Open access peer-reviewed chapter

Calorimetry to Quantify Protein-Ligand Binding

Written By

Salerwe Mosebi

Submitted: 12 January 2022 Reviewed: 31 January 2022 Published: 18 May 2022

DOI: 10.5772/intechopen.102959

From the Edited Volume

Applications of Calorimetry

Edited by José Luis Rivera-Armenta and Cynthia Graciela Flores-Hernández

Chapter metrics overview

143 Chapter Downloads

View Full Metrics


Isothermal titration calorimetry (ITC) is the preferred method used to study biochemical reactions like protein-ligand binding due to its sensitivity, accuracy, and precision. ITC measures directly the heat absorbed or released (∆H) associated with a given binding process. A typical ITC experiment allows the dissection of the binding energy of a reaction into ligand-enzyme association constant (Ka), change in enthalpy (∆H), change in entropy (∆S), change in Gibbs-free energy (∆G), and the stoichiometry of association (N). The change in heat capacity (∆Cp) is obtained from the measurements of binding enthalpy over a range of temperatures. The magnitude and signs of the thermodynamic parameters that were obtained provide insight into the nature of interactions involved in the binding process. The strength of interaction is thermodynamically favorable is determined by the Gibbs free energy. ∆G is an important thermodynamic descriptor of a binding reaction since it dictates the binding affinity and is in turn defined by the enthalpy and entropy changes expressed in the following equation: ∆G = ∆H–T∆S. Up-close, this reflects the contradistinctions of two thermodynamic effects at a molecular level—the propensity to drop to lower energy (bond formation, negative ∆H), counterbalanced by the innate thermal Brownian motion’s destructive characteristic (bond breakage, positive ∆S).


  • isothermal titration calorimetry
  • binding energy
  • association constant
  • entropy change
  • enthalpy change
  • heat capacity

1. Introduction

The completion of the human genome project over 18 years ago has catapulted the number of novel targets for drug development to great heights. Many of these targets belong to protein families with homologous structures and similar binding pockets, which are crucial in regulating pathways and interaction networks describing cell function and inter-relation. It is also apparent that the basis of molecular recognition in drug discovery, signal-transduction, and protein-ligand complexes requires complete structural and thermodynamic dissection of macromolecular interactions involved. Several techniques (fluorescence, absorbance, nuclear magnetic resonance, surface plasmon resonance, biolayer interferometry, and ultracentrifugation) have been used as premier tools for characterizing interactions of biomolecules. These techniques can only determine the binding affinity constant (Ka) and indirectly derive other thermodynamic parameters. However, due to its sensitivity, accuracy, and precision, isothermal titration calorimetry (ITC) is the most rigorous and preferred method applied in a wide range of chemical and biochemical reactions. ITC has the advantage of directly quantifying the binding energetics of biological processes that include but not limited to protein–protein binding, protein-ligand binding, protein-DNA binding, protein-carbohydrate binding, protein-lipid binding, and antigen–antibody binding. ITC does this by measuring, directly and in real-time, the heat absorbed or released (∆H) associated with a given binding process. A typical ITC experiment allows the dissection of binding energy of a reaction into ligand-enzyme association constant or binding affinity (Ka), change in enthalpy (∆H), change in entropy (∆S), change in Gibbs free energy (∆G), the stoichiometry of association or number of binding sites (N), and the change in heat capacity (∆Cp) obtained from measurements of binding enthalpy over a range of temperature. More importantly, ITC can be used to determine very low (103 M−1) to very high association constants (1012 M−1) without the need to use labels or immobilization of the binding components.


2. Fundamental principles of the ITC technique

A detailed description of the instrument and technique can be found elsewhere in the literature [1, 2, 3, 4, 5]. Briefly, the titration calorimeter consists of the injector system, adiabatic shield, and matched reference and sample cells (see Figure 1a). There is a self-stirring padded injection syringe and the thermostatic and feedback power systems that are computer-controlled. This instrument measures in real-time the thermal power that occurs when a solution in a syringe is titrated into a sample cell. In a typical ITC instrument, a pair of cylindrical cells (referred to as sample cell and reference cell) with volumes ranging from 200 to 1400 μl are present and contain analyte solution and reference buffer or water, respectively [6, 7]. The thermostated adiabatic shield ensures that no heat exchange occurs between the cells and the surroundings [2]. The two cells are maintained at a constant and identical temperature by a feedback system that supplies thermal power continuously. In the event of a reaction in the sample cell usually accompanied by heat (exothermic reaction), the system ensures that the feedback power is withdrawn in order to retain thermal equilibrium between the cells. The feedback power supplied or withdrawn by electric resistive heaters located on the outer surfaces of the sample and reference cells to minimize temperature imbalances upon ligand injection is measured and converted into the heat of interaction. A sequence of injections is programmed and the ligand solution is injected at regular intervals into the sample cell through an automated injection syringe, which is stirred by rotation of the paddle-shaped syringe. After each injection (typically between 1 and 20 μl), the composition inside the sample cell changes causing the rearrangement of populations and complex formation [5]. Accordingly, as the series of injections continues, the system will experience various states of equilibrium each differing in composition. The heat released or absorbed with each injection corresponds to the increase in interacting species’ concentration (as the reaction advances), and it is determined by the integration of the region under the deflection signal measured (amount of heat per unit of time provided to maintain thermal equilibrium in the sample and reference cells) [5]. If the binding between the injectant and the analyte is exothermic, this will result in the reduction in the power supplied by the feedback heater to maintain a constant temperature. On the other hand, if the binding is endothermic, there will be an increase in feedback power. At the end of the experiment, when no further heat is released or absorbed in the sample cell and saturation of the macromolecule is reached and it is possible to estimate Ka, ∆H, and N (independent variables). A typical result output of an ITC instrument is the feedback power measured as a function of time as shown in Figure 1b. The top panel represents the sequence of peaks as the solution in the syringe is injected into the analyte in the sample cell. The observed signal is the additional power that needs to be supplied or removed during the course of the experiment to keep a constant temperature in the sample cell and equal to the reference cell temperature. The reaction shown is that of an endothermic reaction, with an integrated heat plot in the bottom panel. Consequently, the areas under each peak, derived from per mole of ligand injected in each injection, are then plotted against the molar ratio of the total concentration of ligand to protein molecule concentration in the sample cell to obtain the following independent thermodynamic parameters: binding affinity, binding enthalpy, and the stoichiometry of binding. Notably, if two binding processes are characterized by different enthalpic and entropic terms and have the same Gibbs free energy of binding, they correspond to different binding modes, and therefore, the main underlying intermolecular interactions are different.

Figure 1.

(A) A schematic representation of the ITC instrument setup, showing the sample and reference cells enclosed by a thermostated jacket. (B) an example of an ITC assay.


3. Protein-ligand binding energetics

As mentioned before, a typical ITC experiment allows the thermodynamic dissection of binding energy of a reaction into (Ka), (∆H), (∆S), (∆G), (N), and (∆Cp). Importantly, the magnitude and signs of the thermodynamic parameters obtained give us clues into the nature of interactions involved in the binding process, for example, the strength of the interaction and whether or not it is thermodynamically favorable is determined by the Gibbs free energy. If one ponders on the binding reaction under equilibrium conditions, where a macromolecule (P, protein) binds another molecule (L, ligand):


And if you assume that only one binding site is available, the association constant, Ka, which is inversely proportional to the dissociation constant, Kd, one is then able to determine the partition of the reactant molecules into free and bound species according to Eq. (2) below:


The Gibbs free energy change of binding is an important thermodynamic descriptor of a binding reaction since it dictates the binding affinity or association constant:


where R is the universal gas constant (8.314 J/mol/K), T is the temperature in kelvin, and Ka is the equilibrium binding constant. ∆G is in turn defined by the enthalpy and entropy changes and is expressed in the following equation:


At the molecular level, this reflects the contradistinctions of two thermodynamic effects at a molecular level—the propensity to drop to lower energy (bond formation, negative ∆H), counterbalanced by the innate thermal (Brownian) motion’s destructive characteristic (bond breakage, positive ∆S) [8].

Since the native state of a protein exists as an ensemble of conformational states, the energy of stabilization of protein structure will not be evenly distributed throughout its three-dimensional structure [9]. There are regions of the protein with high stability constants (e.g., the hydrophobic core) and regions with low stability constants (e.g., loops and turns) with the majority of proteins exhibiting a dual character as originally observed for the HIV-1 protease [10, 11]. Since ligands with low molecular weight are in general not found attached to the exterior of proteins but are engulfed in crevices or binding pockets created by loops or other proteins’ structural elements, the number of interactions between ligand and protein is increased and concomitantly enshrouds a substantial surface area from the solvent [9]. This conformational rearrangement often permits the entry of the ligand into the binding site and its subsequent shielding from the solvent; hence, makes favorable contributions to the Gibbs free energy of binding. If the rearrangements are only transient and the free and the bound states of the protein are similar, only binding kinetics are affected. If, however, the free and bound conformations of the protein are different, the binding affinity will be affected [9]. The Gibbs free energy associated with the change in protein conformation from its free to its bound state is included in the computation of the effective Gibbs energy of binding and corresponding binding affinity:


where ∆bind is the Gibbs energy of binding obtained under the assumption that the free and bound states of the protein are the same, and ∆Gconf is the Gibbs energy associated with the change in protein conformation from its free to its bound form. In general, the Gibbs energy associated with a change from a less stable region to the bound conformation will be smaller than that associated with a change from a stable conformation to the bound conformation [9]. The presence of flexible regions in the protein molecule appears to facilitate the ligand-induced conformational changes if the putative binding site is not binding-competent in the ligand-free protein. The presence of regions with low stability also appears to provide a mechanism for achieving high binding affinity for low molecular weight ligands and serves as a starting point for the propagation of binding signals to distal sites [9].

Enthalpic and entropic contributions of the Gibbs energy originate from different types of interactions in the binding process. The binding enthalpy primarily reflects the energetic contribution of many individual interactions (hydrogen bonds, van der Waals interactions, polar, and dipolar interactions) between the ligand and the protein during the binding process, the conformational changes associated with binding, including interactions associated with the solvent. A negative (favorable) ∆H occurs when the interactions between the interacting molecules (e.g., hydrogen bond formation and van der Waals interactions) over-compensate the interactions of the individual molecules with the bulk solvent; otherwise, it will be positive (unfavorable, as for nonspecific hydrophobic interactions) [12]. The observed binding ∆H measured from a single ITC experiment often includes contributions not only from the actual binding event but also from the heat that is due to buffer ionization [13, 14, 15]. This is particularly true when the primary binding event is accompanied by the transfer of protons between the solvent and the protein-ligand complex. Thus, the determination of the intrinsic energetics of ligand binding requires experiments or measurements to be performed separately as a function of pH in buffers with different ionization enthalpies [13, 14, 16]. From this, pKa values of ionizable groups responsible for proton linkage in the free and bound states and the number of protons that are coupled to the binding reaction can be easily calculated [14].

The binding entropy refers to the degree of disorder accompanying complex formation. Two major terms that contribute to the change in entropy are the solvation and conformational entropies. Solvation entropy arises from the gain in degrees of freedom of water molecules that, prior to the binding, are localized on the surface of the binding molecules and are released to the bulk solvent upon binding due to partial or complete desolvation of the two binding molecules. The change in solvation entropy is favorable (positive) if the surfaces that are buried upon binding are predominantly hydrophobic. It, therefore, originates from the burial of hydrophobic surfaces upon binding. Entropically driven ligand binding reactions are characterized by a large positive entropic contribution driven by the tendency of the molecule to escape water rather than by favorable interactions with the target molecule. In addition, the burial of solvent-exposed molecular surface area upon binding also contributes substantially to the heat capacity change upon complex formation due to the release of electro-restricted water or “hydrophobic water” from the binding site [17]. The conformational entropy, on the other hand, arises from changes in conformational degrees of freedom experienced by both the protein and the ligand upon binding. It is usually negative (unfavorable) due to the loss of degrees of freedom resulting from the reduction in the number of accessible conformations and configurations of both molecules (protein and ligand) upon binding.


4. Protein-ligand quantification and lead drug design

Currently, the development of lead compounds or drug design is centered on the optimization of their binding affinity toward the intended target. The binding affinity of a compound can be improved by generating a favorable binding enthalpy, favorable solvation entropy, and by minimizing the unfavorable conformational entropy. It is evident that simultaneous optimization of the three factors can achieve extremely high affinity. However, it is entirely feasible to design lead compounds that bind to the intended target with similar affinity but with different binding mechanisms, i.e., entropically or enthalpically driven ligands [18]. Entropically driven ligand derives most of its binding energy from a nonspecific hydrophobic effect, i.e., by making interactions of the drug with the solvent unfavorable, whilst enthalpically driven ligand derives its binding energy by establishing strong and specific hydrogen bonds with the target. Drug designers have long aimed at developing conformationally constrained ligands preshaped to the geometry of the selected binding site, which completes entropy optimization. Accordingly, a conformationally constrained molecule that is preshaped to the target achieves affinity, specificity, and selectivity through hydrophobicity and shape complementarity [19]. Perhaps, the most significant example is given by the development of the first-generation HIV-1 protease (HIV-1 PR) inhibitors (saquinavir, ritonavir, indinavir, and nelfinavir). The binding of these HIV-1 protease inhibitors is entropically driven and their binding enthalpy is either unfavorable (saquinavir, indinavir, and nelfinavir) or only slightly favorable (ritonavir) [20, 21]. In all cases, the dominant force for binding is a large positive entropy change that originates primarily from the burial of a large hydrophobic surface upon binding [20]. Moreover, since shape and hydrophobicity are nonspecific interactions, a change in the target binding site would lead to a reduction in the binding affinity. A low binding affinity reflects the inability of these conformationally rigid ligands to adapt to changes in the target binding pocket due to mutations or naturally occurring polymorphisms arising from genetic diversity. Hydrophobicity has historically been the preferred variable in the pharmaceutical industry due to its ease of implementation [22].

An enthalpically driven binding indicates specific interactions between two binding partners and corresponds well with ligand specificity, selectivity, and adaptability. Alternatively, an unfavorable enthalpic binding energy is indicative of nonspecific interactions between the binding partners, which in turn affects the ligand’s specificity, selectivity, and adaptability. Despite apparent advantages of enthalpic interactions in achieving high affinity and improved selectivity, the optimization of the binding enthalpy has been more cumbersome to implement due to a large and unfavorable desolvation enthalpy of polar groups [23]. Generally, a polar group needs to make a strong interaction with the target in order to compensate for the desolvation enthalpy. Energetic contributions to binding affinity are not simply localized to the direct interactions between the molecules but contain interactions from structural and dynamic changes propagated throughout the protein, and from counter ions and hydrating water molecules located at the binding site. To be effective, an inhibitor needs to exhibit an extremely high affinity for the intended target and be mildly affected by mutations. Ideally, an inhibitor should have a binding affinity in the 1–50 pM range against the wild-type and be affected by mutations by a factor of 100 or less [24, 25, 26]. Compounds that achieve high binding affinity or that maximize binding affinity have been shown to combine or balance the favorable entropic and enthalpic contributions to the overall Gibbs energy of binding [27, 28, 29, 30].

Notably, drug design paradigms have, to a large extent, illustrated how the enthalpic or entropic character of inhibitors is not dependent on the intended target, and that it is possible to develop entropically as well as enthalpically optimized inhibitors against the same binding site (e.g., HIV-1 protease). It has, for example, taken over 10 years to optimize HIV-1 protease inhibitors from the entropically driven inhibitors to the new and more potent enthalpically driven inhibitors [21, 24, 31]. The second-generation HIV-1 protease inhibitor, KNI-764 (AG-1776) for example, achieves the highest affinity (Kd = 32 pM) to the HIV-1 protease with a binding enthalpy (∆H) of—7.6 kcal/mol and an entropic contribution (−T∆S) of −6.7 kcal/mol and can still afford the presence of certain flexible elements [21, 32]. The introduction of flexible asymmetrical functional groups in regions facing or in close proximity to mutation-prone areas of the protein provides adaptability to the inhibitor and low susceptibility to mutations [25, 26]. The increased conformational flexibility found in the second-generation HIV-1 protease inhibitors can also allow the inhibitor to compensate for the loss of interactions as a result of mutations in the target by burying a comparable or even larger surface area from the solvent [25].

New drug design strategies by calorimetric characterization have permitted the designers to recognize the nature of forces by which the HIV-1 proteins inhibitors bind the target primarily because these forces originate from different interactions. ITC was particularly crucial at the later stages since it gave a detailed description of the thermodynamic factors governing protein-inhibitor interactions essential for molecular recognition in HIV-1 protease binding and led to improvement in drug design. This task was also facilitated by structure-based algorithms able to predict the enthalpic and entropic consequences of introducing different functional groups in the lead compounds under investigation [9, 32]. Extensive studies using numerous techniques of molecular biology and the deepened understanding of drug-target at the molecular level have helped greatly in achieving rapid success in the area of drug development, especially in the treatment of AIDS [33, 34, 35, 36, 37, 38, 39, 40, 41, 42].


5. Experimental approaches to determining the protein-ligand binding energetics using ITC

ITC experiments can be performed to determine the binding affinity, binding enthalpy, Gibbs free energy of binding, and stoichiometry of different inhibitors to the wild-type HIV-1 (South African subtype C (C-SA) protease. Indinavir, used in this study as an example, is an inhibitor that binds the wild-type HIV-1 protease with high affinity (with Ki ≤ 1 nM). Therefore, the typical titration experiments are not able to accurately determine the association constant, even though the enthalpic contributions can be measured with high precision. A solution to this challenge is to perform calorimetric displacement titrations that will allow for the calculation of the binding affinity and enthalpy, as reported previously [25, 26, 43]. This technique allows complete determination of binding thermodynamics of high-affinity ligands (Ka ≥ 109 M−1) that are beyond the range of determination by direct titration. In calorimetric displacement titrations, the high-affinity inhibitor is titrated into a protease sample prebound to a weaker binding inhibitor (acetyl-pepstatin), a well-characterized inhibitor of lower binding affinity and unfavorable binding enthalpy [11]. The selection of a weak binding inhibitor with a binding isotherm of opposite sign (positive ∆H) produces a larger signal during the displacement reaction due to the displacement of the weaker binding inhibitor by an inhibitor yielding an exothermic isotherm (negative ∆H). As depicted in Figure 2, in the presence of the weak binding inhibitor, the apparent binding constant for the inhibitor which binds tightly, Kapp, falls within the range required for ITC determination. Kapp is given by Eq. (6) below:

Figure 2.

Overview of a displacement titration assay for HIV-1 protease. The binding affinity of ritonavir, Ka, is beyond the limit of direct calorimetric determination. The displacement titration experiment is performed in the presence of the weak binding inhibitor acetyl-pepstatin (KB = 2.0 × 106 M−1).


where B is the concentration of the weaker binding inhibitor. In addition, Kapp can be lowered to the desired level by increasing the concentration of the weak inhibitor. In addition, the binding isotherm, in this case, has sufficient curvature to allow for the calorimetric measurement of the apparent binding affinity of the stronger binding ligand [43]. Two calorimetric titrations need to be performed to work out the binding competition equations and calculate the association constant and enthalpic contributions of the tight-binding inhibitor: (1) titration of the weak binding inhibitor into the protease and (2) titration of the inhibitor of interest into the protease-(weak binding inhibitor) complex. The competition experiments were also performed at pH 5.0 using an acetate buffer with negligible binding enthalpy to minimize any proton coupling effect on the observed binding enthalpy [25].

Figure 3 shows typical displacement titrations for active site inhibitors of the wild-type C-SA HIV-1 protease in the presence of acetyl-pepstatin, pH 5.0. Each peak in the top panel represents the displacement of a weaker binding inhibitor (acetyl-pepstatin) from the active site of the protein by the tight-binding inhibitor (e.g., indinavir, with high binding affinity). As the titration progresses, the area under each peak becomes smaller due to increased occupancy of the available binding sites on the enzyme by the inhibitor of interest. The bottom panel in the figure shows the calorimetric binding isotherm obtained by plotting integrated heats obtained after each injection as a function of inhibitor concentration of interest per protein dimer. Figure 3a shows the integrated heats for the above peaks plotted against the molar ratio of acetyl-pepstatin to HIV-1 protease molecule. The solid line through the data represents the best fit using a one-site binding model. For the wild-type HIV-1 C-SA protease, the experimental data fit best to a single-site displacement binding model; i.e., with the stoichiometry of 1:1 as shown in Figure 3b. The binding isotherms are monophasic with a sigmoidal fit to the data representing the decrease in available binding sites on the protein as the reaction progresses to completion. Used as a reference here, the clinical inhibitor, indinavir, binds to the wild-type C-SA HIV-1 protease with high binding affinity, Ka, of 0.2 × 109 M−1 in a process strongly favored by entropic contributions, contributing about 12 kcal/mol to the overall Gibbs energy of binding at 25°C. At 25°C, the stoichiometry of binding for indinavir is 1.0 interpreted as one molecule of the inhibitor bound per dimer of HIV-1 protease and is consistent with crystallographic data [44, 45, 46, 47, 48]. Accordingly, the binding of indinavir is favored by entropic contributions of −15.0 kcal/mol, whereas its binding to the wild-type HIV-1 C-SA protease is characterized by a positive (unfavorable) enthalpy change of 2.70 kcal/mol. This is in agreement with the thermodynamic data obtained previously, which showed entropically controlled binding affinities and unfavorable or slightly favorable binding enthalpies [20, 49, 50]. Interestingly, for indinavir and other HIV-1 protease inhibitors like saquinavir, ritonavir, and nelfinavir, entropy (−T∆S) contributions as large as −16 kcal/mol, have also been shown by others to be required to compensate for the unfavorable binding enthalpies [20, 49].

Figure 3.

(A) A representative calorimetric profile of the titration of the wild-type HIV-1 C-SA protease with acetyl-pepstatin. Titrations of acetyl-pepstatin (300 μM) into protease solution (20 μM). (B) ITC displacement calorimetric titration of indinavir (250 μM) into a solution of the wild-type HIV-1 C-SA protease (20 μM) prebound to acetyl-pepstatin (200 μM).


6. Determination of the heat capacity change of a binding reaction

Although with a single ITC experiment, one is able to gain insights regarding the binding constant, binding enthalpy, binding entropy, stoichiometry of the reaction, and the Gibbs free energy of binding, another important parameter—the change in heat capacity (ΔCp) upon binding can be obtained by performing the experiment at different temperatures and constant pressure. By applying Eq. (7) below, one can determine its value:


where 𝜕ΔH is the enthalpic change of binding at different temperatures (𝜕T) and ΔCp is the change in heat capacity or slope obtained from plotting ΔH versus temperature. The heat capacity of a binding reaction is indicative of the burial of polar and nonpolar surfaces upon binding [51, 52, 53]. ΔCp on an ITC instrument is typically obtained by measuring the enthalpic contributions of binding from 10–35°C at 5°C intervals without changing buffer and pH conditions. Although reports of the binding processes between a protein and a ligand have shown a negative and < 1 kcal/Kmol ΔCp, the binding of two macromolecules (e.g., antigen–antibody) can induce higher heat capacity change, which is reflective of the burial of a larger solvent-accessible surface area as a result of the binding [26].


7. Conclusions

This chapter demonstrated the important role of calorimetry, in particular, isothermal titration calorimetry in dissecting the binding profile of two interacting species (e.g., a macromolecule and a ligand). It has obvious applications in drug development as it can be used for the characterization and optimization of lead compounds due to a wealth of thermodynamic information that is obtained from a single experiment. Some of the notable successes are in the lead optimization of HIV drugs exemplified by the HIV-1 protease discussed above. To this day, ITC remains a favored technique that can accurately characterize the interaction between the macromolecules and their biologically relevant binding partners. It is also uniquely positioned to assist us in getting a deepened thermodynamic understanding of the important biological processes in living systems like metabolism, active transport, biosensing, regulation, signal transduction, and integration to name a few.



The author would like to acknowledge the University of South Africa and the University of the Witwatersrand for the financial assistance and provision of resources and infrastructure needed to complete this work. The work was also supported by a grant from the National Research Foundation (Grant 121281 to S.M). Lastly, the author would like to thank Prof. Yasien Sayed from the University of the Witwatersrand for the invaluable supervisory role he played on the project.


Conflict of interest

The author declares no conflict of interest.


  1. 1. McKinnon IR, Fall L, Parody-Morreale A, Gill SJ. A twin titration microcalorimeter for the study of biochemical reactions. Analytical Biochemistry. 1984;139:134-139. DOI: 10.1016/0003-2697(84)90398-1
  2. 2. Wiseman T, Williston S, Brandts JF, Lin LN. Rapid measurement of binding constants and heats of binding using a new titration calorimeter. Analytical Biochemistry. 1989;179:131-137. DOI: 10.1016/0003-2697(89)90213-3
  3. 3. Freire E. Isothermal titration calorimetry: Controlling binding forces in lead optimization. Drug Discovery Today: Technologies. 2004;3:295-299. DOI: 10.1016/j.ddtec.2004.11.016
  4. 4. Velazquez-Campoy A, Leavitt SA, Freire E. Characterization of protein-protein interactions by isothermal titration calorimetry. Methods in Molecular Biology. 2004;261:35-54. DOI: 10.1385/1-59259-762-9:035
  5. 5. Velazquez-Campoy A, Freire E. ITC in the post-genomic era…? Priceless. Biophysical Chemistry. 2005;115:115-124. DOI: 10.1016/j.bpc.2004.12.015
  6. 6. Malvern. Microcal ITC Systems: Understanding Biomolecular Interactions. Cambridge: Malvern; 2016
  7. 7. TA. Microcalorimetry: ITC and DSC. Newcastle, DE: TA Instruments; 2019
  8. 8. Cooper A. Thermodynamic analysis of biomolecular interactions. Current Opinion in Chemical Biology. 1999;3:557-563. DOI: 10.1016/s1367-5931(99)00008-3
  9. 9. Luque I, Freire E. Structural stability of binding sites: Consequences for binding affinity and allosteric effects. Proteins. 2000;4:63-71. DOI: 10.1002/1097-0134(2000)41:4+<63::aid-prot60>;2-y
  10. 10. Luque I, Todd MJ, Gomez J, Semo N, Freire E. Molecular basis of resistance to HIV-1 protease inhibition: A plausible hypothesis. Biochemistry. 1998;37:5791-5797. DOI: 10.1021/bi9802521
  11. 11. Todd MJ, Freire E. The effect of inhibitor binding on the structural stability and cooperativity of the HIV-1 protease. Proteins. 1999;36:147-156. DOI: 10.1002/(sici)1097-0134(19990801)36:2<147::aid-prot2>;2-3
  12. 12. Ross PD, Subramanian S. Thermodynamics of protein association reactions: Forces contributing to stability. Biochemistry. 1981;20:3096-3102. DOI: 10.1021/bi00514a017
  13. 13. Gomez J, Freire E. Thermodynamic mapping of the inhibitor site of the aspartic protease endothiapepsin. Journal of Molecular Biology. 1995;252:337-350. DOI: 10.1006/jmbi.1995.0501
  14. 14. Baker BM, Murphy KP. Evaluation of linked protonation effects in protein binding reactions using isothermal titration calorimetry. Biophysical Journal. 1996;71:2049-2055. DOI: 10.1016/S0006-3495(96)79403-1
  15. 15. Baker BM, Murphy KP. Dissecting the energetics of a protein-protein interaction: The binding of ovomucoid third domain to elastase. Journal of Molecular Biology. 1997;268:557-569. DOI: 10.1006/jmbi.1997.097
  16. 16. Doyle ML, Louie G, Dal Monte PR, Sokoloski TD. Tight binding affinities determined from thermodynamic linkage to protons by titration calorimetry. Methods in Enzymology. 1995;259:183-194. DOI: 10.1016/0076-6879(95)59044-7
  17. 17. Sturtevant JM. Heat capacity and entropy changes in processes involving proteins. Proceedings of the National Academy of Sciences of the United States of America. 1977;74:2236-2240. DOI: 10.1073/pnas.74.6.2236
  18. 18. Velazquez-Campoy A, Todd MJ, Vega S, Freire E. Catalytic efficiency and vitality of HIV-1 proteases from African viral subtypes. Proceedings of the National Academy of Sciences of the United States of America. 2001;98:6062-6067. DOI: 10.1073/pnas.111152698
  19. 19. Ruben AJ, Kiso Y, Freire E. Overcoming roadblocks in lead optimization: A thermodynamic perspective. Chemical Biology & Drug Design. 2006;67:2-4. DOI: 10.1111/j.1747-0285.2005.00314.x
  20. 20. Todd MJ, Luque I, Velazquez-Campoy A, Freire E. Thermodynamic basis of resistance to HIV-1 protease inhibition: Calorimetric analysis of the V82F/I84V active site resistant mutant. Biochemistry. 2000;39:11876-11883. DOI: 10.1021/bi001013s
  21. 21. Velazquez-Campoy A, Muzammil S, Ohtaka H, Schon A, Vega S, Freire E. Structural and thermodynamic basis of resistance to HIV-1 protease inhibition: Implications for inhibitor design. Current Drug Targets. Infectious Disorders. 2003;3:311-328. DOI: 10.2174/1568005033481051
  22. 22. Lipinski CA. Drug-like properties and the causes of poor solubility and poor permeability. Journal of Pharmacological and Toxicological Methods. 2000;44:235-249. DOI: 10.1016/s1056-8719(00)00107-6
  23. 23. Cabani S, Gianni P, Mollica V, Lepori L. Group distribution to the thermodynamic properties of non-ionic solutes in dilute aqueous solution. Journal of Solution Chemistry. 1981;10:563-595. DOI: 10.1007/BF00646936
  24. 24. Velazquez-Campoy A, Freire E. Incorporating target heterogeneity in drug design. Journal of Cellular Biochemistry. Supplement. 2001;37:82-88. DOI: 10.1002/jcb.10068
  25. 25. Velazquez-Campoy A, Kiso Y, Freire E. The binding energetics of first- and second-generation HIV-1 protease inhibitors: Implications for drug design. Archives of Biochemistry and Biophysics. 2001;390:169-175. DOI: 10.1006/abbi.2001.2333
  26. 26. Ohtaka H, Schon A, Freire E. Overcoming drug resistance in HIV-1 chemotherapy: The binding thermodynamics of amprenavir and TMC-126 to wild-type and drug-resistant mutants of the HIV-1 protease. Protein Science. 2002;11:1908-1916. DOI: 10.1110/ps.0206402
  27. 27. Ohtaka H, Velazquez-Campoy A, Xie D, Freire E. Multidrug resistance to HIV-1 protease inhibition requires cooperative coupling between distal mutations. Biochemistry. 2003;42:13659-13666. DOI: 10.1021/bi0350405
  28. 28. Ohtaka H, Muzammil S, Schon A, Velazquez-Campoy A, Vega S, Freire E. Thermodynamic rules for the design of high affinity HIV-1 protease inhibitors with adaptability to mutations and high selectivity towards unwanted targets. The International Journal of Biochemistry & Cell Biology. 2004;36:1787-1799. DOI: 10.1016/j.biocel.2004.02.021
  29. 29. Ohtaka H, Freire E. Adaptive inhibitors of the HIV-1 protease. Progress in Biophysics and Molecular Biology. 2005;88:193-208. DOI: 10.1016/j.pbiomolbio.2004.07.005
  30. 30. Carbonell T, Freire E. Binding thermodynamics of statins of HMG-CoA reductase. Biochemistry. 2005;44:11741-11748. DOI: 10.1021/bi050905v
  31. 31. Muzammil S, Armstrong AA, Kang LW, Jakalian A, Bonneau PR, Schmelmer V, et al. Unique thermodynamic response of tipranavir to human immunodeficiency virus type 1 protease drug resistance mutations. Journal of Virology. 2007;81:5144-5154. DOI: 10.1128/JVI.02706-06
  32. 32. Vega S, Kang L, Velazquez-Campoy A, Kiso Y, Amzel LM, Freire E. A structural and thermodynamic escape mechanism from a drug resistant mutation of the HIV-1 protease. Proteins. 2004;55:594-602. DOI: 10.1002/prot.20069
  33. 33. DeVita VTJr, Broder S, Fauci AS, Kovacs JA, Chabner BA. Developmental therapeutics and the acquired immunodeficiency syndrome. Annals of Internal Medicine. 1987;106:568-581. DOI: 10.7326/0003-4819-106-4-568
  34. 34. Fitzgerald PM, Springer JP. Structure and function of retroviral proteases. Annual Review of Biophysics and Biophysical Chemistry. 1991;20:299-320. DOI: 10.1146/
  35. 35. Kohlstaedt LA, Wang J, Friedman JM, Rice PA, Steitz TA. Crystal structure at 3.5 Å resolution of HIV-1 reverse transcriptase complexed with an inhibitor. Science. 1992;256:1783-1790. DOI: 10.1126/science.1377403
  36. 36. Martin JA. Recent advances in the design of HIV proteinase inhibitors. Antiviral Research. 1992;17:265-278. DOI: 10.1016/0166-3542(92)90022-w
  37. 37. Fitzgerald PMD. HIV protease-ligand complexes. Current Opinion in Structural Biology. 1993;3:868-874. DOI: 10.1016/0959-440X(93)90150-J
  38. 38. Jacobo-Molina A, Ding J, Nanni RG, Clark AD Jr, Lu X, Tantillo C, et al. Crystal structure of human immunodeficiency virus type 1 reverse transcriptase complexed with double-stranded DNA at 3.0 Å resolution shows bent DNA. Proceedings of the National Academy of Sciences of the United States of America. 1993;90:6320-6324. DOI: 10.1073/pnas.90.13.6320
  39. 39. Wlodawer A, Erickson JW. Structure-based inhibitors of HIV-1 protease. Annual Review of Biochemistry. 1993;62:543-585. DOI: 10.1146/
  40. 40. Dyda F, Hickman AB, Jenkins TM, Engelman A, Craigie R, Davies DR. Crystal structure of the catalytic domain of HIV-1 integrase: Similarity to other polynucleotidyl transferases. Science. 1994;266:1981-1986. DOI: 10.1126/science.7801124
  41. 41. Bujacz G, Alexandratos J, Zhou-Liu Q , Clement-Mella C, Wlowader A. The catalytic domain of human immunodeficiency virus integrase: Ordered active site in the F185H mutant. FEBS Letters. 1996;398:175-178. DOI: 10.1016/s0014-5793(96)01236-7
  42. 42. Vacca JP, Condra JH. Clinically effective HIV-1 protease inhibitors. Drug Discovery Today. 1997;2:261-272. DOI: 10.1016/S1359-6446(97)01053-2
  43. 43. Sigurskjold BW. Exact analysis of competition ligand binding by displacement isothermal titration calorimetry. Analytical Biochemistry. 2000;277:260-266. DOI: 10.1006/abio.1999.4402
  44. 44. Baldwin ET, Bhat TN, Gulnik S, Liu B, Topol IA, Kiso Y, et al. Structure of HIV-1 protease with KNI-272, a tight-binding transition-state analog containing allophenylnorstatine. Structure. 1995;3:581-590. DOI: 10.1016/s0969-2126(01)00192-7
  45. 45. Chen Z, Schock HB, Hall D, Chen E, Kuo LC. Three-dimensional structure of a mutant HIV-1 protease displaying cross-resistance to all protease inhibitors in clinical trials. The Journal of Biological Chemistry. 1995;270:21433-21436. DOI: 10.1074/jbc.270.37.21433
  46. 46. Hong L, Treharne A, Hartsuck JA, Foundling S, Tang J. Crystal structures of complexes of a peptidic inhibitor with wild type and two mutant HIV-1 proteases. Biochemistry. 1996;35:10627-10633. DOI: 10.1021/bi960481s
  47. 47. Hong L, Zhang XJ, Foundling S, Hartsuck JA, Tang J. Structure of a G48H mutant of HIV-1 protease explains how glycine-48 replacements produce mutants resistant to inhibitor drugs. FEBS Letters. 1997;420:11-16. DOI: 10.1016/s0014-5793(97)01477-4
  48. 48. Hong L, Zhang XC, Hartsuck JA, Tang J. Crystal structure of an in vivo HIV-1 protease mutant in complex with saquinavir: Insights into mechanisms of drug resistance. Protein Science. 2000;9:1898-1904. DOI: 10.1110/ps.9.10.1898
  49. 49. Mosebi S, Morris L, Dirr H, Sayed Y. Active site mutations in the south African HIV-1 subtype C protease have a significant impact on clinical inhibitor binding: A kinetic and thermodynamic study. Journal of Virology. 2008;82:11476-11479. DOI: 10.1128/JVI.00726-08
  50. 50. Maseko S, Padayachee E, Maphumulo S, Govender T, Sayed Y, Maguire G, et al. Kinetic and thermodynamic characterisation of HIV-protease inhibitors against E35D↑G↑S mutant in the south African HIV-1 subtype C protease. Journal of Enzyme Inhibition and Medicinal Chemistry. 2019;34:1451-1456. DOI: 10.1080/14756366.2019.1636234
  51. 51. Privalov PL, Makhatadze GI. Contribution of hydration and non-covalent interactions to the heat capacity effect on protein unfolding. Journal of Molecular Biology. 1992;224:715-723. DOI: 10.1016/0022-2836(92)90555-x
  52. 52. Murphy KP, Freire E. Thermodynamics of structural stability and cooperative folding behavior in proteins. Advances in Protein Chemistry. 1992;43:313-361. DOI: 10.1016/s0065-3233(08)60556-2
  53. 53. Gomez J, Hilser VJ, Freire E. The heat capacity of proteins. Proteins. 1995;22:404-412. DOI: 10.1002/prot.340220410

Written By

Salerwe Mosebi

Submitted: 12 January 2022 Reviewed: 31 January 2022 Published: 18 May 2022