You could also try running the experiment at a different temperature or pH. Also, make absolutely certain that there is no difference between the buffers of the two solutions. If the ligand is a salt, consider using a different counterion, because dissociation of  the counterion can give a heat signal.

@Bilge Ercan and Adam B Shapiro

Thank you both for reply. Both protein and ligand were dissolved in PBS followed by dialysis. The working conc. of protein and ligand were 0.4mM and 20mM respectively. The ligand affinity is low so, i have gradually increased the conc. to 20mM where i could see a profile. Here, i wanted to subtract the heat of dilution of ligand.

Ligand does not consists of salt. I have performed titration at three different temperatures (298K, 303K and 310K). I could see the similar profile for three of these expts. However, when i fit the raw data by subtracting the average of last three titrations (considering as heat of dilution of ligand), the affinity, dH, dS and n values are as given

Ka       2.8e+04    1.9e+04     9.1e+03

dH      0.072         0.089         0.138

dS      85.58         82.52         76.28

n        7.62              9.01           8.54

Is it alright if i subtract the average of last three titrations, as it is one of the recommended procedures?

Are you concerned about a ligand binding stoichiomery of 7.6-9.0?

yes. I would repeat the same experiment two more times to make sure the obtained result. But how about subtraction of heat of dilution?

I don't know the answer from experience, but it occurs to me that the heat of dilution measurement may be different at the start of a titration than at the end because the dilution factor is greater at the beginning than at the end. If that is true, then a better way to subtract the heat of dilution is to do a blank titration. Unfortunately, the precision of the subtraction will be problematic if two large numbers are subtracted to obtain a small difference. To improve precision, you should do several replicates and subtract the averages.

@ Adam B Shapiro: Thank you.

Dilution heats are most often due to either buffer mismatch or ligand dissociation. In the first case the buffer composition (including pH) of the cell and syringe samples are different - the bigger the difference the larger the heat. The type of buffer does not really matter - the recommendation about PBS in the first answer actually refers to the buffer ionization heats (nothing to do with dilution). Best way to match the buffers is co-dialysis assuming both protein and ligand are large enough for that. In the second case - dissociation, the ligand forms oligomers (dimer for example) at the high concentrations in the syringe and these dissociate upon injection (dilution). This is an equilibrium process by itself and cannot be simply subtracted from the protein-ligand titration curve. How to distinguish between the 2 – do a control experiment, inject ligand into blank (buffer). The simple buffer mismatch tends to be a constant (or slightly sloped) offset that can be easily subtracted from the data. The dissociation will look more or less curved (depending on the diss. Kd). The best practice is to try to minimize the dilution heats by proper sample preparation. If this does not work you can try to subtract them from the data no matter how large they are – assuming mismatch I would do a linear fit of the control titration and subtract this fit from the protein-ligand titration. I am not sure how this type of analysis works in practice on the TA software, on the MicroCal (Malvern Instruments) data analysis this is very straight forward and in the case of the new PEAQ software it is automatic. Since you are dealing with low affinity sample I’d recommend the following white paper: http://www.malvern.com/en/support/resource-center/Whitepapers/WP140701-studying-low-affinity-fragments-of-ligands-by-itc.aspx . More general ITC method articles are:  http://faculty.missouri.edu/~tannerjj/bchem/fbdd-pdfs/perozzo-%20thermodynamics%20of%20proteins.pdf and the attached.

http://www.malvern.com/en/support/resource-center/Whitepapers/WP140701-studying-low-affinity-fragments-of-ligands-by-itc.aspx

Isothermal Titration Calorimetry (ITC) is a technique used to measure the heat released or absorbed during a chemical reaction or binding event, providing insights into the thermodynamics of the interaction. When considering the heat of reaction (enthalpy change, Δ�ΔH) in ITC experiments, the heat of dilution can be a significant factor that needs to be accounted for, especially if it interferes with or masks the true enthalpic signal of the interaction of interest.

Neglecting or correcting for the heat of dilution involves a few strategies:

1. Baseline Correction

• Perform a control experiment by titrating the ligand into the buffer (or solvent) alone, without the macromolecule or reaction partner present. This measures the heat of dilution of the ligand itself. Subtracting this baseline from your experimental data involving the actual reaction partner will correct for the heat of dilution.

2. Use of an Appropriate Buffer

• Choose a buffer that minimizes the heat of dilution. This might involve testing several buffers to identify one that produces minimal heat upon dilution of your reactants. The choice of buffer can significantly affect the heat of dilution and, consequently, the accuracy of your measurements.

3. Concentration Optimization

• Optimize the concentrations of the reactants. By using higher concentrations, the relative contribution of the heat of dilution to the total heat observed can be minimized. However, this needs to be balanced with the potential for non-ideal behavior at high concentrations.

4. Incremental Titration

• Use small increments during titration. Smaller aliquots can help in reducing the magnitude of the heat of dilution per injection, making it easier to distinguish from the heat of the reaction. However, this approach requires careful analysis to ensure the heat of reaction is still accurately measurable.

5. Mathematical Correction

• Apply mathematical models or corrections that account for the heat of dilution. This can be complex and requires a good understanding of the thermodynamics involved in both the reaction and the dilution processes. Advanced data analysis software often has features to assist in making these corrections.

6. Experimental Design

• Design your experiment to minimize the impact of the heat of dilution. This could involve adjusting the volume of the titrant or the concentration of your solutions to ensure that the dilution effect is as small as possible compared to the heat of reaction.

7. Data Analysis Software

• Utilize data analysis software specifically designed for ITC data, which often includes options to correct for the heat of dilution. These software tools can automatically apply the necessary corrections based on control experiments and mathematical models.

By implementing these strategies, you can effectively minimize or correct for the heat of dilution in your ITC experiments, ensuring that the measured heat changes more accurately reflect the heat of reaction or binding events of interest.

l This protocol list might provide further insights to address this issue.