The authors are very thankful to Joseph Mancini (formerly with GE Healthcare), Pawel Czudec, Thomas Cage (Malvern Instruments limited) for their role in the installation and training on the differential scanning calorimeter, Sasmit Deshmukh and Webster Magcalas for their discussions.

1. Instrument Start-up
<ol>
	<li>Switch on the differential scanning calorimeter and increase the pressure in the cells to suppress boiling of the samples as well as prevent the formation bubbles at elevated temperatures. This is typically achieved by supplying nitrogen into the system.</li>
	<li>Depending on the constituting material of the cell (e.g., tantalum, gold, platinum, etc.), adjust the pressure of the nitrogen gas supply according to the manufacturer&#39;s recommended pressure to avoid damaging the cell. For example, set the pressure of the nitrogen gas supply to 45 psi for the instrument used to develop this procedure, and pressure above 80 psi may damage the cell.</li>
	<li>Ensure that all the cleaning agent reservoirs are filled to the required volume. Cleaning agents required include detergent and water to wash and clean the cell respectively after each sample run.</li>
	<li>Set the temperature of the sample holding compartment to a suitable value, preferably 5 &#176;C, to maintain the integrity of the sample prior to experiment.</li>
</ol>
2. Sample Preparation
<ol>
	<li>Dialyze the sample against the buffer that will be used as the reference for the experiment. Alternatively, elution buffer collected at the final step of protein purification (i.e. column elution) can be used.</li>
	<li>Determine the concentration of the protein sample using the most suitable protein concentration determination method such as Kjedahl method 33 or Lowry method 34. For objective comparison of results, use the same method consistently within the same study. The required concentration range may vary depending on the model of the instrument. For the instrument used in this protocol, the preferable working range is 0.5 &#8211; 1 mg/mL.</li>
	<li>Degas the sample and reference buffer in vacuum to get rid of microbubbles that can cause volume inaccuracy. This step can be skipped for newer calorimeter models.</li>
	<li>Using a micropipette and sterile tips in a laminar flow biocontainment cabinet, load the samples and their respective buffer in pairs into 96 well plates compatible with the instrument. Fill the first two pairs of wells with buffer and the last two pairs with water for the buffer-buffer and the water scan respectively. Buffer-buffer scans verify the suitability of the instrument prior to sample measurement (i.e. assessment of instrumentation error) as well as establish a baseline; while water scans are run to clean the cells.</li>
	<li>Cover the 96-well plate with a sealing film, and ensure that the wells are properly sealed before taking the plate out of the Biosafety Cabinet to avoid sample contamination.</li>
	<li>Place the plate in the sample holding compartment in the proper orientation.</li>
</ol>
3. Experimental Parameter Setup
Note: Depending on the instrumentation, samples can be loaded into the cell either manually using a syringe, or automatically using an autosampler. In this case (i.e. an industrial setting), an autosampler is used to save time.
<ol>
	<li>Using the acquisition software, enter the sample information in the order the plate was loaded as per section 2.4.&#160; Enter concentrations if available, otherwise, enter concentration values into analysis software prior to data analysis (section 4.2).</li>
	<li>Select the option that ensures cleaning of cells with detergent before every sample scan, which should be followed by multiple water rinse steps to ensure no detergent residue is left in the cells.</li>
	<li>Set the starting temperature of the experiment to 20 &#176;C, but this can vary depending on prior knowledge of the sample. For known proteins, pre-determined starting temperature can be used, while a lower starting temperature can be applied for unknown samples.</li>
	<li>Set the final temperature of the experiment, e.g. 100 &#176;C. The final temperature may vary depending on prior knowledge of the sample.</li>
	<li>Set the scan rate of the experiment, e.g. 60 &#176;C/h, which is the typical scan rate. However, scan rate may vary depending on prior knowledge of the sample, e.g. 90 &#176;C/h, or 120 &#176;C/h. It is advisable to scan unknown samples at different scan rates to assess the kinetics of unfolding.</li>
	<li>&#160;Rescan samples to investigate the reversibility of the thermal unfolding. The unfolding of a protein is considered reversible if the enthalpy obtained for the second scan is at least 80% of the enthalpy value for the first scan.</li>
	<li>Set the post-experiment thermostat to 10 &#176;C to preserve the integrity of the calorimeter&#39;s cells.</li>
	<li>Verify that the experiment setup parameters are correct before executing the experiment. If everything is in place, start the experiment.</li>
</ol>
4. Data Analysis
<ol>
	<li>Retrieve raw data from the experiment and select one sample at a time for analysis. Subtract reference scan, i.e. buffer, from the sample scan. 
	NOTE: Reference subtraction is carried out automatically by newer models of DSC instruments.</li>
	<li>Enter sample concentration value if it was omitted as per section 3.1.</li>
	<li>Fit and subtract baseline from the acquired thermogram to account for differences in the heat capacities of the folded and unfolded states of the protein which is caused by the exposure of hydrophobic groups to water upon unfolding. Linear or cubic curve fitting can be applied depending on the shape of the DSC profile for the sample. For consistency, the same type of fitting has to be used during a study, e.g. real-time stability study. This step is required to process the curve for peak integration to obtain enthalpy of transition.</li>
	<li>Perform peak integration using non-linear least square fit. Based on product knowledge apply two-state or non-two-state model. Two-state model can be used for single cooperative thermal transitions, and for unknown proteins, apply non-two state model until further product knowledge is available. If applicable, adjust curve fitting using the iterative curve fitting function of the equipment&#39;s software until the Chi-square value remains constant.</li>
	<li>Obtained results will show the values for midpoint of transition temperatures (Tm), calorimetric enthalpy (&#916;H), and van&#8217;t Hoff enthalpy (&#916;HVH) of the sample.</li>
</ol>

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All authors are employees at Sanofi Pasteur. The work was funded by Sanofi Pasteur, and publication fees for this video-article were paid by Sanofi Pasteur.&#160; The authors have no relevant affiliations or financial involvement with any organization or entity that has a financial conflict with the subject matter or materials discussed in the manuscript. These include employment, consultancies, stock ownership or options, or royalties.
No writing assistance was utilized in the production of this manuscript.

This procedure has been successfully incorporated in various characterization test packages, including stability and product comparability studies 21. In real-time stability studies, DSC is used to monitor the Tm, as well as estimate the Fa of biologics over time to determine their shelf-life. With regards to product comparability, it is used to assess the impact of process and facility change as well as the effect of key manufacturing steps on the structural conformation of produced lots. This typically involves the direct comparison of the &#916;H of produced lot to a reference product that has been designated as the ideal product. In addition, DSC has proven to be a useful analytical tool for product formulation studies 37. The Tm of a protein in different buffers and at different concentrations can be used to determine the formulation that proffers the most stability to the protein.
To ensure the reliability of this method and objectivity of its results, it is important to keep testing parameters consistent from run to run within the same study (e.g., vaccine formulation study). However, the procedure can be modified to accommodate differences in the physical properties of various proteins. An example of a modification that can be made is altering the scanning rate of the experiment 38, 39. Proteins that were prone to forming aggregates when heated were examined at a faster scanning rate (e.g., 120 &#176;C/h) to avoid the contribution of aggregates to the thermal transition profile as well as clogging the capillaries of the calorimeter. It is worth noting that scanning rate can influence the outcome of a DSC experiment 38. Broadening of the thermal transition peak has been observed with increasing scanning rates in some proteins; however, Tm remained fairly constant 38. Furthermore, the dialysis and degassing steps for sample preparation are also very crucial for accurate results 31. Dialysis ensures that the only difference in the composition of the sample and the buffer is the protein; thus, all the excess heat absorbed by the sample can be attributed to the heat capacity of the protein. Degassing ensures precise volume analysis, as the extrapolation of the thermodynamic parameter assumes that the unfolding event is occurring under constant volume and pressure 31. The constant pressure portion of the assumption is accounted for by nitrogen pressurization of the system as per section 1.1 of the procedure.
In comparison to other methods of determining the stability of protein conformations such as Circular Dichroism (CD) and Fluorescence Spectroscopies, DSC offers a number of advantages in a commercial setting including cost and time savings. Firstly, the adiabatic design of a differential scanning calorimeter allows for the measurement of thermal stability with better temperature precision as compared to measurements with instrumentation for CD and Fluorescence Spectroscopies 6. Secondly, unlike CD, the accuracy of DSC data is not dependent on the helicity of the protein 39, 40; however, CD provides additional information about the unfolding of the secondary structure, which would be complimentary to the DSC 41. Additionally, the pressurization of the DSC system allows for testing with a wide temperature range without boiling the sample; thus, a wide range of proteins can be tested by DSC.
While DSC is a relatively fast and straightforward approach to determine the thermal stability of biologics, it is not without limitations. First, the baseline subtraction step introduces some form of human inconsistency into the raw data analysis; thus, variations in results may be observed among different users. Second, differential scanning calorimeters have minimum concentration limits which might be difficult to achieve at bulk manufacturing scale. Third, the &#916;H of irreversible thermal denaturation is not absolute; which implies that derived &#916;G (an indicator of protein stability) in similar scenarios can be misleading. Furthermore, the method works best for purified samples. Presence of impurities may either cause a shift in the Tm if there is an interaction with the protein under investigation, or appearance of new thermal transitions if there is no interaction. In any case these extra features on the thermograms can be wrongly attributed to samples, thus impacting the interpretation of results. Despite these limitations, DSC remains a reliable method that can provide detailed thermodynamic information about the protein unfolding process if implemented properly 42.
In conclusion, DSC offers considerable advantage as a conformational readout tool for vaccine products and their intermediates. The two parameters, Tm and &#916;H, collected for an array of lots of the same product can become an empirical baseline that can be used to examine the impact of process changes, formulation, and storage conditions on the tertiary structure and stability of protein and viral antigens 21, 43.

Differential scanning calorimetry (DSC) is an experimental method that directly measures the difference in heat energy uptake taking place in a sample relative to a reference during a regulated temperature change 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12. Carried out in a differential scanning calorimeter, the method involves introducing heat energy into a sample cell and a reference cell simultaneously while identically increasing the temperature of both cells over time 2, 13, 14. Due to difference in the composition of the sample and the reference, different amount of energy will be required to raise the temperature of the cells 2, 12, 13. Thus, the excess amount of energy required to compensate for the temperature difference between the cells is measured and directly correlated to specific thermodynamic properties of the sample 1, 3.
In the 1960s, M.J. O'Neil and E. Watson of Perkin Elmer developed the first differential scanning calorimeter to measure the heat flow of solid materials 2, 3, 4. In parallel, P.L. Privalov and D.R. Monaseldze E.L. of the Institute of Physics, Republic of Georgia (former USSR) created a unique differential adiabatic calorimeter that can be used for biochemical research 5, 6. Subsequently, Andronikashvili's team at the Institute of Physics, Republic of Georgia, reported the heat capacity of biomolecules such as fibrous and globular proteins, DNA, and RNA using DSC 7, 8, 9. Several teams led by Sturtevant 10, 11, 12, Brandts 13, and Privalov 14, 15, 16focused on the development of the theory and practical applications of DSC to investigate the thermodynamic details of protein unfolding. The value of DSC in studying large supramolecular structures such as phages, chloroplast, phospholipid liquid crystals, and meat proteins have also been reported 17, 18, 19, 20.
DSC has now become commonplace in pharmaceutical research and development for the assessment of the thermal stability of biomolecules, especially proteins 1, 21, 22. This is mostly due to advancements in terms of sensitivity and automation of the instrumentation used to carry out the experiment 23, 24. Here, the final result of the DSC experiment, namely, molar heat capacity as a function of temperature, is used to estimate  the following thermodynamic parameters (change in heat capacity (∆Cp), enthalpy (∆H), entropy (∆S), and Gibbs free energy (∆G)) using the equation below:
<img alt="Specific heat capacity equation Cp=(dq/dT), showing heat transfer concepts." src="/files/ftp_upload/55262/55262eq1.jpg" data-altupdatedat="1747911167000" data-alt="Equation 1">   (1)
<img alt="ΔCp equation for specific heat capacity difference in thermodynamic study, formula analysis." src="/files/ftp_upload/55262/55262eq2.jpg" data-altupdatedat="1747911167000" data-alt="Equation 2">   (2)
<img alt="Enthalpy equation, ΔH(T)=∫T0ΔCpdT, thermodynamics formula, energy change, temperature integration." src="/files/ftp_upload/55262/55262eq3.jpg" data-altupdatedat="1747911167000" data-alt="Equation 3">   (3)
<img alt="Thermodynamic entropy change formula, ΔS(T), integral diagram, heat capacity analysis." src="/files/ftp_upload/55262/55262eq4.jpg" data-altupdatedat="1747911167000" data-alt="Equation 4">   (4)
<img alt="Gibbs free energy formula ΔG(T)=ΔH(T)-TΔS(T); thermodynamics equation." src="/files/ftp_upload/55262/55262eq5.jpg" data-altupdatedat="1747911167000" data-alt="Equation 5">   (5)
Where Cp is measured heat capacity; q is the heat flow into the test material; T0 and T are the initial and final temperatures of the transition respectively 22, 25. It is also worth noting that the equations above apply to single-domain proteins that can undergo two-state transition and reversible thermal unfolding 22. Analysis of more complex proteins (e.g., non-two-state proteins, and oligomers) have been reported by Friere et al. 26; Johnson et al. 27; and Kasimova et al. 28.
To determine whether a protein undergoes two-state transition or forms intermediates during thermal denaturation, the experimentally derived enthalpy (ΔH; also referred to as calorimetric enthalpy ΔHCal) is compared to the enthalpy derived using the van't Hoff equation given below (also referred to as van't Hoff enthalpy; ΔHVH):
<img alt="Protein stability thermodynamics formula for equilibrium analysis, showing ΔHvH calculation." src="/files/ftp_upload/55262/55262eq6.jpg" data-altupdatedat="1747911167000" data-alt="Equation 6">   (6)
Where Tm is the midpoint temperature of the transition, R is the ideal gas constant (1.987 cal mol-1 K-1) and Y is the fraction of the protein population in the unfolded state 16, 29. If ΔHVH is equal to ΔHCal; or ΔHVH/ΔHCal is equal to 1, then the protein undergoes an "all-or-none" transition (i.e. two-state transition) 16, 25, 29. However, if ΔHVH is less than ΔHCal; or ΔHVH/ΔHCal is less than 1, the protein undergoes a non-two-state transition 16, 25, 29. The ratio of ΔHVH/ΔHCal also corresponds to the proportion of the protein structure that melts as a thermodynamic cooperative unit or domain 26.
The thermodynamic parameters mentioned above such as ΔG and ΔH provide useful information about the thermal stability of proteins, including biologics 30. However, emphasis will be laid on Tm and ΔH in this publication, as they are the reported values for this protocol. Tm is the mid-point temperature of the transition, where the folded and the unfolded states of the protein are at equilibrium (i.e., ΔG = 0) 25, 31. The higher the Tm of a protein, the higher its thermal stability 31. ΔH corresponds to the area under the peak(s) of the Heat Capacity versus Temperature graph (also known as thermogram) generated at the end of the DSC experiment 16, 25. It is the energy required to denature proteins and can be used to estimate the active fraction (Fa) in a protein formulation (i.e., the proportion of proteins with active conformation in a sample) using the following equation:
<img alt="Static equilibrium formula: Fa = ΔH/Q, emphasizing force balance concepts." src="/files/ftp_upload/55262/55262eq7.jpg" data-altupdatedat="1747911167000" data-alt="Equation 7">   (7)
Where ΔH is the experimentally derived enthalpy of the protein sample and Q is the enthalpy determined for a well characterized reference or standardized protein 22. The estimation of Fa is significant for monitoring the real-time stability of products as well as conducting stability studies under stress conditions as required by ICH guidelines 32. Comparison of ΔH also provides information about the compactness of the tertiary structure conformation of a protein 31.
This protocol details a procedure for assessing the thermal stability of proteins in an industrial setting and has been extensively used for the formulation of vaccines. It was developed using an automated differential scanning calorimeter that generates reproducible results for protein concentrations as low as 300 µg/mL.

<table><tbody><tr><td>Differential Scanning Calorimeter</td><td>Malvern Instruments Ltd</td><td>28428948 (Via GE Healthcare)</td><td>Has an autosampler for automated dispensing of samples into the cell to reduce human effort and errors.</td></tr><tr><td>Contrad 100</td><td>Decon Laboratories Inc</td><td>1504</td><td>Dilute with water to 20% before use</td></tr><tr><td>500 &amp;micro;L Polypropylene round bottom 96 well plate</td><td>Canadian Life Science</td><td>ML072100</td><td>Equivalent plates from other suppliers (&lt;em&gt;e.g.&lt;/em&gt;, VW) can also be used</td></tr><tr><td>MicroCal ThermoVac&amp;nbsp;</td><td>Malvern Instruments Ltd</td><td>N/Ap</td><td>provided with the Cap VP DSC</td></tr><tr><td>Biosafety cabinet&amp;nbsp;</td><td>Labconco</td><td>Logic+ - A2</td><td>biocontainment laminar flow cabinet for sample preparation</td></tr><tr><td>Slide-A-Lyzer dialysis cassette</td><td>Thermo Scientific</td><td>66810 or 66380</td><td>to equilibrate the sample and buffer</td></tr></tbody></table>

differential scanning calorimetry &#8212; a method for assessing the thermal stability and conformation of protein antigen

Differential scanning calorimetry (DSC) is an analytical technique that measures the molar heat capacity of samples as a function of temperature. In the case of protein samples, DSC profiles provide information about thermal stability, and to some extent serves as a structural &#8220;fingerprint&#8221; that can be used to assess structural conformation. It is performed using a differential scanning calorimeter that measures the thermal transition temperature (melting temperature; Tm) and the energy required to disrupt the interactions stabilizing the tertiary structure (enthalpy; &#8710;H) of proteins. Comparisons are made between formulations as well as production lots, and differences in derived values indicate differences in thermal stability and structural conformation. Data illustrating the use of DSC in an industrial setting for stability studies as well as monitoring key manufacturing steps are provided as proof of the effectiveness of this protocol. In comparison to other methods for assessing the thermal stability of protein conformations, DSC is cost-effective, requires few sample preparation steps, and also provides a complete thermodynamic profile of the protein unfolding process.

The raw data from most DSC experiments are presented as a heat flux versus temperature graph, as the calorimeter actually measures the difference in the rate of heat flow into the sample solution and buffer 35. Therefore, if both cells (i.e. sample and reference cells) contain identical solutions during an experiment, the raw data from the scan should be a flat line with no observable peaks. Any peak observed can be attributed to instrumentation error (e.g. damaged or contaminated cells), which is why running buffer scans prior to sample analysis is an adequate system suitability test. Figure 1 illustrates the result of a typical buffer scan indicating that the calorimeter was in good working condition prior to sample analysis.
Figure 2 shows the raw data for a DSC experiment carried out on different lots of two protein samples. As implied earlier, the observed peaks are the differences in the heat flux of the samples and their respective buffers. Differences in sample concentration can cause variations in heat capacity recorded by the calorimeter; however, these variations are normalized during sample analysis as per section 4.2 of the procedure. Higher concentrations can also reveal additional thermodynamic domains not contributing to the transition at lower concentrations. In addition, each transition represents a thermodynamic domain that may include one or more structural domains of the protein 36. In this case, the Protein 1 has three structural domains that melt cooperatively.
Figure 3 shows the results generated from the analysis of the raw data for protein 1 and 2 presented in Figure 2, i.e., after baseline subtraction and iterative curve fitting. The resulting thermograms have been normalized for scanning rate (automatically carried out by a pre-set algorithm in the analysis software) and concentration; thus, presenting the results of the experiment in comparable heat capacity versus temperature graphs. The analysis software uses data from the Heat Capacity versus Temperature graphs, such as Tm and ΔCp, to derive other thermodynamic parameters using variations of the equations given above depending on the cooperativity of protein unfolding.
When testing unknown samples, setting the appropriate temperature range is crucial. Otherwise, incomplete thermograms may result, as illustrated in Figure 4. Although Tm from such profiles can be derived, ΔH cannot be accurately determined. Therefore, the sample must be retested with a larger temperature range to completely capture the thermal transition. Some proteins also readily form aggregates after complete denaturation, resulting in an increasing post-transition heat capacity: this often appears as an incomplete thermogram as illustrated in Figure 2B. However, retesting with a higher final temperature can help confirm whether there is an occurrence of a conformational transition at that region of the thermogram or it is merely the heat absorbing effect of protein aggregates.
Thermal stability is one of the most significant physical properties of proteins and protein-based products in the industry 37. In pharmaceuticals, it is used to determine the stability of biologics under different conditions, including formulation buffers and environmental factors such as humidity and temperature. It is also used to monitor key manufacturing step (e.g., purification and detoxification) to ensure conformational consistency between production lots. Figures 5 and 6 illustrate the use of DSC to examine the effects of chemical detoxification and storage conditions respectively on the stability and structural conformation of two different proteins. The significant differences in Tm and ∆H indicate conformational changes and protein degradation respectively. In addition, the loss of the third transition in Figure 6 further illustrates the degradation of a domain which was confirmed by a decrease in molecular weight when the samples were analyzed using Size-Exclusion Chromatography with multi-angle light scattering (SEC-MALS) (data not shown).
<img alt="Differential scanning calorimetry graph showing heat capacity vs temperature for buffer analysis." src="/files/ftp_upload/55262/55262fig1.jpg" data-altupdatedat="1747911167000" data-alt="Figure 1"> 
Figure 1: Buffer Scans. The similarity in gradient of each scan with no observable peaks indicates that the instrument is in good working condition and generated reproducible results. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55262/55262fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Thermal analysis graphs of protein heat capacity vs temperature, depicting different protein loads." src="/files/ftp_upload/55262/55262fig2.jpg" data-altupdatedat="1747911167000" data-alt="Figure 2"> 
Figure 2: Raw Data Collected from DSC Experiments. These graphs are good representations of the unanalyzed (raw) data acquired after experimental runs (i.e. prior to baseline subtraction and curve fitting). Each line represents a production lot. Protein 2 tends to aggregate more readily upon heating, resulting in an increase in heat capacity above 100 °C in the post-transition region of the thermogram. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55262/55262fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Thermal denaturation graphs of proteins; Cp vs. Temperature; thermogram and curve fit comparison." src="/files/ftp_upload/55262/55262fig3.jpg" data-altupdatedat="1747911167000" data-alt="Figure 3"> 
Figure 3: Analyzed DSC Data. These graphs are good representations of analyzed DSC data (i.e. after baseline subtraction and curve fitting). The blue line represents the thermogram after baseline subtraction, while the red line represents the curve with the best fit to the thermogram. (A) The Tm and ΔH for Protein 1 Sample # 12 are 80.16 °C and 1.69 x 106 cal/mol respectively. (B) The Tm and ΔH for Protein 1 Sample# 13 are 80.15 °C and 1.71 x 106 cal/mol respectively. (C) The Tm and ΔH for Protein 2 Sample # 21 are 75.01 °C and 4.08 x 106 cal/mol respectively. (D) The Tm and ΔH for Protein 2 Sample # 22 are 75.67 °C and 4.22 x 106 cal/mol respectively. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55262/55262fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Protein thermal stability, graph, Cp vs. Temperature, two protein samples, calorimetry results." src="/files/ftp_upload/55262/55262fig4.jpg" data-altupdatedat="1747911167000" data-alt="Figure 4"> 
Figure 4: An Incomplete Thermogram. Raw data collect for Protein 1 analyzed at an inadequate temperature range. The final temperature of experiment was set to 90 °C which did not accommodate the entire transition profile of the protein as compared to the experiment for Figure 2A which was set to 120 °C. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55262/55262fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Protein thermograms with curve fitting; heat capacity vs. temperature; differential scanning." src="/files/ftp_upload/55262/55262fig5.jpg" data-altupdatedat="1747911167000" data-alt="Figure 5"> 
Figure 5: Analyzed Data Showing the Effect of Chemical Detoxification on the Tertiary Structure of Protein 1. (A) Protein 1 is a toxin in its native conformation and has its Tm at 56.84 °C and ΔH at 2.57 x 105 cal/mol. (B) The detoxified form of Protein 1 (i.e. toxoid) has Tm and ΔH values of 81.01 °C and 1.89 x 106 cal/mol respectively. Thus, it can be concluded that the detoxification step introduced some form of variation to the structural conformation of Protein 1 which confers greater stability (higher Tm) to its detoxified form. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55262/55262fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Thermal analysis graphs showing Cp vs. temperature, curve fitting, protein stability data comparison." src="/files/ftp_upload/55262/55262fig6.jpg" data-altupdatedat="1747911167000" data-alt="Figure 6"> 
Figure 6: Analyzed Data Showing the Effect of Storage Conditions on the Conformation of Protein 3. These graphs illustrate the effect of storage temperature (2 - 8 °C) on the stability and tertiary structure of Protein 3 over 30 weeks. The Tm and ΔH values for Protein 3 at the 8th (A) and 38th week (B) of storage are given in Table 1 below. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55262/55262fig6large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table fo:keep-together.within-page="1">
	<tbody>
		<tr>
			<td>Sample</td>
			<td>Tm 1 (°C)</td>
			<td>∆H 1 (cal/mol)</td>
			<td>Tm 2 (°C)</td>
			<td>∆H 2 (cal/mol)</td>
			<td>Tm 3 (°C)</td>
			<td>∆H 3 (cal/mol)</td>
		</tr>
		<tr>
			<td>Protein 3 stored at 2-8 °C for 8 weeks</td>
			<td>61.91</td>
			<td>1.71 x 105</td>
			<td>75.54</td>
			<td>2.17 x 105</td>
			<td>90.29</td>
			<td>4.17 x 105</td>
		</tr>
		<tr>
			<td>Protein 3 stored at 2-8 °C for 38 weeks</td>
			<td>61.87</td>
			<td>1.66 x 105</td>
			<td>75.18</td>
			<td>1.46 x 105</td>
			<td>90.22</td>
			<td>5.76 x 105</td>
		</tr>
	</tbody>
</table>
Table 1: Tm and ΔH Values for Protein 3 at the 8th and 38th Week of storage at 2 - 8 °C. Although the Tm values at both time points are similar, the difference in the ΔH values indicates that the tertiary structure of Protein 3 has degraded over 30 weeks under the specified storage condition.

Watch this Scientific Journal Video about Differential Scanning Calorimetry Ã¢â‚¬â€ A Method for Assessing the Thermal Stability and Conformation of Protein Antigen at JoVE.com

Differential Scanning Calorimetry &#8212; A Method for Assessing the Thermal Stability and Conformation of Protein Antigen

Differential scanning calorimetry measures the thermal transition temperature(s) and total heat energy required to denature a protein. Results obtained are used to assess the thermal stability of protein antigens in vaccine formulations.

Differential scanning calorimetry (DSC) is an analytical technique that measures the molar heat capacity of samples as a function of temperature. In the ...

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38.8K Views.  Sanofi Pasteur Limited.  Differentiële scanning calorimetrie meet de thermische overgangstemperatuur (s) en de totale warmte-energie nodig is om een ​​eiwit te denatureren. De resultaten worden gebruikt om de thermische stabiliteit van eiwitantigenen beoordelen vaccinformuleringen. 

Video: Differential Scanning Calorimetry — A Method for Assessing the Thermal Stability and Conformation of Protein Antigen

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.

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 ...

Designing Silk-silk Protein Alloy Materials for Biomedical Applications

Fibrous proteins display different sequences and structures that have been used for various applications in biomedical fields such as biosensors, nanomedicine, tissue regeneration, and drug delivery. Designing materials based on the molecular-scale interactions between these proteins will help generate new multifunctional protein alloy biomaterials with tunable properties. Such alloy material systems also provide advantages in comparison to traditional synthetic polymers due to the materials biodegradability, biocompatibility, and tenability in the body. This article used the protein blends of wild tussah silk (Antheraea pernyi) and domestic mulberry silk (Bombyx mori) as an example to provide useful protocols regarding these topics, including how to predict protein-protein interactions by computational methods, how to produce protein alloy solutions, how to verify alloy systems by thermal analysis, and how to fabricate variable alloy materials including optical materials with diffraction gratings, electric materials with circuits coatings, and pharmaceutical materials for drug release and delivery. These methods can provide important information for designing the next generation multifunctional biomaterials based on different protein alloys.

Blending is an efficient approach to generate biomaterials with a broad range of properties and combined features. By predicting the molecular interactions between different natural silk proteins, new silk-silk protein alloy platforms with tunable mechanical resiliency, electrical response, optical transparency, chemical processability, biodegradability, or thermal stability can be designed.

Fibrous proteins display different sequences and structures that have been used for various applications in biomedical fields such as biosensors, ...

Bioengineering

How to Stabilize Protein: Stability Screens for Thermal Shift Assays and Nano Differential Scanning Fluorimetry in the Virus-X Project

The Horizon2020 Virus-X project was established in 2015 to explore the virosphere of selected extreme biotopes and discover novel viral proteins. To evaluate the potential biotechnical value of these proteins, the analysis of protein structures and functions is a central challenge in this program. The stability of protein sample is essential to provide meaningful assay results and increase the crystallizability of the targets. The thermal shift assay (TSA), a fluorescence-based technique, is established as a popular method for optimizing the conditions for protein stability in high-throughput. In TSAs, the employed fluorophores are extrinsic, environmentally-sensitive dyes. An alternative, similar technique is nano differential scanning fluorimetry (nanoDSF), which relies on protein native fluorescence. We present here a novel osmolyte screen, a 96-condition screen of organic additives designed to guide crystallization trials through preliminary TSA experiments. Together with previously-developed pH and salt screens, the set of three screens provides a comprehensive analysis of protein stability in a wide range of buffer systems and additives. The utility of the screens is demonstrated in the TSA and nanoDSF analysis of lysozyme and Protein X, a target protein of the Virus-X project.

A protocol is presented to rapidly test the thermal stability of proteins in a variety of conditions through thermal shift assays and nano differential scanning fluorimetry. Buffer systems, salts and additives, together comprising three unique stability screens, are assayed with proteins to identify suitable buffers for functional and structural studies.

The Horizon2020 Virus-X project was established in 2015 to explore the virosphere of selected extreme biotopes and discover novel viral proteins. To ...

Nano-Differential Scanning Fluorimetry for Screening in Fragment-based Lead Discovery

Thermal shift assays (TSAs) examine how the melting temperature (Tm) of a target protein changes in response to changes in its environment (e.g., buffer composition). The utility of TSA, and specifically of nano-Differential Scanning Fluorimetry (nano-DSF), has been established over the years, both for finding conditions that help stabilize a specific protein and for looking at ligand binding by monitoring changes in the apparent Tm. This paper presents an efficient screening of the Diamond-SGC-iNEXT Poised (DSi-Poised) fragment library (768 compounds) by the use of nano-DSF, monitoring Tm to identify potential fragment binding. The prerequisites regarding protein quality and concentration for performing nano-DSF experiments are briefly outlined followed by a step-by-step protocol that uses a nano-liter robotic dispenser commonly used in structural biology laboratories for preparing the required samples in 96-well plates. The protocol describes how the reagent mixtures are transferred to the capillaries needed for nano-DSF measurements. In addition, this paper provides protocols to measure thermal denaturation (monitoring intrinsic tryptophan fluorescence) and aggregation (monitoring light back-scattering) and the subsequent steps for data transfer and analysis. Finally, screening experiments with three different protein targets are discussed to illustrate the use of this procedure in the context of lead discovery campaigns. The overall principle of the method described can be easily transferred to other fragment libraries or adapted to other instruments.

Monitoring changes in the melting temperature of a target protein (i.e., thermal shift assay, TSA) is an efficient method for screening fragment libraries of a few hundred compounds. We present a TSA protocol implementing robotics-assisted nano-Differential Scanning Fluorimetry (nano-DSF) for monitoring intrinsic tryptophan fluorescence and light back-scattering for fragment screening.

Thermal shift assays (TSAs) examine how the melting temperature (Tm) of a target protein changes in response to changes in its environment (e.g., buffer ...

A Package of Established Analytical Tools to Investigate the Solid-State Alteration of Lipid-Based Excipients

Lipid-based excipients (LBEs) are low-toxic, biocompatible, and natural-based, and their application supports the sustainability of pharmaceutical manufacturing. However, the major challenge is their unstable solid-state, affecting the stability of the pharmaceutical product. Critical physical properties of lipids for their processing-such as melt temperature and viscosity, rheology, etc.-are related to their molecular structure and their crystallinity. Additives, as well as thermal and mechanical stress involved in the manufacturing process, affect the solid-state of lipids and thus the performance of pharmaceutical products thereof. Therefore, understanding the alteration in the solid-state is crucial. In this work, the combination of powder x-ray diffraction and differential scanning calorimetry (DSC) is introduced as the gold standard for the characterization of lipids' solid state. X-ray diffraction is the most efficient method to screen polymorphism and crystal growth. The polymorphic arrangement and the lamella length are characterized in the wide- and small-angle regions of x-ray diffraction, respectively. The small-angle x-ray scattering (SAXS) region can be further used to investigate crystal growth. Phase transition and separation can be indicated. DSC is used to screen the thermal behavior of lipids, estimate the miscibility of additives and/or active pharmaceutical ingredients (API) in the lipid matrix, and provide phase diagrams. Four case studies are presented in which LBEs are either used as a coating material or as an encapsulation matrix to provide lipid-coated multiparticulate systems and lipid nanosuspensions, respectively. The lipid solid-state and its potential alteration during storage are investigated and correlated to the alteration in the API release. Qualitative microscopical methods such as polarized light microscopy and scanning electron microscopy are complementary tools to investigate micro-level crystallization. Further analytical methods should be added based on the selected manufacturing process. The structure-function-processability relationship should be understood carefully to design robust and stable lipid-based pharmaceutical products.

This publication shows the application of x-ray diffraction and differential scanning calorimetry as gold standards for investigating the solid-state of lipid-based excipients (LBEs). Understanding the solid-state alteration in LBEs and its effect on the performance of pharmaceutical products thereof is the key factor for manufacturing robust lipid-based dosage forms.

Lipid-based excipients (LBEs) are low-toxic, biocompatible, and natural-based, and their application supports the sustainability of pharmaceutical ...

Chemistry

High-Throughput Thermal Shift Assays for Protein-Ligand Interactions

Utilizing Thermal Shift Assay to Probe Substrate Binding to Selenoprotein O

Defining the biological importance of proteins with unknown functions poses a significant obstacle in understanding cellular processes. Although bioinformatic and structural predictions have contributed to the study of unknown proteins, in vitro experimental validations are often hampered by the optimal conditions and cofactors required for biochemical activity. Cofactor binding is not only essential for the activity of some enzymes but may also enhance the thermal stability of the protein. One practical application of this phenomenon lies in utilizing the change in thermal stability, as measured by alterations in the protein's melting temperature, to probe ligand binding. 
Thermal shift assay (TSA) can be used to analyze the binding of different ligands to the protein of interest or find a stabilizing condition to perform experiments such as X-ray crystallography. Here we will describe a protocol for TSA utilizing the pseudokinase, Selenoprotein O (SelO), for a simple and high-throughput method for testing metal and nucleotide binding. In contrast to canonical kinases, SelO binds ATP in an inverted orientation to catalyze the transfer of AMP to the hydroxyl side chains of proteins in a posttranslational modification known as protein AMPylation. By leveraging the shift in the melting temperatures, we provide crucial insights into the molecular interactions underlying SelO function.

Author Spotlight: Advancing Structural and Biochemical Studies of Proteins Through Thermal Shift Assays

Here, we present the thermal shift assay, a high-throughput, fluorescence-based technique used to investigate the binding of small molecules to proteins of interest.

Defining the biological importance of proteins with unknown functions poses a significant obstacle in understanding cellular processes. Although ...

Determination of Protein-ligand Interactions Using Differential Scanning Fluorimetry

A wide range of methods are currently available for determining the dissociation constant between a protein and interacting small molecules. However, most of these require access to specialist equipment, and often require a degree of expertise to effectively establish reliable experiments and analyze data. Differential scanning fluorimetry (DSF) is being increasingly used as a robust method for initial screening of proteins for interacting small molecules, either for identifying physiological partners or for hit discovery. This technique has the advantage that it requires only a PCR machine suitable for quantitative PCR, and so suitable instrumentation is available in most institutions; an excellent range of protocols are already available; and there are strong precedents in the literature for multiple uses of the method. Past work has proposed several means of calculating dissociation constants from DSF data, but these are mathematically demanding. Here, we demonstrate a method for estimating dissociation constants from a moderate amount of DSF experimental data. These data can typically be collected and analyzed within a single day. We demonstrate how different models can be used to fit data collected from simple binding events, and where cooperative binding or independent binding sites are present. Finally, we present an example of data analysis in a case where standard models do not apply. These methods are illustrated with data collected on commercially available control proteins, and two proteins from our research program. Overall, our method provides a straightforward way for researchers to rapidly gain further insight into protein-ligand interactions using DSF.

Differential scanning fluorimetry is a widely used method for screening libraries of small molecules for interactions with proteins. Here, we present a straightforward method to extend these analyses to provide an estimate of the dissociation constant between a small molecule and its protein partner.

A wide range of methods are currently available for determining the dissociation constant between a protein and interacting small molecules. However, most ...

Biology

High-Sensitivity Detection of Compound-Protein Binding Using Fluorescence

Detection of CD40 Protein-Umbelliferone Interaction via Differential Scanning Fluorescence

The investigation of interactions between different molecules is a crucial aspect of understanding disease pathogenesis and screening for drug targets. Umbelliferone, an active ingredient in Tibetan medicine Vicatia thibetica, exhibits an immunomodulatory effect with an unknown mechanism. The CD40 protein is a key target in the immune response. Therefore, this study employs the principle of differential scanning fluorescence technology to analyze the interactions between CD40 protein and umbelliferone using fluorescent enzyme markers. Initially, the stability of the protein fluorescent orange dye was experimentally verified, and the optimal dilution ratio of 1:500 was determined. Subsequently, it was observed that the temperature melting (Tm) value of CD40 protein tended to decrease with an increase in concentration. Interestingly, the interaction between CD40 protein and umbelliferone was found to enhance the thermal stability of CD40 protein. This study represents the first attempt to detect the binding potential of small molecule compounds and proteins using fluorescence microplates and fluorescent dyes. The technique is characterized by high sensitivity and accuracy, promising advancements in the fields of protein stability, protein structure, and protein-ligand interactions, thus facilitating further research and exploration.

Author Spotlight: Streamlining PCR Methods for Enhanced Accessibility and Efficiency

This protocol describes a unique method for detecting the binding between compounds and protein molecules, offering the advantages of minimal protein sample loss and high data accuracy.

The investigation of interactions between different molecules is a crucial aspect of understanding disease pathogenesis and screening for drug targets. ...

Medicine

Differential Scanning Calorimetry

Source: Danielle N. Beatty and <a href="https://www-jove-com.remotexs.ntu.edu.sg/author/Taylor+D._Sparks">Taylor D. Sparks</a>, Department of Materials Science and Engineering, The University of Utah, Salt Lake City, UT
Differential scanning calorimetry (DSC) is an important measurement to characterize thermal properties of materials. DSC is used primarily to calculate the amount of heat stored in a material as it heats up (heat capacity) as well as the heat absorbed or released during chemical reactions or phase changes. However, measurement of this heat can also lead to the calculation of other important properties such as glassy transition temperature, polymer crystallinity, and more.
Due to the long, chain-like nature of polymers it is not uncommon for polymer strands to be entangled and disordered. As a result, most polymers are only partially crystalline with the remainder of the polymer being amorphous. In this experiment we will utilize DSC to determine polymer crystallinity.

Differential Scanning Calorimetry of Polymers

Source: Danielle N. Beatty and Taylor D. Sparks, Department of Materials Science and Engineering, The University of Utah, Salt Lake City, UT
Differential ...

JoVE Science Education

Engineering

Materials Engineering

Using Differential Scanning Calorimetry to Measure Changes in Enthalpy

Source: Laboratory of Dr. Terry Tritt &#8212; Clemson University
Differential Scanning Calorimetry (DSC) is a method of thermodynamic analysis based on heat-flux method, wherein a sample material (enclosed in a pan) and an empty reference pan are subjected to identical temperature conditions. The energy difference that is required to maintain both the pans at the same temperature, owing to the difference in the heat capacities of the sample and the reference pan, is recorded as a function of temperature. This energy released or absorbed is a measure of the enthalpy change (&#916;&#919;) of the sample with respect to the reference pan.

Differential Scanning Calorimetry: Measuring Enthalpy Changes

Source: Laboratory of Dr. Terry Tritt &#8212; Clemson University
Differential Scanning Calorimetry (DSC) is a method of thermodynamic analysis based on ...

Differential Scanning Calorimetry — A Method for Assessing the Thermal Stability and Conformation of Protein Antigen

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