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Abstract

A series of 12 new thiazolidine-2,4-dione derivatives were obtained by microwave-assisted synthesis. All compounds were physicochemically characterized by quantitative elemental C, H, N, S analysis and spectral data (mass spectrometry [MS], infrared [IR], and nuclear magnetic resonance [NMR]), with the results being in agreement with the expected data. An in vitro screening performed on Candida albicans ATCC 10231 showed their moderate antifungal activity, which was further investigated by determining the minimum inhibitory concentration and minimum fungicidal concentration values for the most active compounds on four strains of Candida. The molecular docking studies, performed against a fungal lanosterol 14α-demethylase, emphasized the importance of different molecular fragments in the compounds’ structures for their antifungal activity. The synthesized compounds were subjected to in silico screening for the prediction of their absorption, distribution, metabolism, excretion, and toxicity (ADMET) and molecular properties. The results of the antifungal activity assays, docking study, and ADMET predictions revealed that the synthesized compounds are potential anti-Candida agents that might act by interacting with the fungal lanosterol 14α-demethylase and could be further optimized and developed as antifungal agents.

Keywords

thiazolidine-2,4-dione antifungal activity docking lanosterol 14α-demethylase ADMET predictors

Introduction

Heterocyclic compounds containing nitrogen, oxygen, and sulfur atoms are known for exhibiting a wide spectrum of pharmacological activities.^1–5 Since the anticonvulsant, antimicrobial, and antihyperglycemic potential of several thiazolidine-2,4-dione-bearing compounds was reported, this moiety has been intensively studied in the last decades.³ Thiazolidine-2,4-dione derivatives have been also identified as potential inhibitors of lanosterol 14α-demethylase.⁴

Infections caused by invasive and pathogenic fungi, especially in high-risk and immunocompromised patients, represent some of the most life-threatening diseases worldwide.^5–7 The opportunistic yeasts that belong to the Candida genus are the most common human fungal pathogens. Antifungals belonging to the azoles class, such as fluconazole, which act by inhibiting the fungal lanosterol 14α-demethylase, are extensively used for fungal infection therapy. Limited therapeutic choices for the control of fungal diseases, the systemic toxicity, and the pharmacokinetic deficiencies of some authorized antifungals, combined with the continuously increasing risk of antifungal resistance, resulted in the need for developing novel antifungal agents.^5,7,8

Lipophilicity is a physicochemical property that affects a drug’s pharmacokinetics and pharmacodynamics;⁹ thus, computational prediction of lipophilicity is essential for the improvement of the absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties from the first steps of drug discovery. Suboptimal pharmacokinetic properties and increased toxicity can lead to a drug’s failure in the development phases; therefore, in silico prediction of ADMET properties of new drug candidates could be useful for eliminating the molecules that will probably fail in the early stages of drug development.

Based on these facts and as a continuation of our research on heterocyclic compounds bearing sulfur and nitrogen atoms, we designed and synthesized under microwave irradiation new thiazolidine-2,4-dione derivatives as potential antifungal agents. The compounds’ antifungal properties were assessed in vitro against several fungal strains, and their affinity toward the fungal lanosterol 14α-demethylase and their ADMET properties were determined in silico in order to select potential lead compounds that could be further optimized into potential anti-Candida agents.

Materials and Methods

Chemistry

Reagents and solvents used for synthesis were of analytical-grade purity and purchased from Alfa Aesar (Karlsruhe, Germany) and Merck (Darmstadt, Germany). Microwave-assisted synthesis was performed using a CEM Discover BenchMate reactor, in open-vessel mode, under a condenser and with magnetic stirring. The synthetic route ( Fig. 1 ), followed to obtain the series of compounds 7a–f and 8a–f and the intermediates 4 and 5, is based on modified protocols that were previously reported in the literature.^1,3,10 The chemical syntheses were monitored by thin-layer chromatography. The melting points were determined using an electrothermal melting point meter in a glass open capillary. Elemental analysis of the final compounds 7a–f and 8a–f was performed on a Vario El CHNS instrument. Mass spectrometry (MS) analyses were performed on an Agilent 1100 series in positive ionization with an Agilent Ion Trap SL mass spectrometer (Agilent, Santa Clara, CA). Infrared (IR) spectra were recorded using a Jasco FT/IR 6100 spectrometer (Jasco, Easton, MD), after compression under vacuum in anhydrous KBr. ¹H-NMR analyses were performed in DMSO-d₆ (δ_H = 2.51 ppm) as solvent on a Bruker Avance nuclear magnetic resonance (NMR) spectrometer (Karlsruhe, Germany), operating at 500 MHz, with tetramethylsilane (TMS) as the internal standard. ¹³C-NMR spectra were recorded on a Bruker Avance NMR spectrometer, operating at 125 MHz, in DMSO-d₆, using a Waltz-16 decoupling scheme, with TMS as the internal standard.

Figure 1.

Route followed in order to obtain the thiazolidine-2,4-dione derivatives 7a–-f and 8a–f.

The protocols for the synthesis of 5-(hydroxybenzylidene)thiazolidine-2,4-diones (4 and 5) and 3,5-disubstituted thiazolidine-2,4-diones (7a–f and 8a–f) are presented in the Supplementary Material.

Antifungal Assay

Stock solutions (1 mg/mL) were prepared by dissolving the test compounds 4, 5, 7a–f, and 8a–f and the reference antifungal (fluconazole) in sterile DMSO. These solutions were stored in a refrigerator at 4 °C. The solvent used (DMSO) showed no inhibition of fungal growth and was used as negative control.

Determination of Inhibition Zone Diameters

The antifungal screening was based on the agar disk diffusion method against Candida albicans ATCC 10231, according to the guidelines of the National Committee for Clinical Laboratory Standards.¹¹ Fifty microliters of each stock solution corresponding to 50 µg of each compound in DMSO was applied in 6 mm diameter wells cut from agar. Plates inoculated with fungus were incubated for 48 h at 37 °C. The anti-Candida effect of the tested compounds was assessed by measuring the diameter of the inhibition zone. All tests were performed in triplicate, and the average was taken as the final reading.

Determination of Minimum Inhibitory Concentration and Minimum Fungicidal Concentration Values

For the compounds that exhibited the best in vitro anti-Candida activity through the screening assay using the diffusimetric method, the minimum inhibitory concentration (MIC) and minimum fungicidal concentration (MFC) were determined.

The microorganisms used for this assay were obtained from the University of Agricultural Sciences and Veterinary Medicine, Cluj-Napoca, Romania. The MIC and MFC values were determined against cultures of C. albicans ATCC 10231, C. albicans ATCC 18804, Candida krusei ATCC 6258, and Candida parapsilosis ATCC 22019. Fluconazole was used as reference antifungal.

Antifungal activity was tested by using the broth microdilution method according to the Clinical and Laboratory Standards Institute (CLSI) guidelines,¹² following a previously reported protocol.¹³ The growth control, sterility control, and control of antifungal compounds were used. The MIC was defined as the lowest concentration required for arresting the growth of fungi. The MFC was defined as the lowest concentration of the agent at which no colonies are observed. All MIC and MFC experiments were repeated three times.

Statistical Analysis

The results of the inhibition zone diameter determination assay were expressed as mean ± standard deviation (SD) of three independent experiments. Statistical comparisons between groups were made using one-way analysis of variance (ANOVA). A value of p < 0.05 was considered to be statistically significant. Analysis was performed using the R environment for statistical computing and graphics, version 3.2.3.

Molecular Docking Study

The molecular docking study was carried out using AutoDock 4.2¹⁴ against a fungal lanosterol 14α-demethylase. A validated experimental structure of lanosterol 14α-demethylase isolated from C. albicans, taken from the Protein Data Bank (PDB ID: 5-FSA), was used as a target. Compounds were docked in the active site of the enzyme, in a cubic space, with edges equal to 75 points. AutoDock searched for 50 conformations. The cluster inclusion criteria of the resulting poses were set to a 2 Å root mean square deviation limit. The search space was defined by center Cartesian coordinates x = 192.556, y = 1.102, and z = 38.147. Files of ligands and macromolecules were prepared using a previously reported protocol.^6,13 The charge of the iron atom from heme was set to +2.

ADMET and Molecular Property Predictions

The new compounds were subjected to a theoretical in silico ADMET prediction study using the web tool SwissADME (http://www.swissadme.ch/), taking into account the Lipinski rule of 5 (RO5).

We have assessed the topological polar surface area (TPSA)¹⁵ and the logarithm of the compound partition coefficient between n-octanol and water (LogP),^16,17 important descriptors in the prediction of bioavailability and the passive transport of an active compound by the blood–brain barrier.¹⁸ Bioavailability is highly multifactorial but is primarily driven by gastrointestinal absorption.¹³ Solubility is an important aspect in designing new molecules and was computed.¹⁹ Being a substrate to P-glycoprotein or an inhibitor of various CYP isoenzymes was computed by built-in functions of SwissADME.

Results and Discussion

Chemistry

The structures of the synthesized compounds were confirmed by elemental analysis and spectral data (¹H-NMR, ¹³C-NMR, Fourier transform [FT]–IR, and MS). All C, H, N, S quantitative elemental analysis data were in agreement with the calculated values, within ±0.4% of the theoretical values.

Microwave-assisted Knoevenagel condensation in position 5 of 2,4-thiazolidinedione (1) with aromatic aldehydes (2 and 3) led to the 5-(hydroxybenzylidene)-thiazolidine-2,4-diones 4 and 5. Spectral analysis of the obtained compounds 4 and 5 proved that Knoevenagel condensation was successful. The phenolic arylidene group gave supplementary signals in the IR spectrum: a broad band at approximately 3400 cm^–-1 because of the stretching of the O–H phenolic bond and signals between 1341 and 1338 cm^–1 and 688 and 680 cm^–1 because of bending in plane and out of plane, respectively, of the O–H bond. The mass spectra of compounds 4 and 5 revealed the correct molecular ion peaks [M+H]⁺. By reacting the intermediate compounds 4 and 5 with various aliphatic halogenated derivatives (6a–f) in an alkaline medium, we obtained the disubstituted compounds (phenolic oxygen and thiazolidine-2,4-dione nitrogen) in only one step.

In the ¹H-NMR spectra of the final compounds 7a–f and 8a–f, the absence of a singlet signal of one proton near 12.50 and 9.5 ppm confirmed that N-alkylation and O-alkylation were successful. Furthermore, the disappearance in the IR spectra of a broad band near 3424–3416 cm^–1, corresponding to the stretching of the phenolic O–H bond, and the appearance of two signals between 1287–1227 and 1048–1011 cm^–1, corresponding to alkyl-aryl ether asymmetric and symmetric stretching, confirmed that the O-alkylation of the intermediate compounds was successful. The disappearance of the signal corresponding to the N–H bond from the thiazolidine-2,4-dione confirmed that the N-alkylation reaction took place. The mass spectra of the final compounds 7a–f and 8a–f revealed the correct molecular ion peaks [M+H]⁺. The ¹H-NMR spectra is consistent with the expected data. The ¹H-NMR spectra showed one singlet for the methylidene proton between 7.83 and 7.89 ppm. The ¹³C-NMR spectra of the synthesized compounds were consistent with the proposed structures. All spectral data and elemental C, H, N, and S analyses confirmed the structures of the title compounds 7a–f and 8a–f.

Antifungal Activity

Determination of Inhibition Zone Diameters

The results of the antifungal activity screening of compounds 4, 5, 7a–f, and 8a–f are presented in Table 1 .

Table 1.

Zone of Inhibition (mm) of Tested Compounds 4, 5, 7a–f, and 8a–f against C. albicans ATCC 10231.

Compound	Inhibition Zone Diameter (mm)
4	12 ± 0.2
5	12 ± 0.2
7a	18 ± 0.5
7b	14 ± 0.2
7c	18 ± 0.5
7d	14 ± 0.2
7e	18 ± 0.2
7f	14 ± 0.2
8a	16 ± 0.5
8b	14 ± 0.2
8c	14 ± 0.2
8d	14 ± 0.2
8e	16 ± 0.5
8f	14 ± 0.5
Fluconazole	24 ± 1

The value obtained for each compound represents the mean of three independent measurements ± SD. The values obtained for the most active compounds are marked in bold.

Both intermediate compounds 4 and 5 had an inhibition diameter equal to 12 mm and are considered with weak antifungal activity. The final compounds 7a–f and 8a–f displayed higher inhibition zone diameters than both intermediates 4 and 5, suggesting that the dialkylation of 5-(hydroxybenzylidene)thiazolidine-2,4-diones 4 and 5 is favorable to the antifungal activity. The most active compounds were 7a, 7c, and 7e. All tested compounds presented lower inhibition zone diameters than fluconazole (p < 0.05).

Minimum Inhibitory Concentration and Minimum Fungicidal Concentration

In the initial in vitro anti-Candida screening, compounds 7a, 7c, 7e, 8a, and 8e presented the best antifungal activity ( Table 1 ), so the MICs and MFCs of these compounds, in comparison with those of fluconazole (used as the reference antifungal), were further determined. The obtained results are presented in Table 2 . The MICs and MFCs were determined against C. albicans ATCC 10231, C. albicans ATCC 18804, C. krusei ATCC 6258, and C. parapsilosis ATCC 22019, using the broth microdilution method. The inoculum control presented growth in all concentrations, and the broth control had no growth.

Table 2.

Minimum Inhibitory Concentration (μg/mL) and Minimum Fungicidal Concentration (μg/mL) of Compounds 7a, 7c, 7e, 8a, and 8e.

	C. albicans ATCC 10231		C. albicans ATCC 18804		C. krusei ATCC 6258		C. parapsilosis ATCC 22019
Compound	MIC	MFC	MIC	MFC	MIC	MFC	MIC	MFC
7a	15.62	31.25	15.62	31.25	15.62	31.25	15.62	31.25
7c	31.25	62.5	15.62	31.25	15.62	31.25	15.62	15.62
7e	62.5	62.5	31.25	31.25	31.25	62.5	31.25	62.5
8a	31.25	62.5	31.25	62.5	31.25	62.5	15.62	31.25
8e	62.5	125	62.5	125	62.5	125	31.25	62.5
Fluconazole	15.62	31.25	15.62	31.25	15.62	31.25	7.81	15.62

The values obtained for the most active compounds are marked in bold.

The most active compound was 7a, having similar anti-Candida activity as fluconazole (p < 0.05), used as the positive control. For these compounds, on all Candida strains, the MIC and MFC values were 15.62 and 31.25 μg/mL, respectively. The same MIC and MFC values were found for fluconazole. The C. parapsilosis strain used in the study seemed to be less susceptible to the tested compounds than fluconazole (p < 0.05). Substitution of intermediates 4 and 5 generally increases the anti-Candida potential. In our series, the most active compound was 7a, with an antifungal activity similar to that of fluconazole (p < 0.05), suggesting that the presence of arylcarbonylmethyl groups is more favorable to the inhibitory activity toward Candida.

The MFC/MIC ratio for all tested compounds ranged from 1 to 2, suggesting that all the synthesized thiazolidine-2,4-one derivatives could act as fungicidal agents.²⁰

Molecular Docking Study

The results of the molecular docking study show the best binding affinities of the compounds in the active site of lanosterol 14α-demethylase and their consequent predicted inhibition constants ( Table 3 ).

Table 3.

Predicted Binding Affinity of Tested Compounds to Lanosterol 14α-Demethylase (ΔG) and the Predicted Inhibition Constant (Ki) and Its Cluster Analysis.

Compound	ΔGmin (kcal/mol)	Ki (nM)	2 Å Cluster of the Best Binding Conformation
Compound	ΔGmin (kcal/mol)	Ki (nM)	Number of Conformations	Mean ΔG (kcal/mol)
4	−7.32	4308.88	26	−7.31
5	−7.42	3639.68	28	−7.38
7a	−12.44	0.76	9	−11.99
7b	−9.44	120.33	34	−8.96
7c	−9.91	54.43	41	−9.23
7d	−9.50	108.74	21	−8.52
7e	−11.58	3.25	39	−11.02
7f	−8.59	505.17	39	−8.15
8a	−12.18	1.18	3	−11.64
8b	−9.22	174.44	19	−8.51
8c	−9.52	105.13	27	−8.90
8d	−9.10	213.60	15	−8.53
8e	−11.8	2.24	25	−10.90
8f	−8.23	927.52	25	−7.89
Fluconazole	–6.71	12,064.26	12	–6.13

The best binding compound is considered 7a, with ΔG = −12.44 kcal/mol and, consequently, Ki = 0.76 nM. Its binding mode is presented in Supplementary Figure S1 . Disubstitution of compounds with a large residue such as R_a or carboxylic such as R_e is probable to give a higher inhibition potential of the enzyme.

An interesting aspect is that ligands substituted with aromatic rings have fewer conformations in the 2 Å cluster (their proposed binding modes are less homogeneous than those substituted with smaller alkyl moieties); thus, they have many clusters with few conformations.

Also, compounds substituted in position 2 (the salicyl derivatives) bind less homogeneously and have lower binding energies in comparison with the 3-hydroxy derivatives.

The C=O groups from the substituents are important for the formation of hydrogen bonds with Ser378. The absence of ketone groups from the side chains of compounds 7f and 8f led to a lower binding affinity to the catalytic site of the enzyme due to the lack of interactions with Ser378 and the iron atom from heme. The C=O groups from thiazolidine-2,4-dione are important for the formation of hydrogen bonds with Ser378, Tyr118, and Met508. Substitution increases overall the binding affinity, compared with the parent compounds 4 and 5. The potential polar interaction between an iron atom from heme and an oxygen from the C=O bond is predicted, as shown in Supplementary Figure S1 .

ADMET and Molecular Property Predictions

The results of virtual screening, carried out with SwissADME, for the following descriptors are presented in Table 4 : molecular weight (MW), number of rotatable bonds (RoB; the number of any single nonring bond, linked to nonterminal heavy atom-amide C–N bonds, is not considered because of their high rotational energy barrier²¹), hydrogen bond acceptors (HBAs; the sum of all oxygen and nitrogen atoms, according to the RO5 definition²²), hydrogen bond donors (HBDs; the sum of all –OH and –NH, according to the RO5 definition²²), TPSA, and the LogP characterizing lipophilicity. The penetration of the blood–brain barrier was evaluated only based on the values predicted for MW, LogP, HBA, HBD, and TPSA, as specified in the literature.²³

Table 4.

Results of Virtual Screening Carried Out for ADMET Descriptors.

Compound	MW (Da)	RoB	HBA	HBD	TPSA	iLogP	mLogP
4	221.23	1	4	2	95.19	1.31	1.07
5	221.23	1	4	2	95.19	1.34	1.07
7a	457.5	8	5	0	106.05	3.31	2.27
7b	335.34	6	7	4	160.07	1.1	0.01
7c	333.36	6	5	0	106.05	2.42	0.48
7d	393.41	10	7	0	124.51	3.53	1
7e	337.3	6	7	2	146.51	1.37	0.01
7f	309.34	6	5	2	112.37	2.2	0.13
8a	457.5	8	5	0	106.05	3.23	2.27
8b	335.34	6	7	4	160.07	0.95	0.01
8c	333.36	6	5	0	106.05	2.25	0.48
8d	393.41	10	7	0	124.51	3.42	1
8e	337.3	6	7	2	146.51	1.32	0.01
8f	309.34	6	5	2	112.37	2.24	0.13
Fluconazole	306.27	5	7	1	81.65	0.41	1.47

iLogP = implicit logarithm of the compound partition coefficient between n-octanol and water; mLogP = Moriguchi’s logarithm of the compound partition coefficient between n-octanol and water.

All compounds passed the RO5, having MW < 500 Da, mLogP < 4.15, less than 10 HBAs, and less than 5 HBDs. Also, all compounds passed the TPSA limit to 140 Å², except 7b and 8b, which far exceeded it (160.07 Å²), and 7e and 8e, which slightly exceeded it (146.51 Å²).

Regarding compounds’ lipophilicity, it was observed that the presence of voluminous substituents (such as phenylcarbonylmethyl in compounds 7a and 8a) or ester groups (in compounds 7d and 8d) considerably increased the lipophilicity of the compounds, whereas introducing polar groups, such as amide (7b and 8b) and carboxyl (7e and 8e), led to lower values of LogP.

The predicted solubility, gastrointestinal absorption, blood–brain barrier penetrability, P-glycoprotein affinity, and CYP inhibition of the synthesized compounds are summarized in Table 5 . Compounds 7a and 8a are predicted to have a poor solubility; others are predicted to be soluble or moderately soluble. Compounds that exceed the TPSA limit are predicted to have a low gastrointestinal absorption; others are predicted to have a high gastrointestinal absorption. No compound is predicted to pass the blood–brain barrier, so the risk of adverse central nervous system effects is diminished. Regarding CYP inhibition, unlike fluconazole, eight of the newly synthesized compounds presented no affinity toward CYP isoenzymes; therefore, there is a lower risk for interactions with drugs that are metabolized through CYP450 isoforms.

Table 5.

Predicted Solubility, Gastrointestinal Absorption, Blood–Brain Barrier Penetrability, P-Glycoprotein Affinity, and CYP Inhibition of the Synthesized Compounds.

	Solubility^a					CYP Inhibition
Compound	LogS	Class	GIA	BBBP	Pgp Substrate	CYP1A2	CYP2C19	CYP2C9	CYP2D6	CYP3A4
4	−3.8	Soluble	High	No	No	No	No	No	No	No
5	−3.8	Soluble	High	No	No	No	No	No	No	No
7a	−7.14	Poorly soluble	High	No	No	No	Yes	Yes	No	Yes
7b	−4.7	Moderately soluble	Low	No	No	No	No	No	No	No
7c	−3.7	Soluble	High	No	No	Yes	Yes	Yes	No	No
7d	−5.2	Moderately soluble	High	No	No	Yes	Yes	Yes	No	Yes
7e	−4.23	Moderately soluble	Low	No	No	No	No	No	No	No
7f	−2.93	Soluble	High	No	No	No	No	No	No	No
8a	−7.14	Poorly soluble	High	No	No	No	Yes	Yes	No	Yes
8b	−4.7	Moderately soluble	Low	No	No	No	No	No	No	No
8c	−3.7	Soluble	High	No	No	Yes	Yes	Yes	No	No
8d	−5.2	Moderately soluble	High	No	No	Yes	Yes	Yes	No	Yes
8e	−4.23	Moderately soluble	Low	No	No	No	No	No	No	No
8f	−2.93	Soluble	High	No	No	No	No	No	No	No
Fluconazole	−1.63	Very soluble	High	No	No	No	Yes	No	No	No

LogS = logarithm of water solubility; GIA = gastrointestinal absorption; BBBP = blood–brain barrier permeant; Pgp = P-glycoprotein.

Water solubility.

Conclusions

In the search for new antifungal agents, 12 novel thiazolidine-2,4-dione derivatives were synthesized by microwave-assisted synthesis and tested in vitro for their antifungal properties, against several strains of Candida, by the disk diffusion method and broth microdilution method. The structures of all synthesized compounds were confirmed by physical data, MS, ¹H-NMR, ¹³C-NMR, and IR spectroscopy and quantitative elemental analyses. The synthesized compounds presented moderate to good antifungal activity that might be improved by further research studies. Compound 7a displayed an anti-Candida potential similar to that of fluconazole, used as a reference drug, against several strains of fungi. Substitution of parent compounds with large aromatic fragments with C=O groups is the most favorable substitution for anti-Candida activity.

For all the studied compounds, a lipophilicity augmentation was observed by introducing ester groups or phenylcarbonyloxomethyl rests. The thorough virtual screening carried out for ADMET profiling of the thiazolidine-2,4-dione derivatives led to the conclusion that based on the predicted values of physicochemical descriptors, all derivatives are small molecules with good predictions for oral bioavailability according to RO5, thus making them suitable for systemic use. An absence of blood–brain barrier penetrability was also forecasted for all the synthesized compounds, thus making them less likely to possess central nervous system adverse effects.

Footnotes

Supplementary material is available online with this article.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The work reported in this paper was financially supported by the “Iuliu Hat̨ieganu” University of Medicine and Pharmacy, Cluj-Napoca, PCD 7690/68/15.04.2016 and 5200/59/01.03.2017.

ORCID iD

Anca Stana

References

Stana

Tiperciuc

Duma

et al . Synthesis and Antimicrobial Activity of Some New N-Substituted-5-Arylidene-Thiazolidine-2,4-Diones. J. Heterocycl. Chem. 2014, 51, 411–417.

Serge

Bikobo

Vodnar

D. C.

et al . Synthesis of 2-Phenylamino-Thiazole Derivatives as Antimicrobial Agents. J. Saudi Chem. Soc. 2017, 21, 861–868.

Chadha

Bahia

M. S.

Kaur

et al . Thiazolidine-2,4-Dione Derivatives: Programmed Chemical Weapons for Key Protein Targets of Various Pathological Conditions. Bioorg. Med. Chem. 2015, 23, 2953–2974.

Zhang

et al . From Antidiabetic to Antifungal: Discovery of Highly Potent Triazole-Thiazolidinedione Hybrids as Novel Antifungal Agents. ChemMedChem 2014, 9, 2639–2646.

Jiang

Zhang

Cao

et al . Synthesis, In Vitro Evaluation and Molecular Docking Studies of New Triazole Derivatives as Antifungal Agents. Bioorg. Med. Chem. Lett. 2011, 21, 4471–4475.

Stoica

C. I.

Marc

Pîrnău

et al . Thiazolyl-Oxadiazole Derivatives Targeting Lanosterol 14α-Demethylase as Potential Antifungal Agents: Design, Synthesis and Molecular Docking Studies. Farmacia 2016, 64, 390–397.

Khedr

Stepwise Design, Synthesis, and In Vitro Antifungal Screening of (Z)-Substituted-Propenoic Acid Derivatives with Potent Broad-Spectrum Antifungal Activity. Drug Des. Devel. Ther. 2015, 4501–4513.

Shah

J. J.

Khedkar

Coutinho

E. C.

et al . Design, Synthesis and Evaluation of Benzotriazole Derivatives as Novel Antifungal Agents. Bioorg. Med. Chem. Lett. 2015, 25, 3730–3737.

Arnott

J. A.

Planey

S. L.

The Influence of Lipophilicity in Drug Discovery and Design. Expert Opin. Drug Discov. 2012, 7, 863–875.

10.

Y. M.

Park

Y. J.

Kim

J. A.

et al . Design and Synthesis of 5-(Substituted Benzylidene)Thiazolidine-2,4-Dione Derivatives as Novel Tyrosinase Inhibitors. Eur. J. Med. Chem. 2012, 49, 245–252.

11.

Clinical and Laboratory Standards Institute. Performance Standards for Antimicrobial Disk Susceptibility Tests; Approved Standard; Clinical and Laboratory Standards Institute: Wayne, PA, 2012; Vol. 32.

12.

Clinical and Laboratory Standards Institute. Reference Method for Broth Dilution Antifungal Susceptibility Testing of Yeasts; Third Informational Supplement—M27-S3. Clin. Lab. Standards Inst. NCCLS 2008, 28.

13.

Stana

Enache

Vodnar

et al . New Thiazolyl-Triazole Schiff Bases: Synthesis and Evaluation of the Anti-Candida Potential. Molecules 2016, 21, 1–19.

14.

Morris

G. M.

Huey

Lindstrom

et al . AutoDock4 and AutoDockTools4: Automated Docking with Selective Receptor Flexibility. J. Comput. Chem. 2009, 30, 2785–2791.

15.

Ertl

Rohde

Selzer

Fast Calculation of Molecular Polar Surface Area as a Sum of Fragment-Based Contributions and Its Application to the Prediction of Drug Transport Properties. J. Med. Chem. 2000, 43, 3714–3717.

16.

Daina

Michielin

Zoete

iLOGP: A Simple, Robust, and Efficient Description of N-Octanol/Water Partition Coefficient for Drug Design Using the GB/SA Approach. J. Chem. Inf. Model. 2014, 54, 3284–3301.

17.

Lipinski

C. A.

Lombardo

Dominy

B. W.

et al . Experimental and Computational Approaches to Estimate Solubility and Permeability in Drug Discovery and Development Settings. Adv. Drug Deliv. Rev. 2001, 46, 3–26.

18.

Daina

Zoete

A Boiled-Egg to Predict Gastrointestinal Absorption and Brain Penetration of Small Molecules. ChemMedChem 2016, 11, 1117–1121.

19.

Ali

Camilleri

Brown

M. B.

et al . Revisiting the General Solubility Equation: In Silico Prediction of Aqueous Solubility Incorporating the Effect of Topographical Polar Surface Area. J. Chem. Inf. Model. 2012, 52, 420–428.

20.

Movahed

Yi Tan

G. M.

Munusamy

et al . Triclosan Demonstrates Synergic Effect with Amphotericin B and Fluconazole and Induces Apoptosis-Like Cell Death in Cryptococcus Neoformans. Front. Microbiol. 2016, 7, 1–10.

21.

Veber

D. F.

Johnson

S. R.

Cheng

H.-Y.

et al . Molecular Properties That Influence the Oral Bioavailability of Drug Candidates. J. Med. Chem. 2002, 45, 2615–2623.

22.

Lipinski

C. A.

Lombardo

Dominy

B. W.

et al . Experimental and Computational Approaches to Estimate Solubility and Permeability in Drug Discovery and Development Settings. Adv. Drug Deliv. Rev. 2012, 64, 4–17.

23.

Jeffrey

Summerfield

Assessment of the Blood–Brain Barrier in CNS Drug Discovery. Neurobiol. Dis. 2010, 37, 33–37.

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3,5-Disubstituted Thiazolidine-2,4-Diones: Design,Microwave-Assisted Synthesis,Antifungal Activity,and ADMET Screening

Abstract

Keywords

Introduction

Materials and Methods

Chemistry

Antifungal Assay

Determination of Inhibition Zone Diameters

Determination of Minimum Inhibitory Concentration and Minimum Fungicidal Concentration Values

Statistical Analysis

Molecular Docking Study

ADMET and Molecular Property Predictions

Results and Discussion

Chemistry

Antifungal Activity

Determination of Inhibition Zone Diameters

Minimum Inhibitory Concentration and Minimum Fungicidal Concentration

Molecular Docking Study

ADMET and Molecular Property Predictions

Conclusions

Footnotes

Declaration of Conflicting Interests

Funding

ORCID iD

References

Supplementary Material