Carboxylic Acid Bioisosteres in Medicinal Chemistry: Synthesis and Properties

Bredael, Kato; Geurs, Silke; Clarisse, Dorien; Bosscher, Karolien De; D’hooghe, Matthias

doi:10.1155/2022/2164558

Cited by 32 publications

(37 citation statements)

References 157 publications

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“…This suggests that tetrazole is even a better replacement of carboxylic acid, and indeed, the AEDs of these two bioisosteric moieties were reported to be identical up to three decimal places, with only 0.2% difference . In fact, tetrazole has been reported in the literature as one of the most common bioisosteres of carboxylic acid. ,,,,, …”

Section: Resultsmentioning

confidence: 91%

“…The 14% AED difference between sulfonamide and carboxylic acid, and the 15% AED difference between furan and carboxylic acid are to be contrasted with the 34% AED difference between sulfonamide and furan. Based on this fact, it is suggests that, while furan and sulfonamide are independently bioisosteric (or suggested bioisosteric) groups of carboxylic acid ,, (), they do not seem to be bioisosteres themselves of each other. This observation is supported by the results reported from the SwissBioisostere website (), which provides potential bioisosteric replacements based on experimental measures collected from the literature.…”

Section: Resultsmentioning

confidence: 99%

“…In fact, carboxylic acid has been successfully substituted with tetrazole to develop many drugs such as cefamandole, ceftezole, tedizolid, letrozole, encequidar, oteseconazole, quilseconazole, losartan, valsartan, candesartan, and tomelukast . In addition, carboxylic acid can be substituted with the chemically and enzymatically more stable sulfonamide bioisostere in order to increase the metabolic resistance of a drug . In non-classical bioisosterism, the similarity in the biological activity is maintained, although the moieties may not share the same physical or chemical properties …”

Section: Introductionmentioning

confidence: 99%

“…9 In addition, carboxylic acid can be substituted with the chemically and enzymatically more stable sulfonamide bioisostere in order to increase the metabolic resistance of a drug. 10 In non-classical bioisosterism, the similarity in the biological activity is maintained, although the moieties may not share the same physical or chemical properties. 11 Computer-aided drug design tools have been heavily involved in assessing bioisosterism.…”

Section: Introductionmentioning

confidence: 99%

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Quantum and Classical Evaluations of Carboxylic Acid Bioisosteres: From Capped Moieties to a Drug Molecule

Osman

Arabi

2022

ACS Omega

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Using the Quantum Theory of Atoms in Molecules, the average electron density (AED) tool was developed and employed to quantitatively evaluate the similarities between bioisosteric moieties in drug design. Bioisosteric replacements are valuable in drug molecules to fine-tune their pharmacokinetic and pharmacodynamic properties while maintaining their biological activity. This study was performed on non-classical bioisosteres of carboxylic acid. It was found that the AED of a given bioisostere is generally transferable, within less than 5% difference, irrespective of its environment. It was shown that the AED tool succeeds at depicting not only the similarities of bioisosteric groups but also at highlighting, as counter examples, the differences in non-bioisosteric groups. For the first time, the AED was used to evaluate bioisosterism in an FDA-approved drug molecule, furosemide, and in five analogues of this medicine. In one of the analogues, non-bioisosteric moieties were exchanged, and in four of the analogues, carboxylic acid was replaced with either furan or sulfonamide, and vice versa. It was also found that irrespective of the pH, the AED tool consistently reproduced experimental predictions. The distinct power of the AED tool in quantitatively and precisely measuring the similarity among bioisosteric groups is contrasted with the relatively ambiguous bioisosteric evaluations through the classical qualitative electrostatic potential (ESP) maps. The ESP maps were demonstrated to fail, even qualitatively, in depicting the similarities, in some cases.

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Section: Resultsmentioning

confidence: 91%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Quantum and Classical Evaluations of Carboxylic Acid Bioisosteres: From Capped Moieties to a Drug Molecule

Osman

Arabi

2022

ACS Omega

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“…In contrast, features that contained carboxylic acids and alcohols had the lowest activity scores presumably due to their ability to form hydrogen bonds ( Abraham et al, 1994 ). At physiological pH of 7.4, carboxylic acids are dissociated to carboxylate ions, which improves their water solubility and the ability to form hydrogen bonds ( Bredael et al, 2022 ). The low lipophilicity of carboxylic acids, at physiological pH, also limits their BBB penetration ( Soloway et al, 1960 ).…”

Section: Discussionmentioning

confidence: 99%

Development of QSAR models to predict blood-brain barrier permeability

et al. 2022

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Assessing drug permeability across the blood-brain barrier (BBB) is important when evaluating the abuse potential of new pharmaceuticals as well as developing novel therapeutics that target central nervous system disorders. One of the gold-standard in vivo methods for determining BBB permeability is rodent log BB; however, like most in vivo methods, it is time-consuming and expensive. In the present study, two statistical-based quantitative structure-activity relationship (QSAR) models were developed to predict BBB permeability of drugs based on their chemical structure. The in vivo BBB permeability data were harvested for 921 compounds from publicly available literature, non-proprietary drug approval packages, and University of Washington’s Drug Interaction Database. The cross-validation performance statistics for the BBB models ranged from 82 to 85% in sensitivity and 80–83% in negative predictivity. Additionally, the performance of newly developed models was assessed using an external validation set comprised of 83 chemicals. Overall, performance of individual models ranged from 70 to 75% in sensitivity, 70–72% in negative predictivity, and 78–86% in coverage. The predictive performance was further improved to 93% in coverage by combining predictions across the two software programs. These new models can be rapidly deployed to predict blood brain barrier permeability of pharmaceutical candidates and reduce the use of experimental animals.

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