Experiment stands corrected: accurate prediction of the aqueous pK a values of sulfonamide drugs using equilibrium bond lengths

Design and synthesis of chromene-1,2,3-triazole benzene sulfonamide hybrids as potent carbonic anhydrase-IX inhibitors against prostate cancer

Considering the promising effects of molecular hybridization on drug discovery in recent years and the ongoing endeavors to develop bioactive scaffolds tethering the 1,2,3-triazole core, the present study sought to investigate whether the 1,2,3-triazole-linked chromene and benzene sulfonamide nucleus could exhibit activity against the human breast cancer cell line MCF-7 and prostate cancer cell line PC-3. To this end, three focused bioactive series of mono- and -bis-1,2,3-triazoles were effectively synthesized via copper-assisted cycloaddition of mono- and/or di-alkyne chromenone derivatives 2a and b and 9 with several sulfa drug azides 4a-d and 6. The resulting molecular derivatives were tested for cytotoxicity against prostate and breast cancer cells. Among the derivatives, 10a, 10c, and 10e exhibited potent cytotoxicity against PC-3 cells with IC50 values of 2.08, 7.57, and 5.52 μM compared to doxorubicin (IC50 = 2.31 μM) with potent inhibition of CA IX with IC50 values of 0.113, 0.134, and 0.214 μM. The most active compound, 10a, was tested for apoptosis-induction; it induced apoptosis by 31.9-fold cell cycle arrest at the G1-phase. Further, the molecular modeling approach highlighted the relevant binding affinity for the top-active compound 10a against CA IX as one of the most prominent PC-3 prostate cancer-associated biotargets.

The role of the methoxy group in approved drugs

The methoxy substituent is prevalent in natural products and, consequently, is present in many natural product-derived drugs. It has also been installed in modern drug molecules with no remnant of natural product features because medicinal chemists have been taking advantage of the benefits that this small functional group can bestow on ligand-target binding, physicochemical properties, and ADME parameters. Herein, over 230 methoxy-containing small-molecule drugs, as well as several fluoromethoxy-containing drugs, are presented from the vantage point of the methoxy group. Biochemical mechanisms of action, medicinal chemistry SAR studies, and numerous X-ray cocrystal structures are analyzed to identify the precise role of the methoxy group for many of the drugs and drug classes. Although the methoxy substituent can be considered as the hybridization of a hydroxy and a methyl group, the combination of these functionalities often results in unique effects that can amount to more than the sum of the individual parts.

Easy to Use DFT Approach for Computational pKa Determination of Carboxylic Acids

In pKa computational determination, the challenge in exploring and fostering new methodologies and approaches goes in parallel with the amelioration of computational performances. In this paper a "ready to use methodology" has been compared to other strategies, such as the re-shaping in solvation cavity (Bondi radius re-shaping), wanting to assess its reliability in predicting the pKa of a broad list of carboxylic acids. Thus, the functionals B3LYP and CAM-B3LYP have been selected, using SMD as continuum solvation model. Exploiting our previous results, two water molecules were made explicit on the reaction centre. Data show that our model (CAM-B3LYP/2H2 O) is capable to accurately predict pKa, leading to mean absolute error (MAE) values lower than 0.5. Noteworthy, good results were achieved in computing the pKa of substituents bearing nitro and cyano groups. Focusing on B3LYP, eventually remarkable outputs were obtained only when Bondi correction was applied to the complex with two water molecules. Hence, massive outcomes were obtained in foreseeing the trichloro and trifluoro acetic acid pKa. These findings demonstrated that no complex level of theory nor external factor is required to accurately predict carboxylic acids pKa, with MAE well below 0.5 units.

Quantum Mechanical Prediction of Dissociation Constants for Thiazol-2-imine Derivatives

As weak acids or bases, in solution, drug molecules are in either their ionized or nonionized states. A high degree of ionization is essential for good water solubility of a drug molecule and is required for drug-receptor interactions, whereas the nonionized form improves a drug's lipophilicity, allowing the ligand to cross the cell membrane. The penetration of a drug ligand through cell membranes is mainly governed by the pKa of the drug molecule and the membrane environment. In this study, with the aim of predicting the acetonitrile pKa's (pKa(MeCN)) of eight drug-like thiazol-2-imine derivatives, we propose a very accurate and computationally affordable protocol by using several quantum mechanical approaches. Benchmark studies were conducted on a set of training molecules, which were selected from the literature with known pKa(water) and pKa(MeCN). Highly well-correlated pKa values were obtained when the calculations were performed with the isodesmic method at the M062X/6-31G** level of theory in conjunction with SMD solvation model for nitrogen-containing heterocycles. Finally, experimentally unknown pKa(MeCN) values of eight thiazol-2-imine structures, which were previously synthesized by some of us, are proposed.

Machine learning methods for pKa prediction of small molecules: Advances and challenges

The acid-base dissociation constant (pK_a) is a fundamental property influencing many ADMET properties of small molecules. However, rapid and accurate pK_a prediction remains a great challenge. In this review, we outline the current advances in machine-learning-based QSAR models for pK_a prediction, including descriptor-based and graph-based approaches, and summarize their pros and cons. Moreover, we highlight the current challenges and future directions regarding experimental data, crucial factors influencing pK_a and in silico prediction tools. We hope that this review can provide a practical guidance for the follow-up studies.

Enhanced electrochemical removal of sulfadiazine using stainless steel electrode coated with activated algal biochar

With the increasingly discharging and inappropriately disposing of antibiotics from human disease treatment and breeding industry, extensive development of antibiotic resistance in bacteria raised serious public health concern. In this work, algal biochar was coated onto the stainless steel mesh, and was employed as cathodic electrode for the degradation of sulfadiazine (SDZ) in an electro-Fenton (EF) system. It was found that algal biochar pyrolyzed at 600 °C with 1:1 KOH achieved best catalytic performance to generate H₂O₂ via oxygen reduction. Moreover, removal efficiency of SDZ reached 96.11% in 4 h with an initial concentration of 25 μg/mL, under the optimized condition as: initial pH at 3, 50 mM of Na₂SO₄ as electrolyte and an applied current of 20 mA/cm². In addition, it was found that the SDZ removal kept at about 96.99% even after four repeated degradation process. Moreover, four possible SDZ degradative pathways during the EF process were proposed according to determined intermediates, model optimization and density functional theory calculation. Finally, acute and chronic biotoxicity of the degradative products against fish and green algae was evaluated, to further elaborate the environmental impact of SDZ after electrochemical degradation.

Stacking Gaussian processes to improve [Formula: see text] predictions in the SAMPL7 challenge

Accurate predictions of acid dissociation constants are essential to rational molecular design in the pharmaceutical industry and elsewhere. There has been much interest in developing new machine learning methods that can produce fast and accurate pKa predictions for arbitrary species, as well as estimates of prediction uncertainty. Previously, as part of the SAMPL6 community-wide blind challenge, Bannan et al. approached the problem of predicting [Formula: see text]s by using a Gaussian process regression to predict microscopic [Formula: see text]s, from which macroscopic [Formula: see text] values can be analytically computed (Bannan et al. in J Comput-Aided Mol Des 32:1165-1177). While this method can make reasonably quick and accurate predictions using a small training set, accuracy was limited by the lack of a sufficiently broad range of chemical space in the training set (e.g., the inclusion of polyprotic acids). Here, to address this issue, we construct a deep Gaussian Process (GP) model that can include more features without invoking the curse of dimensionality. We trained both a standard GP and a deep GP model using a database of approximately 3500 small molecules curated from public sources, filtered by similarity to targets. We tested the model on both the SAMPL6 and more recent SAMPL7 challenge, which introduced a similar lack of ionizable sites and/or environments found between the test set and the previous training set. The results show that while the deep GP model made only minor improvements over the standard GP model for SAMPL6 predictions, it made significant improvements over the standard GP model in SAMPL7 macroscopic predictions, achieving a MAE of 1.5 [Formula: see text].

Insights on a new sulfonamide chalcone with potential antineoplastic application

Chalcones (E)-1,3-diphenyl-2-propene-1-ones, a class of biosynthetic precursor molecules of flavonoids, have a wide variety of biological applications. Besides the natural products, many synthetic derivatives and analogs became an object of continued interest in academia and industry. In this work, a synthesis and an extensive structural study were performed on a sulfonamide chalcone 1-Benzenesulfonyl-3-(4-bromobenzylidene)-2-(2-chlorophenyl)-2,3-dihydro-1H-quinolin-4-one with potential antineoplastic application. In addition, in silico experiments have shown that the sulfonamide chalcone fits well in the ligand-binding site of EGFR with seven μ-alkyl binding energy interactions on the ligand-binding site. Finally, the kinetic stability and the pharmacophoric analysis for EGFR indicated the necessary spatial characteristics for potential activity of sulfonamide chalcone as an antagonist.

SAMPL7 blind challenge: quantum-mechanical prediction of partition coefficients and acid dissociation constants for small drug-like molecules

The physicochemical properties of a drug molecule determine the therapeutic effectiveness of the drug. Thus, the development of fast and accurate theoretical approaches for the prediction of such properties is inevitable. The participation to the SAMPL7 challenge is based on the estimation of logP coefficients and pK_a values of small drug-like sulfonamide derivatives. Thereby, quantum mechanical calculations were carried out in order to calculate the free energy of solvation and the transfer energy of 22 drug-like compounds in different environments (water and n-octanol) by employing the SMD solvation model. For logP calculations, we studied eleven different methodologies to calculate the transfer free energies, the lowest RMSE value was obtained for the M06L/def2-TZVP//M06L/def2-SVP level of theory. On the other hand, we employed an isodesmic reaction scheme within the macro pK_a framework; this was based on selecting reference molecules similar to the SAMPL7 challenge molecules. Consequently, highly well correlated pK_a values were obtained with the M062X/6-311+G(2df,2p)//M052X/6-31+G(d,p) level of theory.

Metal-Free Electrochemical Synthesis of Sulfonamides Directly from (Hetero)arenes, SO2 , and Amines

Sulfonamides are among the most important chemical motifs in pharmaceuticals and agrochemicals. However, there is no methodology to directly introduce the sulfonamide group to a non-prefunctionalized aromatic compound. Herein, we present the first dehydrogenative electrochemical sulfonamide synthesis protocol by exploiting the inherent reactivity of (hetero)arenes in a highly convergent reaction with SO2 and amines via amidosulfinate intermediate. The amidosulfinate serves a dual role as reactant and supporting electrolyte. Direct anodic oxidation of the aromatic compound triggers the reaction, followed by nucleophilic attack of the amidosulfinate. Boron-doped diamond (BDD) electrodes and a HFIP-MeCN solvent mixture enable selective formation of the sulfonamides. In total, 36 examples are demonstrated with yields up to 85 %.

Enhancing Carbon Acid pKa Prediction by Augmentation of Sparse Experimental Datasets with Accurate AIBL (QM) Derived Values

The prediction of the aqueous pKa of carbon acids by Quantitative Structure Property Relationship or cheminformatics-based methods is a rather arduous problem. Primarily, there are insufficient high-quality experimental data points measured in homogeneous conditions to allow for a good global model to be generated. In our computationally efficient pKa prediction method, we generate an atom-type feature vector, called a distance spectrum, from the assigned ionisation atom, and learn coefficients for those atom-types that show the impact each atom-type has on the pKa of the ionisable centre. In the current work, we augment our dataset with pKa values from a series of high performing local models derived from the Ab Initio Bond Lengths method (AIBL). We find that, in distilling the knowledge available from multiple models into one general model, the prediction error for an external test set is reduced compared to that using literature experimental data alone.

Sequence-defined oligoampholytes using hydrolytically stable vinyl sulfonamides: design and UCST behaviour

Water soluble sequence-defined oligoampholytes with precisely positioned charges were synthesised via an iterative solid-phase synthesis protocol using vinyl sulfonamide and acrylate building blocks.

Raise the anchor! Synthesis, X-ray and NMR characterization of 1,3,5-triazinanes with an axial tert-butyl group

N-t-Bu-N',N''-Disulfonamide-1,3,5-triazinanes were synthesized and characterized by X-ray single crystal structure analysis. In the course of the X-ray structure elucidation, the first solid experimental evidence of the axial position of the tert-butyl group in unconstrained hexahydro-1,3,5-triazacyclohexanes was obtained. Dynamic low-temperature NMR analysis allowed to fully investigate a rare case of crystallization-driven unanchoring of the tert-butyl group in the chair conformation of saturated six-membered cycles. DFT calculations show that the use of explicit solvent molecules is necessary to explain the equatorial position of the t-Bu group in solution. Otherwise, the axial conformer is the thermodynamically stable isomer.

A water-soluble bithiophene with increased photoluminescence efficiency and metal recognition ability

A new water-soluble tri-tert-butyl-bithiophenesulfonamide (α2-tbS) was synthesized and a comprehensive spectroscopic and photophysical study was undertaken in organic solvents and water at different pH values. In contrast to the behaviour found for the parent (and un-substituted) α,α'-bithiophene (α2), in which radiationless decay processes are the main excited-state deactivation channels, the tert-butylsulfonamide derivative presents a significant fluorescence quantum yield (φF) (ca. one order of magnitude higher than that of α2). The high φF allowed further exploring α2-tbS as a selective fluorimetric sensor for metal ions. A strong selectivity towards Cu(ii) is observed at neutral pH values, whereas at pH = 9.5 a strong quenching upon the addition of Hg(ii) is observed. An additional high sensitivity of 0.64 ± 0.02 ppm towards Cu(ii) was observed, well below 1.25 ppm (∼20 μM), the maximum value allowed in drinking water by the EPA.

Intramolecular sp2-sp3 Disequalization of Chemically Identical Sulfonamide Nitrogen Atoms: Single Crystal X-Ray Diffraction Characterization, Hirshfeld Surface Analysis and DFT Calculations of N-Substituted Hexahydro-1,3,5-Triazines

In this manuscript, the synthesis and single crystal X-ray diffraction characterization of four N-substituted 1,3,5-triazinanes are reported along with a detailed analysis of the noncovalent interactions observed in the solid state architecture to these compounds, focusing on C–H···π and C–H···O H-bonding interactions. These noncovalent contacts have been characterized energetically by using DFT calculations and also by Hirshfeld surface analysis. In addition, the supramolecular assemblies have been characterized using the quantum theory of “atoms-in-molecules” (QTAIM) and molecular electrostatic potential (MEP) calculations. The XRD analysis revealed a never before observed feature of the crystalline structure of some molecules: symmetrically substituted 1,3,5-triazacyclohexanes possess two chemically identical sulfonamide nitrogen atoms in different sp2 and sp3-hybridizations.

Aqueous pKa prediction for tautomerizable compounds using equilibrium bond lengths

The accurate prediction of aqueous pK_a values for tautomerizable compounds is a formidable task, even for the most established in silico tools. Empirical approaches often fall short due to a lack of pre-existing knowledge of dominant tautomeric forms. In a rigorous first-principles approach, calculations for low-energy tautomers must be performed in protonated and deprotonated forms, often both in gas and solvent phases, thus representing a significant computational task. Here we report an alternative approach, predicting pK_a values for herbicide/therapeutic derivatives of 1,3-cyclohexanedione and 1,3-cyclopentanedione to within just 0.24 units. A model, using a single ab initio bond length from one protonation state, is as accurate as other more complex regression approaches using more input features, and outperforms the program Marvin. Our approach can be used for other tautomerizable species, to predict trends across congeneric series and to correct experimental pK_a values.