagonists, and inverse agonists. The present protocol outlines a sensitive and specific method for studying GPCR signaling using crude membrane preparations of an archetypal GPCR, the &#181;-opioid receptor (MOR1). Although alternative approaches to fractionate cells and tissues exist, many are cost-prohibitive, tedious, and/or require non-standard laboratory equipment. The present method provides a simple procedure that enriches functional crude membranes. After isolating MOR1, various pharmacological properties of its agonist, [D-Ala, N-MePhe, Gly-ol]-enkephalin (DAMGO), and antagonist, naloxone, were determined.

Guanosine triphosphate (GTP) binding is one of the earliest events in G-Protein-Coupled Receptor (GPCR) activation. This protocol describes how to pharmacologically characterize specific GPCR-ligand interactions by monitoring the binding of the radio-labeled GTP analog, [35S]guanosine-5&#39;-O-(3-thio)triphosphate ([35S]GTP&#947;S), in response to a ligand of interest.

G-Protein-Coupled Receptors (GPCRs) are a large family of transmembrane receptors that play critical roles in normal cellular physiology and constitute a ...

Measuring Protein Binding to F-actin by Co-sedimentation

Filamentous actin (F-actin) organization within cells is regulated by a large number of actin-binding proteins that control actin nucleation, growth, cross-linking and/or disassembly. This protocol describes a technique &#8211; the actin co-sedimentation, or pelleting, assay &#8211; to determine whether a protein or protein domain binds F-actin and to measure the affinity of the interaction (i.e., the dissociation equilibrium constant). In this technique, a protein of interest is first incubated with F-actin in solution. Then, differential centrifugation is used to sediment the actin filaments, and the pelleted material is analyzed by SDS-PAGE. If the protein of interest binds F-actin, it will co-sediment with the actin filaments. The products of the binding reaction (i.e., F-actin and the protein of interest) can be quantified to determine the affinity of the interaction. The actin pelleting assay is a straightforward technique for determining if a protein of interest binds F-actin and for assessing how changes to that protein, such as ligand binding, affect its interaction with F-actin.

This protocol describes a method to test the ability of a protein to co-sediment with filamentous actin (F-actin) and, if binding is observed, to measure the affinity of the interaction.

Filamentous actin (F-actin) organization within cells is regulated by a large number of actin-binding proteins that control actin nucleation, growth, ...

Detection of Small GTPase Prenylation and GTP Binding Using Membrane Fractionation and  GTPase-linked Immunosorbent Assay

The Rho GTPase family belongs to the Ras superfamily and includes approximately 20 members in humans. Rho GTPases are important in the regulation of diverse cellular functions, including cytoskeletal dynamics, cell motility, cell polarity, axonal guidance, vesicular trafficking, and cell cycle control. Changes in Rho GTPase signaling play an essential regulatory role in many pathological conditions, such as&#160;cancer, central nervous system diseases, and immune system-dependent diseases. The posttranslational modification of Rho GTPases (i.e., prenylation by mevalonate pathway intermediates) and GTP binding are key factors which affect the activation of this protein. In this paper, two essential and simple methods are provided to detect a broad range of Rho GTPase prenylation and GTP binding activities. Details of the technical procedures that have been used are explained step by step in this manuscript.

Here we describe a protocol to investigate the prenylation and guanosine-5'-triphosphate (GTP)-loading of Rho GTPase. This protocol consists of two detailed methods, namely membrane fractionation and a GTPase-linked immunosorbent assay. The protocol can be used for measuring the prenylation and GTP loading of different other small GTPases.

The Rho GTPase family belongs to the Ras superfamily and includes approximately 20 members in humans. Rho GTPases are important in the regulation of ...

Interactions with and Membrane Permeabilization of Brain Mitochondria by Amyloid Fibrils

A growing body of evidence indicates that membrane permeabilization, including internal membranes such as mitochondria, is a common feature and primary mechanism of amyloid aggregate-induced toxicity in neurodegenerative diseases. However, most reports describing the mechanisms of membrane disruption are based on phospholipid model systems, and studies directly targeting events occurring at the level of biological membranes are rare. Described here is a model for studying the mechanisms of amyloid toxicity at the membrane level. For mitochondrial isolation, density gradient medium is used to obtain preparations with minimal myelin contamination. After mitochondrial membrane integrity confirmation, the interaction of amyloid fibrils arising from &#945;-synuclein, bovine insulin, and hen egg white lysozyme (HEWL) with rat brain mitochondria, as an in vitro biological model, is investigated. The results demonstrate that treatment of brain mitochondria with fibrillar assemblies can cause different degrees of membrane permeabilization and ROS content enhancement. This indicates structure-dependent interactions between amyloid fibrils and mitochondrial membrane. It is suggested that biophysical properties of amyloid fibrils and their specific binding to mitochondrial membranes may provide explanations for some of these observations.

Provided here is a protocol for investigating the interactions between native form, prefibrillar, and mature amyloid fibrils of different peptides and proteins with mitochondria isolated from different tissues and various areas of the brain.

A growing body of evidence indicates that membrane permeabilization, including internal membranes such as mitochondria, is a common feature and primary ...

Measuring Nucleotide Binding to Intact, Functional Membrane Proteins in Real Time

We have developed a method to measure binding of adenine nucleotides to intact, functional transmembrane receptors in a cellular or membrane environment. This method combines expression of proteins tagged with the fluorescent non-canonical amino acid ANAP, and FRET between ANAP and fluorescent (trinitrophenyl) nucleotide derivatives. We present examples of nucleotide binding to ANAP-tagged KATP ion channels measured in unroofed plasma membranes and excised, inside-out membrane patches under voltage clamp. The latter allows for simultaneous measurements of ligand binding and channel current, a direct readout of protein function. Data treatment and analysis are discussed extensively, along with potential pitfalls and artefacts. This method provides rich mechanistic insights into the ligand-dependent gating of KATP channels and can readily be adapted to the study of other nucleotide-regulated proteins or any receptor for which a suitable fluorescent ligand can be identified.

This protocol presents a method for measuring adenine nucleotide binding to receptors in real time in a cellular environment. Binding is measured as F&#246;rster resonance energy transfer (FRET) between trinitrophenyl nucleotide derivatives and protein labeled with a non-canonical, fluorescent amino acid.

We have developed a method to measure binding of adenine nucleotides to intact, functional transmembrane receptors in a cellular or membrane environment. ...

Removal and Replacement of Endogenous Ligands from Lipid-Bound Proteins and Allergens

Many major allergens bind to hydrophobic lipid-like molecules, including Mus m 1, Bet v 1, Der p 2, and Fel d 1. These ligands are strongly retained and have the potential to influence the sensitization process either through directly stimulating the immune system or altering the biophysical properties of the allergenic protein. In order to control for these variables, techniques are required for the removal of endogenously bound ligands and, if necessary, replacement with lipids of known composition. The cockroach allergen Bla g 1 encloses a large hydrophobic cavity which binds a heterogeneous mixture of endogenous lipids when purified using traditional techniques. Here, we describe a method through which these lipids are removed using reverse-phase HPLC followed by thermal annealing to yield Bla g 1 in either its Apo-form or reloaded with a user-defined mixture of fatty acid or phospholipid cargoes. Coupling this protocol with biochemical assays reveal that fatty acid cargoes significantly alter the thermostability and proteolytic resistance of Bla g 1, with downstream implications for the rate of T-cell epitope generation and allergenicity. These results highlight the importance of lipid removal/reloading protocols such as the one described herein when studying allergens from both recombinant and natural sources. The protocol is generalizable to other allergen families including lipocalins (Mus m 1), PR-10 (Bet v 1), MD-2 (Der p 2) and Uteroglobin (Fel d 1), providing a valuable tool to study the role of lipids in the allergic response.

This protocol describes the removal of endogenous lipids from allergens, and their replacement with user-specified ligands through reverse-phase HPLC coupled with thermal annealing. 31P-NMR and circular dichroism allow for the rapid confirmation of ligand removal/loading, and the recovery of native allergen structure.

Many major allergens bind to hydrophobic lipid-like molecules, including Mus m 1, Bet v 1, Der p 2, and Fel d 1. These ligands are strongly retained and ...

Identifying the Binding Proteins of Small Ligands with the Differential Radial Capillary Action of Ligand Assay (DRaCALA)

The past decade has seen tremendous progress in the understanding of small signaling molecules in bacterial physiology. In particular, the target proteins of several nucleotide-derived secondary messengers (NSMs) have been systematically identified and studied in model organisms. These achievements are mainly due to the development of several new techniques including the capture compound technique and the differential radial capillary action of ligand assay (DRaCALA), which were used to systematically identify target proteins of these small molecules. This paper describes the use of the NSMs, guanosine penta- and tetraphosphates (p)ppGpp, as an example and video demonstration of the DRaCALA technique. Using DRaCALA, 9 out of 20 known and 12 new target proteins of (p)ppGpp were identified in the model organism, Escherichia coli K-12, demonstrating the power of this assay. In principle, DRaCALA could be used for studying small ligands that can be labeled by radioactive isotopes or fluorescent dyes. The critical steps, pros, and cons of DRaCALA are discussed here for further application of this technique.

Identifying the Binding Proteins of Small Ligands with the Differential Radial Capillary Action of Ligand Assay DRaCALA

The Differential Radial Capillary Action of Ligand Assay (DRaCALA) can be used to identify small ligand binding proteins of an organism by using an ORFeome library.

The past decade has seen tremendous progress in the understanding of small signaling molecules in bacterial physiology. In particular, the target proteins ...

Mass-Sensitive Particle Tracking to Characterize Membrane-Associated Macromolecule Dynamics

Short-lived or transient interactions of macromolecules at and with lipid membranes, an interface where a multitude of essential biological reactions take place, are inherently difficult to assess with standard biophysical methods. The introduction of mass-sensitive particle tracking (MSPT) constitutes an important step toward a thorough quantitative characterization of such processes. Technically, this was made possible through the advent of interferometric scattering microscopy (iSCAT)-based mass photometry (MP). When the background removal strategy is optimized to reveal the two-dimensional motion of membrane-associated particles, this technique allows the real-time analysis of both diffusion and molecular mass of unlabeled macromolecules on biological membranes. Here, a detailed protocol to perform and analyze mass-sensitive particle tracking of membrane-associated systems is described. Measurements performed on a commercial mass photometer achieve time resolution in the millisecond regime and, depending on the MP system, a mass detection limit down to 50 kDa. To showcase the potential of MSPT for the in-depth analysis of membrane-catalyzed macromolecule dynamics in general, results obtained for exemplary protein systems such as the native membrane interactor annexin V are presented.

This protocol describes an iSCAT-based image processing and single-particle tracking approach that enables the simultaneous investigation of the molecular mass and the diffusive behavior of macromolecules interacting with lipid membranes. Step-by-step instructions for sample preparation, mass-to-contrast conversion, movie acquisition, and post-processing are provided alongside directions to prevent potential pitfalls.

Short-lived or transient interactions of macromolecules at and with lipid membranes, an interface where a multitude of essential biological reactions take ...

Quantifying the Binding Interactions Between Cu(II) and Peptide Residues in the Presence and Absence of Chromophores

Copper(II) is an essential metal in biological systems, conferring unique chemical properties to the biomolecules with which it interacts. It has been reported to directly bind to a variety of peptides and play both necessary and pathological roles ranging from mediating structure to electron transfer properties to imparting catalytic function. Quantifying the binding affinity and thermodynamics of these Cu(II)-peptide complexes in vitro provides insight into the thermodynamic driving force of binding, potential competitions between different metal ions for the peptide or between different peptides for Cu(II), and the prevalence of the Cu(II)-peptide complex in vivo. However, quantifying the binding thermodynamics can be challenging due to a myriad of factors, including accounting for all competing equilibria within a titration experiment, especially in cases where there are a lack of discrete spectroscopic handles representing the peptide, the d-block metal ion, and their interactions.
Here, a robust set of experiments is provided for the accurate quantification of Cu(II)-peptide thermodynamics. This article focuses on the use of electronic absorption spectroscopy in the presence and absence of chromophoric ligands to provide the needed spectroscopic handle on Cu(II) and the use of label-free isothermal titration calorimetry. In both experimental techniques, a process is described to account for all competing equilibria. While the focus of this article is on Cu(II), the described set of experiments can apply beyond Cu(II)-peptide interactions, and provide a framework for accurate quantification of other metal-peptide systems under physiologically relevant conditions.

Quantifying the Binding Interactions Between CuII and Peptide Residues in the Presence and Absence of Chromophores

This article focuses on the use of electronic absorption spectroscopy and isothermal titration calorimetry to probe and quantify the thermodynamics of Cu(II) binding to peptides and proteins.

Copper(II) is an essential metal in biological systems, conferring unique chemical properties to the biomolecules with which it interacts. It has been ...