Crystal structure correlations with the intrinsic thermodynamics of human carbonic anhydrase inhibitor binding

Exploration of 1,3,5-trisubstituted pyrazoline derivatives as human carbonic anhydrase inhibitors: Synthesis, biological evaluation and in silico studies

The human carbonic anhydrase (hCA) IX and XII isoforms are overexpressed in hypoxic conditions, contributing to cancer. Lack of isoform selectivity has been one of the main challenges associated with the existing drugs targeting hCAs. Hence, the development of alternative approaches, such as tail approach to develop more selective hCA IX and XII inhibitors is need of the hour. In the present work, we designed and synthesized 24 new 1,3.5-trisubstituted-pyrazoline derivatives with diverse substitutions. The synthesized analogs were evaluated for their hCA inhibitory activities against hCA I, II, IX, and XII isoforms. Among the tested compounds, derivative 8 displayed good inhibitory activity against hCA IX (Ki = 331 nM) and XII (Ki = 96.7 nM). In addition, 9a-g also exhibited some inhibitory activities against hCA IX and XII, with Kis ranging from 574-799 nM and 137-369 nM, respectively. Molecular modelling studies of compound 8 displayed metal coordination with zinc ion and hydrophobic, hydrophilic interactions with adjacent amino acid residues, and maintained stable interactions throughout 100 ns. In addition, ADMET studies demonstrated that compound 8 obeyed the Lipinski's rule of five and was found to be druggable and non-toxic. Hence, compound 8 was identified as potential lead for further development.

Privileged Scaffold Hybridization in the Design of Carbonic Anhydrase Inhibitors

Human Carbonic Anhydrases (hCA) are enzymes that contribute to cancer's development and progression. Isoforms IX and XII have been identified as potential anticancer targets, and, more specifically, hCA IX is overexpressed in hypoxic tumor cells, where it plays an important role in reprogramming the metabolism. With the aim to find new inhibitors towards IX and XII isoforms, the hybridization of the privileged scaffolds isatin, dihydrothiazole, and benzenesulfonamide was investigated in order to explore how it may affect the activity and selectivity of the hCA isoforms. In this respect, a series of isatin thiazolidinone hybrids have been designed and synthesized and their biological activity and selectivity on hCA I, hCA II, hCA IX, and hCA XII explored. The new compounds exhibited promising inhibitory activity results on isoforms IX and XII in the nanomolar range, which has highlighted the importance of substituents in the isatin ring and in position 3 and 5 of thiazolidinone. In particular, compound 5g was the most active toward hCA IX, while 5f was the most potent inhibitor of hCA XII within the series. When both potency and selectivity were considered, compound 5f appeared as one of the most promising. Additionally, our investigations were supported by molecular docking experiments, which have highlighted the putative binding poses of the most promising compound.

2H-chromene and 7H-furo-chromene derivatives selectively inhibit tumour associated human carbonic anhydrase IX and XII isoforms

Tumour associated carbonic anhydrases (CAs) IX and XII have been recognised as potential targets for the treatment of hypoxic tumours. Therefore, considering the high pharmacological potential of the chromene scaffold as selective ligand of the IX and XII isoforms, two libraries of compounds, namely 2H-chromene and 7H-furo-chromene derivatives, with diverse substitution patterns were designed and synthesised. The structure of the newly synthesised compounds was characterised and their inhibitory potency and selectivity towards human CA off target isoforms I, II and cancer-associated CA isoforms IX and XII were evaluated. Most of the compounds inhibit CA isoforms IX and XII with no activity against the I and II isozymes. Thus, while the potency was influenced by the substitution pattern along the chromene scaffold, the selectivity was conserved along the series, confirming the high potential of both 2H-chromene and 7H-furo-chromene scaffolds for the design of isozyme selective inhibitors.

Machine-Learning-Based Data Analysis Method for Cell-Based Selection of DNA-Encoded Libraries

DNA-encoded library (DEL) is a powerful ligand discovery technology that has been widely adopted in the pharmaceutical industry. DEL selections are typically performed with a purified protein target immobilized on a matrix or in solution phase. Recently, DELs have also been used to interrogate the targets in the complex biological environment, such as membrane proteins on live cells. However, due to the complex landscape of the cell surface, the selection inevitably involves significant nonspecific interactions, and the selection data are much noisier than the ones with purified proteins, making reliable hit identification highly challenging. Researchers have developed several approaches to denoise DEL datasets, but it remains unclear whether they are suitable for cell-based DEL selections. Here, we report the proof-of-principle of a new machine-learning (ML)-based approach to process cell-based DEL selection datasets by using a Maximum A Posteriori (MAP) estimation loss function, a probabilistic framework that can account for and quantify uncertainties of noisy data. We applied the approach to a DEL selection dataset, where a library of 7,721,415 compounds was selected against a purified carbonic anhydrase 2 (CA-2) and a cell line expressing the membrane protein carbonic anhydrase 12 (CA-12). The extended-connectivity fingerprint (ECFP)-based regression model using the MAP loss function was able to identify true binders and also reliable structure-activity relationship (SAR) from the noisy cell-based selection datasets. In addition, the regularized enrichment metric (known as MAP enrichment) could also be calculated directly without involving the specific machine-learning model, effectively suppressing low-confidence outliers and enhancing the signal-to-noise ratio. Future applications of this method will focus on de novo ligand discovery from cell-based DEL selections.

Methyl 2-Halo-4-Substituted-5-Sulfamoyl-Benzoates as High Affinity and Selective Inhibitors of Carbonic Anhydrase IX

Among the twelve catalytically active carbonic anhydrase isozymes present in the human body, the CAIX is highly overexpressed in various solid tumors. The enzyme acidifies the tumor microenvironment enabling invasion and metastatic processes. Therefore, many attempts have been made to design chemical compounds that would exhibit high affinity and selective binding to CAIX over the remaining eleven catalytically active CA isozymes to limit undesired side effects. It has been postulated that such drugs may have anticancer properties and could be used in tumor treatment. Here we have designed a series of compounds, methyl 5-sulfamoyl-benzoates, which bear a primary sulfonamide group, a well-known marker of CA inhibitors, and determined their affinities for all twelve CA isozymes. Variations of substituents on the benzenesulfonamide ring led to compound 4b, which exhibited an extremely high observed binding affinity to CAIX; the Kd was 0.12 nM. The intrinsic dissociation constant, where the binding-linked protonation reactions have been subtracted, reached 0.08 pM. The compound also exhibited more than 100-fold selectivity over the remaining CA isozymes. The X-ray crystallographic structure of compound 3b bound to CAIX showed the structural position, while several structures of compounds bound to other CA isozymes showed structural reasons for compound selectivity towards CAIX. Since this series of compounds possess physicochemical properties suitable for drugs, they may be developed for anticancer therapeutic purposes.

Switching the Inhibitor-Enzyme Recognition Profile via Chimeric Carbonic Anhydrase XII

A key part of the optimization of small molecules in pharmaceutical inhibitor development is to vary the molecular design to enhance complementarity of chemical features of the compound with the positioning of amino acids in the active site of a target enzyme. Typically this involves iterations of synthesis, to modify the compound, and biophysical assay, to assess the outcomes. Selective targeting of the anti-cancer carbonic anhydrase isoform XII (CA XII), this process is challenging because the overall fold is very similar across the twelve CA isoforms. To enhance drug development for CA XII we used a reverse engineering approach where mutation of the key six amino acids in the active site of human CA XII into the CA II isoform was performed to provide a protein chimera (chCA XII) which is amenable to structure-based compound optimization. Through determination of structural detail and affinity measurement of the interaction with over 60 compounds we observed that the compounds that bound CA XII more strongly than CA II, switched their preference and bound more strongly to the engineered chimera, chCA XII, based on CA II, but containing the 6 key amino acids from CA XII, behaved as CA XII in its compound recognition profile. The structures of the compounds in the chimeric active site also resembled those determined for complexes with CA XII, hence validating this protein engineering approach in the development of new inhibitors.

Isoform-Selective Enzyme Inhibitors by Exploring Pocket Size According to the Lock-and-Key Principle

In the design of high-affinity and enzyme isoform-selective inhibitors, we applied an approach of augmenting the substituents attached to the benzenesulfonamide scaffold in three ways, namely, substitutions at the 3,5- or 2,4,6-positions or expansion of the condensed ring system. The increased size of the substituents determined the spatial limitations of the active sites of the 12 catalytically active human carbonic anhydrase (CA) isoforms until no binding was observed because of the inability of the compounds to fit in the active site. This approach led to the discovery of high-affinity and high-selectivity compounds for the anticancer target CA IX and antiobesity target CA VB. The x-ray crystallographic structures of compounds bound to CA IX showed the positions of the bound compounds, whereas computational modeling confirmed that steric clashes prevent the binding of these compounds to other isoforms and thus avoid undesired side effects. Such an approach, based on the Lock-and-Key principle, could be used for the development of enzyme-specific drug candidate compounds.

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

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.

Isothermal Analysis of ThermoFluor Data can readily provide Quantitative Binding Affinities

Differential scanning fluorimetry (DSF), also known as ThermoFluor or Thermal Shift Assay, has become a commonly-used approach for detecting protein-ligand interactions, particularly in the context of fragment screening. Upon binding to a folded protein, most ligands stabilize the protein; thus, observing an increase in the temperature at which the protein unfolds as a function of ligand concentration can serve as evidence of a direct interaction. While experimental protocols for this assay are well-developed, it is not straightforward to extract binding constants from the resulting data. Because of this, DSF is often used to probe for an interaction, but not to quantify the corresponding binding constant (Kd). Here, we propose a new approach for analyzing DSF data. Using unfolding curves at varying ligand concentrations, our "isothermal" approach collects from these the fraction of protein that is folded at a single temperature (chosen to be temperature near the unfolding transition). This greatly simplifies the subsequent analysis, because it circumvents the complicating temperature dependence of the binding constant; the resulting constant-temperature system can then be described as a pair of coupled equilibria (protein folding/unfolding and ligand binding/unbinding). The temperature at which the binding constants are determined can also be tuned, by adding chemical denaturants that shift the protein unfolding temperature. We demonstrate the application of this isothermal analysis using experimental data for maltose binding protein binding to maltose, and for two carbonic anhydrase isoforms binding to each of four inhibitors. To facilitate adoption of this new approach, we provide a free and easy-to-use Python program that analyzes thermal unfolding data and implements the isothermal approach described herein ( https://sourceforge.net/projects/dsf-fitting ).