Hostname: page-component-89b8bd64d-ksp62 Total loading time: 0 Render date: 2026-05-08T06:08:53.442Z Has data issue: false hasContentIssue false

Thermodynamic, kinetic, and structural parameterization of human carbonic anhydrase interactions toward enhanced inhibitor design

Published online by Cambridge University Press:  26 November 2018

Vaida Linkuvienė
Affiliation:
Department of Biothermodynamics and Drug Design, Institute of Biotechnology, Life Sciences Center, Vilnius University, Saulėtekio 7, 10257 Vilnius, Lithuania
Asta Zubrienė
Affiliation:
Department of Biothermodynamics and Drug Design, Institute of Biotechnology, Life Sciences Center, Vilnius University, Saulėtekio 7, 10257 Vilnius, Lithuania
Elena Manakova
Affiliation:
Department of Protein-DNA Interactions, Institute of Biotechnology, Life Sciences Center, Vilnius University, Saulėtekio 7, 10257 Vilnius, Lithuania
Vytautas Petrauskas
Affiliation:
Department of Biothermodynamics and Drug Design, Institute of Biotechnology, Life Sciences Center, Vilnius University, Saulėtekio 7, 10257 Vilnius, Lithuania
Lina Baranauskienė
Affiliation:
Department of Biothermodynamics and Drug Design, Institute of Biotechnology, Life Sciences Center, Vilnius University, Saulėtekio 7, 10257 Vilnius, Lithuania
Audrius Zakšauskas
Affiliation:
Department of Biothermodynamics and Drug Design, Institute of Biotechnology, Life Sciences Center, Vilnius University, Saulėtekio 7, 10257 Vilnius, Lithuania
Alexey Smirnov
Affiliation:
Department of Biothermodynamics and Drug Design, Institute of Biotechnology, Life Sciences Center, Vilnius University, Saulėtekio 7, 10257 Vilnius, Lithuania
Saulius Gražulis
Affiliation:
Department of Protein-DNA Interactions, Institute of Biotechnology, Life Sciences Center, Vilnius University, Saulėtekio 7, 10257 Vilnius, Lithuania
John E. Ladbury
Affiliation:
Department of Molecular and Cell Biology and Astbury Centre for Structural Biology, University of Leeds, Leeds, UK
Daumantas Matulis*
Affiliation:
Department of Biothermodynamics and Drug Design, Institute of Biotechnology, Life Sciences Center, Vilnius University, Saulėtekio 7, 10257 Vilnius, Lithuania
*
Author for correspondence: Daumantas Matulis, E-mail: matulis@ibt.lt, daumantas.matulis@bti.vu.lt
Rights & Permissions [Opens in a new window]

Abstract

The aim of rational drug design is to develop small molecules using a quantitative approach to optimize affinity. This should enhance the development of chemical compounds that would specifically, selectively, reversibly, and with high affinity interact with a target protein. It is not yet possible to develop such compounds using computational (i.e., in silico) approach and instead the lead molecules are discovered in high-throughput screening searches of large compound libraries. The main reason why in silico methods are not capable to deliver is our poor understanding of the compound structure–thermodynamics and structure–kinetics correlations. There is a need for databases of intrinsic binding parameters (e.g., the change upon binding in standard Gibbs energy (ΔGint), enthalpy (ΔHint), entropy (ΔSint), volume (ΔVintr), heat capacity (ΔCp,int), association rate (ka,int), and dissociation rate (kd,int)) between a series of closely related proteins and a chemically diverse, but pharmacophoric group-guided library of compounds together with the co-crystal structures that could help explain the structure–energetics correlations and rationally design novel compounds. Assembly of these data will facilitate attempts to provide correlations and train data for modeling of compound binding. Here, we report large datasets of the intrinsic thermodynamic and kinetic data including over 400 primary sulfonamide compound binding to a family of 12 catalytically active human carbonic anhydrases (CA). Thermodynamic parameters have been determined by the fluorescent thermal shift assay, isothermal titration calorimetry, and by the stopped-flow assay of the inhibition of enzymatic activity. Kinetic measurements were performed using surface plasmon resonance. Intrinsic thermodynamic and kinetic parameters of binding were determined by dissecting the binding-linked protonation reactions of the protein and sulfonamide. The compound structure–thermodynamics and kinetics correlations reported here helped to discover compounds that exhibited picomolar affinities, hour-long residence times, and million-fold selectivities over non-target CA isoforms. Drug-lead compounds are suggested for anticancer target CA IX and CA XII, antiglaucoma CA IV, antiobesity CA VA and CA VB, and other isoforms. Together with 85 X-ray crystallographic structures of 60 compounds bound to six CA isoforms, the database should be of help to continue developing the principles of rational target-based drug design.

Information

Type
Invited Review
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
Copyright © Cambridge University Press 2018
Figure 0

Fig. 1. General illustration of the term intrinsic. The standard observed Gibbs energy of a protein–ligand binding depends on various non-essential experimental conditions if there are binding-linked reactions that require energy consumption in order for the binding reaction to occur. The standard intrinsic Gibbs energy of binding is obtained by summation of the energies from those linked reactions. The intrinsic energy is thus always greater than the observed and the intrinsic affinity is greater than the observed. The same argument applies to all thermodynamic and kinetic parameters as will be demonstrated below for the case of CA where the binding-linked reactions are protonation reactions of the protein, the ligand, and the compensation by the buffer.

Figure 1

Fig. 2. Localization and multimerization of catalytically active 12 human CA isoforms in the cell. Isoforms CA I, CA II, CA III, CA VII, and CA XIII are cytosolic, CA VA and CA VB are found in mitochondria, CA VI is excreted in human saliva and milk, CA IV is anchored to the membrane via a covalently attached lipid moiety, and CA IX, CA XII, and CA XIV are membrane-bound via a single transmembrane alpha helix with the catalytic domain being outside of the cell. The remaining three isoforms (named CARP – CA-related protein), CA VIII, CA X, and CA XI are catalytically inactive and not shown in the figure. The CA VI, CA IX, and CA XII are dimers while the rest are monomers. The CA IX bears a proteoglycan-like (PG) domain – a unique feature of CA IX.

Figure 2

Fig. 3. Overlay of the backbones of five human CA isoforms shown in different colors (CA I – blue, CA II – grey, CA VII – yellow, CA IX – red, and CA XII – green). Their backbones superimpose essentially identically.

Figure 3

Fig. 4. Comparison between interactions of primary aromatic sulfonamide, and bicarbonate with the CA.

Figure 4

Fig. 5. Examples of ITC data of 1 binding to catalytically active recombinant human CA isoforms at pH 8, 25 °C as determined using the VP-ITC calorimeter. Insets show the raw curves with unflattened baselines, without user-biased interference. Experiments were performed in 50 mM sodium phosphate buffer containing 100 mM NaCl and 2% DMSO as previously described in: CA I and CA II (Morkūnaitė et al., 2015), CA IV (Mickevičiūtė et al., 2017), CA VB (Kasiliauskaitė et al., 2016), CA VI (Kazokaitė et al., 2015), CA VII (Pilipuitytė and Matulis, 2015), CA IX (Linkuvienė et al., 2016b), CA XII (Jogaitė et al., 2013), and CA XIII (Baranauskienė and Matulis, 2012). All panels are drawn at the same scale to help visualize the differences both in enthalpies and affinities of binding. No data have been determined at comparable conditions for CA III, CA VA, and CA XIV.

Figure 5

Fig. 6. Example of FTSA data of 1 binding to all 12 catalytically active recombinant human CA isoforms at pH 6. The insets show raw melting curves obtained by following ANS fluorescence. The experiments were performed at pH 6 in universal buffer made of 50 mM sodium phosphate, 50 mM sodium acetate, and 25 mM sodium borate containing 100 mM NaCl and up to 2% DMSO and 50 µM ANS as previously described: CA I and CA II (Morkūnaitė et al., 2015), CA IV (Mickevičiūtė et al., 2017), CA VB (Kasiliauskaitė et al., 2016), CA VI (Kazokaitė et al., 2015), CA VII (Pilipuitytė and Matulis, 2015), CA IX (Linkuvienė et al., 2016b), CA XII (Jogaitė et al., 2013), CA XIII (Baranauskienė and Matulis, 2012), and CA XIV (Juozapaitienė et al., 2016).

Figure 6

Fig. 7. Comparison of SFA, FTSA, and ITC techniques, their advantages and limitations. Panels on the left show simulated curves, while on the right – the examples of measured data. The figure is adapted from Smirnovienė et al. (2017). (a) The application of Hill equation at protein concentration Pt = 10nM and various values of apparent IC50. The assay would not distinguish between 1 nM and 1 pM compounds because Pt cannot be reduced to less than 1 nM or 1 pM to obtain distinguishable dosing curves of nanomolar (solid line) or picomolar (dotted line) affinity. (b) Experimental data of an interaction between CA II-307 at several compound concentrations. Data points were fitted according to the Hill equation with varied Hill coefficient. The inset shows the raw absorbance curves at several compound concentrations. (c) The simulated FTSA dosing curves for different binding affinities (Kd from 1 pM to 1 mM) are shown. These curves were generated using the following set of parameters: T = 37 °C, Pt = 10 µM, enthalpy of CA II unfolding is 690 kJ mol−1, heat capacity of unfolding is 17 kJ mol−1 K−1, enthalpy of binding is −42 kJ mol−1, heat capacity of binding is −0.8 kJ mol−1 K−1 , and the melting temperature Tm without added ligand is 60 °C. (d) Experimental FTSA data of CA I-323 (squares), CA II-10 (circles), and CA XIII-310 (triangles). The insets show raw melting curves at 0 and 200 µM inhibitor concentrations. (e) Simulated ITC curves using a single binding site model of different binding affinities at Pt = 10 µM. (f) Experimental ITC curves of the same binding interactions as in panel D. Affinity of CA I-323 is too strong to be determined by ITC but FTSA assay provides accurate Kd.

Figure 7

Fig. 8. Comparison of the experimentally determined Kd,obs obtained by four techniques: fluorescent thermal shift assay (FTSA), isothermal titration calorimetry (ITC), stopped-flow assay of the inhibition of CA enzymatic activity, CO2 hydration (SFA), and the surface plasmon resonance (SPR). All Kds have been determined by FTSA as the most robust and reliable technique and compared with the results obtained for a portion of compounds by ITC, SFA, and SPR. The FTSA practically does not have limits or range of reliable determinations, the compound Kds may be determined from pM to mM affinity range in a single experiment, while the other three techniques have limitations of the range where reliable determinations may be made, shown with arrows and shaded in grey.

Figure 8

Table 1. Comparison of binding and inhibition constants of CA I, CA II, CA VI, CA VII, CA IX, CA XII, and CA XIII obtained by SFA (pH 7.0–7.5, 25 °C), FTSA, ITC (pH 7.0, 37 °C), and SPR (pH 7.0–7.4, 25 °C). SFA. The used KM values were, for CA I – 1.4 mM, CA II – 4.7 mM, CA VI – 6.9 mM, CA VII – 11.4 mM, CA IX – 6.9 mM, CA XII – 12 mM, and CA XIII – 13.8 mM, taken from Supuran (2008). The IC50 is the 50% inhibition concentration of enzymatic activity obtained by Hill fit of the data. Ki is the inhibition constant obtained after application of the Cheng–Prusoff equation to the IC50. The Kd,obs is the dissociation constant obtained via Morrison equation. FTSA. The Kd,obs is the observed dissociation constant obtained by FTSA at the CA concentration 5 to 10 µM. ITC. The Kd,obs is the observed dissociation constant obtained by ITC at the CA concentration of 4 to 10 µM. SPR. The Kd,obs is the observed dissociation constant obtained by SPR at the CA concentration for immobilization of 75 µg ml−1 for CA I, 100 µg ml−1 for CA II, 25 µg ml−1 for CA VII, 100 µg ml−1 for CA IX, 25 µg ml−1 for CA XII, 75μg ml−1 for CA XIII as described by Talibov et al. (2016). Values are shown in the regular font when the results match among three methods within an approximate error of ±2 fold. Values are shown in bold to point the most reliable value when results are significantly different among the methods. Values are in italic to emphasize unreliable results when the methods should not be used due to their limitations (for SFA – concentration of the enzyme above the concentration of inhibitor, for ITC – Wiseman c-factor outside the required range). SFA, FTSA, and ITC data are taken from the references indicated next to the compound number. The standard error of Kd measurements is ±2 times (Petrauskas et al., 2016; Linkuvienė et al., 2016a)

Figure 9

Fig. 9. The model of the linked reactions (also shown as Eq. (8)), occurring upon sulfonamide ligand binding to CA. A sum of several binding-linked reactions occur that we observe by any experimental technique, but the Quantitative Structure–Activity Relationship (QSAR)-type analysis requires that we analyze only the intrinsic reaction and correlate the intrinsic affinity and other intrinsic parameters with the structure of the ligand and the ligand–protein complex. The linked contributing reactions must be subtracted from the observed ones to obtain the intrinsic reaction.

Figure 10

Fig. 10. Relationship between the intrinsic (independent of pH, shown as horizontal line) and observed affinities (filled circles fit by the solid line of overturned U-shape) of 1 binding to CA IX. The observed affinity is reduced both at acidic and alkaline pHs due to reduced fractions of available binding-ready species (negatively charged sulfonamide, shown as solid red line, and CA, bearing the neutral water molecule, shown as a dashed red line).

Figure 11

Fig. 11. The dependence of ΔGobs on pH determined by FTSA (filled circles) and ITC (open circles) methods at 25 °C. Circles show the binding of 1 and squares of 303 (to CA III and CA VA). Solid curve is a fit of the model, solid line is intrinsic Gibbs energy of binding, dashed line is a fraction of ligand, dotted line is a fraction of protein. Experiments were performed in universal buffer made of 50 mM sodium phosphate, 50 mM sodium acetate, and 25 mM sodium borate containing 100 mM NaCl and up to 2% DMSO as previously described in: CA I and CA II (Morkūnaitė et al., 2015), CA IV (Mickevičiūtė et al., 2017), CA VB (Kasiliauskaitė et al., 2016), CA VI (Kazokaitė et al., 2015), CA VII (Pilipuitytė and Matulis, 2015), CA IX (Linkuvienė et al., 2016b), CA XII (Jogaitė et al., 2013), CA XIII (Baranauskienė and Matulis, 2012), and CA XIV (Juozapaitienė et al., 2016). All panels are drawn at the same scale to help visualize the differences in affinities of binding.

Figure 12

Fig. 12. ITC data of 1 binding to CA IX in two buffers at several pHs at 25 °C. The observed enthalpies depended both on the buffer and on the pH used in the experiment. In such cases, it is necessary to obtain the intrinsic enthalpy to perform any meaningful Structure–Activity Relationship (SAR)-type study. The inset shows a typical ITC raw data curve.

Figure 13

Fig. 13. The observed enthalpies obtained by ITC of 1 binding to CA I in sodium phosphate or TRIS chloride buffer as a function of pH at 25 °C. Blue datapoints show the ΔHobs in phosphate buffer, while black – in TRIS. Solid black and blue lines are global fits to the above-described model (fit in the way where the pKas are consistent with the FTSA data for each isoform) yielding the intrinsic enthalpy of binding (ΔHint, red line) that is independent of pH. Dashed line shows a hypothetical situation how the observed enthalpy dependence should look like if the enthalpy of buffer protonation was equal to zero.

Figure 14

Fig. 14. ITC data of 1 binding to CA isoforms at 25 °C. Filled circles – ΔHobs determined in sodium phosphate buffer, open circles – ΔHobs determined in TRIS buffer, dotted line shows value of ΔHint of 1 binding, solid curves are fits of experimental data, while the dashed curve is a fit of a hypothetical situation if there were no buffer or the enthalpy of buffer protonation (ΔHpr,buf) was equal to zero. The fits were global with the FTSA U-shapes keeping the sulfonamide and CA pKas the same. Experiments were performed in either 50 mM sodium phosphate or 50 mM TRIS chloride buffer containing 100 mM NaCl and up to 2% DMSO as previously described in: CA I and CA II (Morkūnaitė et al., 2015), CA IV (Mickevičiūtė et al., 2017), CA VB (Kasiliauskaitė et al., 2016), CA VI (Kazokaitė et al., 2015), CA VII (Pilipuitytė and Matulis, 2015), CA IX (Linkuvienė et al., 2016b), CA XII (Jogaitė et al., 2013), CA XIII (Baranauskienė and Matulis, 2012). All panels are drawn at the same scale to help visualize the differences in enthalpies of binding. No data has been determined at comparable conditions for CA III, CA VA, and CA XIV. The overall pattern of the X-shapes is similar, but details are different due to different pKa,CA and ΔHint for each isoform.

Figure 15

Fig. 15. The enthalpy changes upon compound 303 binding to CA XIII at various pHs. The curve was fit using the following parameters: pKa,SA = 6.25, pKa,CA = 8.3, ΔHint = −37 kJ mol−1 , ΔHpr,SA = −28 kJ mol−1 , ΔHpr,CA = −40 kJ mol−1. The open and closed symbols show the data obtained by two independent researchers. The solid curve matched the data resembling all bends in the curve except the discrepancy in the alkaline region. Possibly the protein is slightly destabilized in this region. The horizontal straight line shows the change in the intrinsic enthalpy upon binding if we assume that the reaction occurs according to Eq. (7). However, the same indistinguishable curve would be obtained for Eq. (4) and Eq. (7). The intrinsic enthalpy would then be different. The thermodynamic data alone cannot distinguish the models and we base our decision that Eq. (7) is correct based on crystallographic data.

Figure 16

Table 2. Thermodynamic parameters of protonation of CA-ZnII-bound hydroxide anion (Eq. (8), third reaction) for all 12 catalytically active CA isoforms. The pKa values determined by various methods and taken from the earlier literature are listed in the second column together with the references. Other values were determined by FTSA and ITC with the references listed in the first column next to the CA isoforms. The uncertainty of the pKa values determined by FTSA and ITC is approximately 0.2 pH units, while for the change in Gibbs energies and enthalpies it is approximately 2 kJ mol−1

Figure 17

Fig. 16. Correlation between the pKas of sulfonamide amino group (determined spectrophotometrically) and the chemical shift of the sulfonamide amino group protons as determined by NMR in deuterated DMSO solvent. Three series of compounds are distinguished in three colors and symbol shapes, VD series are mostly fluorinated benzenesulfonamides, EA and E series are mostly chlorinated compounds. The correlation is approximately linear. The plot may be used to obtain an estimate of the amino group pKa from proton NMR data when characterizing newly synthesized primary sulfonamides.

Figure 18

Fig. 17. Determination of the pKa and enthalpy of protonation (ΔHpr,SA) of the sulfonamide amino group. Left panels (a), (c), and (e) show the spectrophotometric, while right panels (b), (d), and (f) show the ITC data. (a) UV-Vis spectra of the compound solution in buffers of various pH. (c) The normalized absorbance change at a chosen wavelength or ratio of two wavelengths. (e) Determination of the ΔHpr,SA via van't Hoff relationship, the dependence of the pKa on temperature. (b) ITC raw data of titrating a base-neutralized (with 1.5 equiv.) sulfonamide with HNO3. (d) Integrated ITC curves of the sulfonamide titration with acid. (f) Determination of the heat capacity of protonation by performing the ITC titrations at various temperatures. The ΔCp values for 310 and 369 were equal to 107 J mol−1 K−1 and 88 J mol−1 K−1, respectively.

Figure 19

Fig. 18. The observed and intrinsic Kd of a series of sulfonamide compound interaction with CA VI (Kazokaitė et al., 2015). There is clearly no correlation between the observed and intrinsic binding affinities.

Figure 20

Fig. 19. The observed and intrinsic Kd of two sulfonamide compound interaction with CA I. The compounds are para-substituted benzenesulfonamides, one of them with four fluorines on the benzene ring. The observed affinity showed that the F-bearing compound bound CA I significantly stronger than the non-fluorinated compound. The intrinsic Kds were practically equal for both compounds, but the observed ones differed by 150-fold mostly due to the reduction of the pKa of the fluorinated compound and not direct recognition between the F atoms and the protein surface.

Figure 21

Fig. 20. An example of raw SPR data. Interaction of 368 with CA II at pH 8.0 as described by Linkuvienė et al. (2018). The data are shown in black while the globally fitted curves – in red. Each consecutive curve was obtained at a half concentration of the compound as compared with the previous one.

Figure 22

Fig. 21. The dependence of observed ka (left graph) and observed kd (right graph) on pH at 25 °C. It is obvious, as previously observed by Taylor et al. (1970), that the on-rate ka depends on pH in a similar fashion as the thermodynamic KD. However, the dissociation rate kd is independent of pH as shown on the right graph drawn at the same scale as the left one.

Figure 23

Fig. 22. The model of linked reactions, similar to the model explaining the intrinsic thermodynamics described above, that explains the pH dependence of the association rate. The observed association rate depends on pH while the observed dissociation rate is independent of pH and thus is equal to the intrinsic dissociation rate. The intrinsic association rates may be calculated applying the same equations describing the fractions of binding-ready species as in the thermodynamic calculations above.

Figure 24

Fig. 23. Association-dissociation rates for a series of compound interaction with several CA isoforms. Each compound-CA interaction is described by two points connected by a vertical line. The upper point describes the intrinsic ka and the lower point describes the observed ka. The dissociation rate kd is the same, observed or intrinsic, therefore there is only one point on the horizontal axis. Observed ka and kd values in the right side of the graph were obtained using SPR, while kds in the grey-shaded area could not be determined with the desired precision by SPR and thus were calculated using KD obtained by FTSA and ka obtained by SPR. The leftmost three compounds exhibit extremely slow dissociation and their residence times are in the order of several hours. Dashed diagonal lines represent isoaffinity lines with the thermodynamic Kd values listed above and on the right side of the graph. Different colors and symbol shapes represent compound binding kinetic parameters to several CA isoforms.

Figure 25

Fig. 24. The enthalpy–entropy compensation plot for all inhibitors listed in Supplementary Table 2. Different colors and symbol shapes represent binding data to various CA isoforms. Most compounds bound to CAs both due to favorable enthalpies and favorable entropy contributions. However, there were few that bound with enthalpy-opposed and entropy-opposed thermodynamics. Note that despite significant differences in compound chemical structures, the values grouped according to CA isoform: CA I binders were mostly on the top-left corner while CA IX – on the right-lower part of the plot.

Figure 26

Fig. 25. Determination of the catalytically active fraction of the preparation of CA XIV as previously described by Juozapaitienė et al. (2016), performed according to Copeland (2005). Two straight lines intersected at exactly 500 nM concentration equal to the added concentration of CA XIV thus confirming that the entire preparation of CA XIV was enzymatically active. The inset shows the decrease in absorbance lines at various inhibitor concentrations (steep blue lines – no inhibitor, shallow red lines – largest inhibitor concentration added). The red CO2 curve shows spontaneous hydration of CO2 in the absence of enzyme.

Figure 27

Fig. 26. Correlation between observed inhibitor binding affinities to CA VI produced by three different paths (Kazokaitė et al., 2015). Human recombinant CA VI was prepared in bacterial and mammalian cell cultures. The native human CA VI was also affinity-purified from human volunteer saliva. Comparing the affinities of the compounds to the three kinds of CA VI we see that affinities are highly similar and identical within an error margin with the exception of bacterial preparation that bound the compounds with systematically higher affinity by approximately 2–3 fold. This difference could be caused by the different dimerization pattern of various CA VI preparations.

Figure 28

Fig. 27. Characterization of CA isoform stability in various buffers at various pHs. The isoform stability profiles look similar with the greatest stability near pH 7, but there are several notable exceptions, especially CA VI that exhibits stability maximum around slightly acidic pH 5. Note that citrate buffer is destabilizing all CAs because it is complexating ZnII and thus destabilizing the native conformation of CA. Experiments were performed in 100 mM buffer containing 2 mM NaCl and 0.5% DMSO as previously described in: CA I and CA II (Morkūnaitė et al., 2015), CA IV (Mickevičiūtė et al., 2017), CA VB (Kasiliauskaitė et al., 2016), CA VI (Kazokaitė et al., 2015), CA VII (Pilipuitytė and Matulis, 2015), CA IX (Linkuvienė et al., 2016b), CA XII (Jogaitė et al., 2013), CA XIII (Baranauskienė and Matulis, 2012), and CA XIV (Juozapaitienė et al., 2016). All panels are drawn at the same scale to help visualize the differences in stabilities among CA isoforms.

Figure 29

Fig. 28. Binding Gibbs energy contributions of compound functional groups in the search of fluorinated compounds that would selectively bind and inhibit CA IX. The map shows a series of compounds connected by arrows beginning with benzenesulfonamide as the weakest inhibitor and ending with the best inhibitors on the right. Numbers next to the structures show the intrinsic Gibbs energies of compound binding to each recombinant human CA isoform. Numbers at the arrows show the differences between the affinities to two connected isoforms. Larger differences are depicted in larger font size to emphasize the largest energy gains upon chemical modifications of the compounds.

Figure 30

Fig. 29. Comparison of the binding thermodynamic parameters in structurally-related compound pairs arranged according to the buried and accessible surface areas (BSA + ASA) which were calculated from the crystal structures as described by Smirnov et al. (2018). Panels (a) and (b) show the Gibbs energies of binding, (c) and (d) the intrinsic enthalpies of binding, and (e) and (f) – the entropies multiplied by the absolute temperature. Panels on the left show the pairs that are called similar, meaning that the sulfonamide benzene ring is positioned identically in both crystal structures, while the panels on the right show dissimilar binders, where the position of the benzene ring is different in the pair. In the similar binders, there is a significant loss of exothermic enthalpy observed upon addition of a hydrophobic group on a compound. However, in dissimilar binders, the opposite tendency is observed – the enthalpy is gained upon the addition of a hydrophobic surface. The bottom two panels G and H show the crystallographic positions of the similar (G) and dissimilar (H) pairs of binders.

Figure 31

Fig. 30. Several compounds that exhibit high affinity towards one CA isoform and significant selectivity over CA I and CA II. The observed and intrinsic Kds of the compounds to the most important CAs are shown below.

Supplementary material: PDF

Linkuvienė et al. supplementary material

Linkuvienė et al. supplementary material 1

Download Linkuvienė et al. supplementary material(PDF)
PDF 9.5 MB