A synergistic investigation of azo-thiazole derivatives incorporating thiazole moieties: a comprehensive exploration of their synthesis, characterization, computational insights, solvatochromism, and multimodal biological activity assessment

Abstract

In the present study, a novel series of azo-thiazole derivatives (3a–c) containing a thiazole moiety was successfully synthesized. The structure of these derivatives was examined by spectroscopic techniques, including ¹H NMR, ¹³C NMR, FT-IR, and HRMS. Further, the novel synthesized compounds were evaluated for their in vitro biological activities, such as antibacterial and anti-inflammatory activities, and an in silico study was performed. The antibacterial results demonstrated that compounds 3a and 3c (MIC = 10 μg mL⁻¹) have a notable potency against Staphylococcus aureus compared to azithromycin (MIC = 40 μg mL⁻¹). Alternatively, compound 3b displayed a four-fold higher potency (24 recovery days, 1.83 mg day⁻¹) than Hamazine (28 recovery days, 4.14 mg day⁻¹) in promoting burn wound healing, and it also exhibited a comparable inhibitory activity against screened bacterial pathogens compared to the reference drug. Docking on 1KZN, considering the excellent impact of compounds on the crystal structure of E. coli 1KZN, a 24 kDa domain, in complex with clorobiocin, indicated the close binding of compounds 3a–c with the active site of the 1KZN protein, which is consistent with their observed biological activity. Additionally, we conducted molecular dynamics simulations on the docked complexes of compounds 3a–c with 1KZN retrieved from the PDB to assess their stability and molecular interactions. Furthermore, we assessed their electrochemical characteristics via DFT calculations. Employing PASS and pkCSM platforms, we gained insights into controlling the bioactivity and physicochemical features of these compounds, highlighting their potential as new active agents.

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1 Introduction

The field of drug discovery has witnessed significant advances that are driven by two primary approaches: the pursuit of novel proteins as drug targets and the optimization of clinical drugs. Modern drug discovery relies on novel protein identification and targeting.¹ Advancements in genomics, proteomics, and structural biology have uncovered unexplored areas in the human proteome. Moreover, optimizing clinical drugs by using data from trials and post-marketing surveillance improves their safety, efficacy, and delivery methods.^2–5 Drug repurposing involves reusing known drugs for new therapies, thus enhancing their clinical value. Advances in pharmaceutical chemistry and drug delivery give rise to extended-release formulations, boosting patient compliance and treatment efficacy.^6–9 Recently, bacterial and inflammatory infections have given rise to diverse and serious diseases. Thus, the discovery of novel antibacterial and anti-inflammatory agents holds promise for mitigating these medical challenges. In recent times, medicinal chemistry research has focused on the development of innovative antimicrobial agents, distinguished by their novel structural designs and molecular targets. A pressing concern for healthcare professionals in the foreseeable future is the escalating prevalence of multidrug-resistant pathogenic bacteria, which swiftly develop resistance to commonly utilized antibiotics for the treatment of human infections.^10–12 Thiazole, a pivotal heterocycle, plays a key role in potent biologically active molecules, such as sulfathiazole (an antimicrobial), ritonavir (an antiretroviral), abafungin (an antifungal), bleomycin (a neoplastic agent), and tiazofurin (a neoplastic agent).¹³ Thiazole and its derivatives have found wide applications in the medical field, addressing various conditions, such as hypertension, inflammation, schizophrenia, bacterial infections, and HIV infections.^14–18 Additionally, they have been utilized as antagonists of fibrinogen receptors, displaying antithrombotic characteristics, and as inhibitors of bacterial DNA gyrase B.^19,20 Thiazole frameworks, exemplified by dasatinib and dabrafenib, are known for their potent antitumor effects.^21,22 Azo-thiazole refers to a class of organic compounds that contain both an azo group (N=N) and a thiazole ring in their molecular structure.²³ This unique combination of functional groups contributes to the distinct properties and potential applications of this compound in various fields. However, although heterocyclic compounds containing azo groups have a substantial presence in pharmaceuticals and the development of therapeutic agents, the related literature remains somewhat limited.^24–26 In current scientific investigations, there has been a noticeable increase in attention directed towards producing heterocyclic compounds that integrate azo groups and their related derivatives. This increase is attributed to their notable biological actions, which encompass a wide spectrum of powerful influences including antimicrobial, antifungal, antiviral, anticonvulsant, antidiabetic, anti-inflammatory, antitubercular, DNA binding for anticancer uses, analgesic characteristics, and their potential for chemical sensing activities.^27,28 The molecular hybridization approach represents an effective and frequently employed strategy in contemporary medicinal chemistry research for developing and advancing novel therapeutic agents.^29–31 Considering previously reported results, we opted to develop some new hybrid structures incorporating azo-thiazole in various thiazole ring systems through an acetamide linkage. This combination was proposed in an effort to investigate the impact of this hybridization and structural diversity on the anticipated antibacterial efficacy. Our aim was to introduce greater biological relevance to the compounds of interest. The final synthesized compounds in this study, i.e., azo-thiazole-bearing benzamide thiazole derivatives, were subjected to in vitro antibacterial and in vivo anti-inflammatory and acute toxicity measurements. Moreover, we conducted molecular docking, molecular dynamic simulation and ADME studies.

2 Experimental

2.1. Materials and reagent

All compounds were directly obtained from SIGMA-ALDRICH (UK) and used as received with no further purification. The melting points of the synthesized substances were measured using an uncorrected Bio Core melting point device equipped with open capillaries. The progress of the reactions was observed via thin-layer chromatography (TLC) on aluminum sheets coated with silica gel 60 F254. The mobile phase consisted of ethyl acetate and diethyl ether in a 1 : 1 ratio, and detection was accomplished under UV light. FT-IR spectra were recorded using a Thermo Scientific Nicolet iS50 series FT-IR spectrometer. Spectral information was collected using a JENWAY UV/vis 6705 series single-beam UV/vis scanning spectrophotometer. ¹H and ¹³C NMR spectroscopy was conducted using a BRUKER AVANCE 500 MHz NMR spectrometer with DMSO-d₆ as the solvent. Chemical shifts were recorded in ppm relative to the Me4Si internal standard, and J values were expressed in Hz. High-resolution mass spectrometry (HRMS) data were acquired using an Agilent LC/MSD TOF mass spectrometer.

2.2. Synthesis method

2.2.1. Synthesis of azo compound (3). Thiazol-2-amine (6.4 g, 64 mmol) was dissolved in a 300 mL glass beaker containing 37% w/v HCl (20 mL, 96 mmol) and distilled water (20 mL). The resulting solution was chilled in an ice bath to reach a temperature in the range of 0 °C to 5 °C. Concurrently, NaNO₂ (5 g, 70.4 mmol) was dissolved in 24 mL of distilled water, and also cooled using an ice bath. A thiazole-2-diazonium chloride salt solution was prepared by gradually introducing the NaNO₂ solution in the thiazol-2-amine solution while stirring, ensuring that the temperature was controlled in the range of 0 °C to 5 °C. The obtained solution was maintained in the temperature range of 0 °C to 5 °C for a specific period. In a distinct procedure, a solution containing 2-hydroxybenzoic acid (10 g, 64 mmol) dissolved in 30 mL of a 10% w/v KOH solution was also cooled to 0 °C to 5 °C using an ice bath. The solution containing potassium 2-carboxyphenolate was slowly added with constant stirring to the thiazole-2-diazonium chloride solution until a gel-like substance developed. Subsequently, 60 mL of cold water was incorporated. The mixture was left stirring at room temperature overnight. The resulting compound was collected through filtration, and then subjected to recrystallization from a mixture containing ethanol and water in a 7 : 3 proportion. After characterization, the final product was obtained as a yellow-colored powder.³²
2.2.1.1. 2-Hydroxy-5-(thiazol-2-yldiazenyl)benzoic acid (3). Light brown solid, yield 93.52%, m.p. 129–130 °C. IR cm⁻¹: 3232.05 (OH), 3007.34 (Csp²–H aromatic), 1655.58 (C=O), 1609.95 (C=C aromatic); 1580.33 (–N=N–), and 852.34 (aromatic substituted). ¹H NMR (DMSO-d₆, δ ppm): 6.70–6.72 (1H, d, Ar–H), 7.16–7.18 (1H, d, Ar–H), 7.52 (1H, s, Ar–H), 8.04–8.05 (1H, d, thiazole-H), 8.34–8.35 (1H, d, thiazole-H), 12.26 (1H, s, 1H, s, OH, D₂O exchangeable), 12.99 (1H, s, Ar–COOH). ¹³C NMR (DMSO-d₆, δ ppm): 113.36, 117.56, 119.65, 123.00, 128.0, 130.74, 136.13, 143.74, 161.62, 172.42. HRMS (ESI) (cal.): C₁₀H₇N₃O₃S [M + H]⁺, m/z: 249.02 (100.0%), 250.02 (11.9%), 251.02 (4.5%); (found): 249.0277 (100.0%), 250.0147 (11.9%), 251.0016 (4.5%), 252.0040 (1.1%).

2.2.2. Synthesis of azo-amide derivatives (3a–c). A three-neck 250 mL round-bottom flask, previously dried using a flame, was secured with two glass stoppers. The arrangement was comprised of a vacuum-jacketed Dean–Stark trap linked to a reflux condenser featuring a nitrogen inlet, in addition to a Teflon-coated magnetic stirring bar. In the reaction container, 2-hydroxy-5-(thiazol-2-yldiazenyl)benzoic acid (2.46 g, 15 mmol), boric acid (0.010 g, 0.15 mmol), and 50 mL of toluene were added. The stirred mixture, showing a distinct hue, was then swiftly mixed with amines (a–c) (15.5 mmol) simultaneously. Subsequently, the obtained reaction mixture was refluxed for a duration of 16 h, resulting in the accumulation of around 0.3 mL of water in the Dean–Stark trap. Following the cooling of the mixture to ambient temperature, it was poured with agitation into 250 mL of hexanes, leading to the immediate generation of a white solid precipitate. Stirring was continued for an extra 30 min, after which the precipitate was filtered under suction through a sintered glass filter funnel. Next, the gathered solid was successively rinsed with two 30 mL quantities of hexanes, followed by two 30 mL quantities of distilled water. Subsequently, the solid was subjected to vacuum drying at room temperature for a duration of 12 h, resulting in the formation of the target products (3a–c).³³
2.2.2.1. 2-Hydroxy-N-(thiazol-2-yl)-5-(thiazol-2-yldiazenyl)benzamide (3a). Gray solid, yield 77.11%, m.p. 125–126 °C, IR cm⁻¹: 3232.75 (OH), 3006.51 (Csp²–H aromatic), 1655.05 (C=O), 1608.99 (C=C aromatic); 1578.76 (–N=N–), and 852.00 (aromatic substituted); ¹H NMR (DMSO-d₆, δ ppm): 4.14 (1H, s, 1H, s, OH, D₂O exchangeable), 6.95–6.97 (1H, d, Ar–H), 7.17–7.19 (1H, d, Ar–H), 7.53 (1H, s, Ar–H), 7.80–7.82 (1H, d, CH-thiazole), 7.92–7.94 (1H, d, CH-thiazole). 8.00–8.02 (1H, d, CH-thiazole), 8.24–8.26 (1H, d, CH-thiazole), 11.52 (1H, s, NH, D₂O exchangeable). ¹³C NMR (DMSO-d₆, δ ppm): 115.09, 119.51, 123.08, 127.95, 129.65, 138.88, 143.79, 144.48, 147.10, 164.90, 166.06, 171.33, 176.74. HRMS (ESI) (cal.): C₁₃H₉N₅O₂S₂ [M + H]⁺, m/z: 331.02 (100.0%), 332.02 (18.4%), 333.02 (1.3%), 334.02 (1.6%); (found): 331.0276 (100.0%), 332.0137 (14.1%), 333.0173 (8.9%), 334.01298 (1.2%).
2.2.2.2. N-(Benzo[d]thiazol-2-yl)-2-hydroxy-5-(thiazol-2-yldiazenyl)benzamide (3b). Reddish-brown solid, yield 61.38%, m.p. 70–71 °C, IR cm⁻¹: 3116.83.05 (OH), 3090.68 (Csp²–H aromatic), 1668.25 (C=O), 1603.12 (C=C aromatic); 1578.42 (–N=N–), and 833.98 (aromatic substituted); ¹H NMR (DMSO-d₆, δ ppm): 4.16 (s, H₁₄, OH), 6.96–6.98 (1H, d, Ar–H), 7.20–7.21 (1H, d, Ar–H), 7.42 (1H, s, Ar–H), 7.53–7.55 (1H, d, CH-thiazole), 7.82–7.84 (1H, d, Ar–H), 7.93–7.95 (1H, d, Ar–H), 8.04–8.06 (1H, d, CH-thiazole), 8.13–8.15 (1H, d, Ar–H), 8.47–7.49 (1H, d, Ar–H), 11.30 (1H, s, NH, D₂O exchangeable). ¹³C NMR (DMSO-d₆, δ ppm): 114.93, 117.57, 119.48, 119.69, 123.19, 127.89, 129.77, 143.07, 143.91, 144.53, 149.45, 155.59, 158.04, 165.74, 169.57, 171.40, 176.69. HRMS (ESI) (cal.): C₁₇H₁₁N₅O₂S₂ [M + H]⁺, m/z: 381.04 (100.0%), 382.04 (18.4%), 383.09 (9.0%), 384.02 (1.7%); (found): 381.0443 (100.0%), 382.0350 (18.4%), 383.0258 (8.9%), 384.0166 (1.6%).
2.2.2.3. 2-Hydroxy-5-(thiazol-2-yldiazenyl)-N-(4-(thiazol-2-ylsulfonyl)phenyl)benzamide (3c). Brown solid, yield 70.06%, m.p. 90–91 °C, IR cm⁻¹: 3116.31 (OH), 3090.60 (Csp²–H aromatic), 1668.16 (C=O), 1603.41 (C=C aromatic); 1578.20 (–N=N–) and 833.91 (aromatic substituted); ¹H NMR (DMSO-d₆, δ ppm): 6.58–6.61 (1H, d, Ar–H), 6.83–6.84–7.21 (1 H, d, Ar–H), 6.94 (1H, s, Ar–H), 6.98–7.00 (1H, d, Ar–H), 7.18–7.21 (1H, d, CH-thiazole), 7.53–7.56 (1H, d, CH-thiazole), 7.79–7.82 (1H, d, Ar–H), 7.92–7.95 (1H, d, Ar–H), 10.63 (1H, s, NH, D₂O exchangeable), 11.96 (1H, s, OH, D₂O exchangeable). ¹³C NMR (DMSO-d₆, δ ppm): 114.93, 117.57, 119.48, 119.69, 123.19, 127.89, 129.77, 143.05, 143.91, 144.53, 149.45, 155.59, 158.04, 165.74, 169.57, 171.40, 176.69. HRMS (ESI) (cal.): for C₁₉H₁₃N₅O₄S₃ [M + H]⁺, m/z: 471.01 (100.0%), 472.02 (20.5%), 473.01 (13.6%), 474.01 (2.8%); (found): 471.0228 (100.0%), 472.0130 (20.5%), 473.0086 (13.3%), 474.0128 (2.7%).

2.3. Biological study

2.3.1. Antibacterial activity. The antibacterial activity of synthetic compounds 3 and 3a–c was assessed in vitro using Gram-positive bacteria including Bacillus cereus, Staphylococcus aureus, Staphylococcus epidermidis, and Pseudomonas aeruginosa, as well as Gram-negative bacteria including Shigella sp., Escherichia coli, Stenotrophomonas maltophilia, Aeromonas sobria and Pseudomonas aeruginosa.
2.3.1.1. Antimicrobial activity measurement. For the preparation of a functional solution aimed at evaluating the inhibition zones and minimal inhibitory concentrations, all compounds 3 and 3a–c were dissolved in DMSO. Subsequently, the concentration was diluted to create a solution of 1000 μg mL⁻¹. The both compare the antibacterial efficacy and validate the method, a reference standard of azithromycin at a concentration of 30 mg mL⁻¹ was utilized.
2.3.1.2. Evaluating inhibition zones. The antimicrobial effectiveness of all the synthesized compounds (3 and 3a–c) was examined against different strains of both Gram-positive and Gram-negative bacteria. To evaluate this, compounds 3 and 3a–c were utilized in disk diffusion assays on Mueller–Hinton agar medium to measure the extent of the inhibition zones.^34,35 Fresh bacterial cultures prepared in sterile physiological water were employed to inoculate individual sterilized Petri plates following the autoclaving of Mueller–Hinton agar medium for 30 min. Subsequently, the cultures were placed on agar plates with sterile 6 mm filter paper discs soaked in the chemicals under investigation at concentrations of 1000 μg mL⁻¹. Then the cultures were incubated at 37 °C for 24 h to assess the bacterial growth. For the negative control, disks embedded with DMSO were utilized. The inhibition zones formed on the medium were quantified in millimeters (mm).
2.3.1.3. Minimum inhibitory concentration (MIC). Using sterile 96-well plates, the minimum inhibitory concentration (MIC) was determined in Muller Hinton broth through the serial dilution technique. A range of doses, including 1000, 800, 600, 400, 200, 100, 80, 60, 40, 20, and 10 μg mL⁻¹, was employed to investigate the antibacterial efficacy of the produced compounds (3 and 3a–c). In 96-well microplates, 50 mL of standard microbe suspension containing 106 colony forming units (cfu mL⁻¹) was introduced. Then, the microplates were placed in an incubator set at 37 °C for a period of 18 to 24 h, following the guidelines outlined by the McFarland turbidity standards. At the end of the incubation period, the plates were inspected to determine whether growth was present or absent. The minimum inhibitory concentration (MIC) was identified as the lowest concentration that visibly prevented bacterial growth. Each bacterium was subjected to testing with samples 3 and 3a–c on three separate occasions.

2.3.2. Induction of burn injuries.
2.3.2.1. Animal care. The trial and data gathering were executed at the Biology Department of the University of Raparin. For this experimental model, albino Wistar female rats with an average weight of 190 ± 20 g were employed. Each experimental group was comprised of three rats accommodated in separate cages with dimensions of 40 × 25 × 20 cm. The conventional care and circumstances, including continuous light/dark photoperiod lighting conditions, temperature regulation at 24 °C ± 2 °C, and unrestricted access to food and water, were established. The experimental protocol was executed according to the animal experimentation ethics committee guidelines outlined in DIRECTIVE 2010/63/EU.
2.3.2.2. Burn procedure. The rats were acclimated to the laboratory for 7 days prior to the study. Initially, 18 rats (n = 3) were weighed and anesthetized with a mixture of 30% chloroform (70 + 10) mg per kg body weight intramuscularly. After all the rats were accurately anesthetized, their hair was removed using electrical clippers. Thermal injury was induced by heating (20 mm width and 30 mm length) a solid stainless steel spatula on a Bunsen burner until the temperature reached between 165–190 °C, which was measured with a thermometer simultaneously. Approximately 6 cm² areas on the dorsal proximal region of the animal skin were contacted with the spatula twice side by side for 10 s to produce thickness burn wounds corresponding to the high temperature of the spatulate, where no pressure was applied on the animal skin in the burn induction.^36,37
2.3.2.3. Preparation of the cream. Three creams containing compounds 3a–c at a concentration of 1% w/w were formulated. This was achieved by dissolving 0.05 g of each compound in 2 mL of acetone in a crucible. Subsequently, 5 g of pure paraffin wax was incorporated, followed by sonication and heating to liquefy the wax and eliminate the acetone from the mixture. Then, the mixture was cooled to room temperature while stirring, ensuring the formation of a uniform cream. Next the creams were sterilized in an autoclave via steam heat at 121 °C (15 lb per in²) for approximately 15 min. Following sterilization, the creams were cooled with continuous stirring.³⁸
2.3.2.4. Healing of burn wounds. The burned rats were randomly allocated into five primary groups, as follows: the experimental groups (3a, 3b, and 3c), the positive control group (pure paraffin wax), the negative control group (no treatment), and the standard group (treated with Hamazine 1%) (n = 3). Treatment commenced 24 h after the infection. The affected area in each wounded rat was swabbed with one application of these creams. Over a 24 h period, the advancement of burn wound closure was observed and recorded for each group.

2.3.3. Acute cytotoxicity.
2.3.3.1. Dose preparation. The necessary quantity of the examined compounds (mg kg⁻¹) relative to body weight was dissolved in ethanol. Subsequently, the mixture was gently heated with continuous stirring to facilitate the dissolution of the tested molecules (3a–c), as indicated in Table 5.
2.3.3.2. Dose administration. Following the guidelines set forth by OECD/OCDE 425-27, three animals were weighed, and a restricted test amount of 0.5 mg per kg body weight was administered in a single 24 h dose through the parenteral route. This administration was carried out using a 1 cm³ tuberculin syringe with a 25 g needle for each compound, with pure ethanol injected in the rats serving as the negative and non-injected rats (non-injected ethanol and 3a–c substances) as positive controls (as outlined in Table 5). After dosing, the animals were meticulously monitored individually during the initial 6 h (at 30 min intervals), at various intervals over the first 24 h, and subsequently on a daily basis for a period of 14 days. Furthermore, comprehensive notations were made regarding behavioral modifications and noticeable transformations in the eyes, skin, and fur of each rat, in contrast to the control group, over the entire experimental period. On the fifteenth day, the rats were compassionately anesthetized using chloroform in a container, and then subjected to macroscopic examination to evaluate their external appearances as well as abdominal and thoracic organs (Fig. S27–S35†).

2.4. Computational studies

2.4.1. Geometry optimization. Within the domain of computational chemistry, quantum mechanical methodologies are widely employed to calculate molecular orbital properties and molecular electrostatic features.³⁹ The Gaussian 09 software package was employed to conduct geometry optimization and subsequent refinement of all the synthesized analogs.⁴⁰ For optimization, the density functional theory (DFT) approach with the 3-21G basis set, incorporating Becke's and Lee, Yang, and Parr's (LYP) (B) functional, was utilized.^41,42 During this optimization process, water was chosen as the solvent environment. Following the optimization, the chemical descriptors were evaluated using Parr and Pearson's interpretation of DFT and Koopman's theorem.⁴³ This encompassed all the relevant chemical characteristics, as defined by the provided formula.

Δ_ε = ε_LUMO − ε_HOMO

2.4.2. PASS cataloging. The PASS online tool (available at https://www.pharmaexpert.ru/passonline/, accessed on July 20, 2023) was employed to ascertain the potential biological effects of the synthesized compounds.⁴⁴ Initially, the configurations of molecules 3 and 3a–c were converted into the SMILES format using the SwissADME web-based tool (https://www.swissadme.ch, accessed on July 20, 2023). Afterwards, the SMILES notations were entered in the PASS online server for the computation of the biological profile. The PASS results are displayed in the form of Pa (probability for active compounds) and Pi (probability for inactive compounds). The acceptable range for the Pa and Pi scores is between 0.00 and 1.00. Usually, Pa + Pi does not equal 1 due to the inherent variability in predictions. Biological activities are considered promising for potential drug candidates when Pa is greater than Pi.

2.4.3. Pharmacokinetics and drug-likeness prediction analysis. The pkCSM platform was employed to assess a range of properties for all the synthesized compounds. These properties included water solubility (represented as log mol L⁻¹), permeability in the Caco-2 cell assay (log PAPP), capability for skin penetration, likelihood of human intestinal absorption, extent of plasma protein binding, permeability through the blood–brain barrier, volume of distribution, permeability within the central nervous system (CNS), recognition as a renal OCT2 substrate, total clearance, inhibitory impact on CYP450 1A2, CYP450 3A4, CYP450 2C9, and CYP450 2D6 enzymes, inhibition of the Herg1 channel, potential for human hepatotoxicity, AMES test outcomes, skin sensitivity assessment, and LD₅₀ values.⁴⁵

2.4.4. Computational molecular docking analysis. In this study, the technique of in silico molecular docking was employed to examine the biomolecular interactions of a novel set of azo-amide compounds (3a–c). The objective of this study was to contribute to the enhancement and optimization of therapeutic molecules aimed at effectively inhibiting specific disease-causing proteins. The Molecular Operating Environment software (Moe-Dock 2015.10) was employed to perform molecular docking studies on each of the compounds (3a–c).⁴⁶ By utilizing the build function, the aforementioned compounds were assigned to their respective structures. In addition, the MOE program utilized the default MMFF94x force field to perform energy minimization on these compound configurations, ensuring their readiness for subsequent docking analyses. The three-dimensional structure of the target protein was created using the binding protein information from the Protein Data Bank entry with the identifier 1KZN (accessible at https://www.rcsb.org/structure/1KZN). The MOE-Alpha site finder was employed to pinpoint the active site in 1KZN, and subsequently MOE Dock was utilized for docking the ligands. The MOE software also facilitated the determination of the optimal interaction scores between the ligands and the active site. The most favorable ligand-active site interactions were highlighted by selecting the top five conformers of the ligands that demonstrated the highest and most advantageous scores. To validate the docking method, the ligand was re-docked into the active site, yielding binding interactions similar to that observed with a co-crystallized ligand. The root mean square deviation (RMSD) between the re-docked ligand and the co-crystallized ligand was less than two units, affirming the reliability of the docking procedure.

2.4.5. Deformability, B-factor, and covariance analysis. Subsequently, an additional molecular dynamics simulation (MDS) of the two complexes was conducted using the iMOD server. The iMOD server employed normal mode analysis to assess the stability of the complexes by analyzing their internal coordinates. Utilizing the iMODS software, deformability, B-factor, and covariance calculations were performed to provide insights into the overall stability of the complexes.⁴⁷

2.4.6. Molecular dynamics study. Compounds 3a–c, which demonstrated the most favorable binding affinity with the target protein (1KZN of E. coli), were selected for an in-depth molecular dynamics (MD) simulation investigation utilizing the GROMACS-2021.4 software platform.⁴⁸ Comprehensive molecular dynamics (MD) simulations were conducted on the protein–ligand complexes that emerged from the initial binding affinity prediction analysis. These simulations were carried out in parallel with the original crystal structure of the target proteins bound to the co-crystal inhibitor. The protein–ligand complexes underwent an initial cleaning and preparation process utilizing the macromolecule tool in Chimera version 1.17.2.⁴⁹ The protein topology files were established employing the Charmm27 force field, incorporating the TIP3P water model. For ligand topology generation, the ligand was initially converted to the LIG.mol2 format using Chimera 1.17.2, and hydrogen atoms were added. Subsequently, the required parameters were calculated using the online generation tool located at https://www.swissparam.ch/.⁵⁰ The topology and coordinate information for both the protein and ligand were then amalgamated, resulting in the creation of an independent system. The system was solvated by introducing 26 994 water solvent molecules, and to ensure neutrality, counter ions were included. Specifically, Na⁺ ions were added to balance the charge in the dodecahedron box. The solvated system underwent an energy minimization process using the steepest descent algorithm, with a total of 5000 steps. This procedure was implemented to rectify any erroneous contacts and steric clashes in the protein–ligand complexes, ensuring structural integrity and stability. The system underwent equilibration at a consistent temperature of 300 K using the NVT (number of particles N, volume V, and temperature T) ensemble, with a duration of 100 ps. Subsequently, equilibration using the NPT (number of particles N, pressure P, and temperature T) ensemble was conducted for an additional 100 ps. The ultimate molecular dynamics (MD) production run was executed at 1 bar pressure and 300 K for an extensive duration of 500 000 000 integration steps, which is equivalent to a simulation time of 100 ns. The output data generated were plotted using Xmgrace, and then visualized and refined using Origin 2022.
2.4.6.1. Calculation of binding free energy using the molecular mechanics-Poisson Boltzmann surface area (MM-PBSA) method. The determination of the affinity of a compound to a biological macromolecule or target, as well as the assessment of the thermodynamic stability of the protein–ligand complex heavily depend on the binding free energy (ΔG) calculation through the MM-PBSA approach.⁵¹ This technique provides a quick and accurate prediction of the absolute binding potency of a compound within the active binding site of a target protein, highlighting the significance of the binding free energy as a pivotal factor in both the stability of the compound and its specific effectiveness.⁵² Following the completion of the molecular dynamics simulations, the determination of the binding free energies for each protein–ligand complex was carried out using the binding free energy in GROMACS-2021.4 software platform, incorporating the MM-PBSA methodology. Throughout this analysis, the binding free energies were computed for all the generated conformations, resulting in the calculation of the average binding free energy (ΔG) for each unique protein–ligand complex.

3 Result and discussion

3.1. Chemistry

The initial starting material, an azo compound referred to as 2-hydroxy-5-(thiazol-2-yldiazenyl)benzoic acid (3), was created through the reaction between a diazonium salt (thiazole-2-diazonium chloride) serving as the electrophilic element and an electron-rich aromatic coupling partner, specifically 2-hydroxybenzoic acid (salicylic acid). This synthesis adhered to an electrophilic aromatic substitution mechanism. The presence of the hydroxyl group (in 2-hydroxybenzoic acid) directed the aryl diazonium ion to the para position, unless this position was already occupied. If the para position was inaccessible, the ion would instead bind to the ortho position.⁵³ The azo-thiazole bearing thiazole moiety derivatives (3a–c) were prepared through a reaction involving aromatic amines (a–c) and 2-hydroxy-5-(thiazol-2-yldiazenyl)benzoic acid (3) in toluene as the solvent (as illustrated in Scheme 1). The structure of compounds 3 and (3a–c) was verified by examining their spectral data and elemental composition. The proposed structures were substantiated by congruent outcomes obtained from diverse spectroscopic and analytical techniques, including ¹H NMR, ¹³C NMR, FT-IR, and HRMS. In the FT-IR spectra of azo compound 3, an absorption band at 1580.83 cm⁻¹ was detected, indicating the presence of the azo (N=N) functional group.^73–75 Furthermore, a noticeable peak emerged at 1655.85 cm⁻¹, suggesting the existence of a carboxylic functional group (C=O). In the FT-IR spectrum of compound 3, a broad spectral feature was observable at approximately 3232.05 cm⁻¹, which corresponds to the absorption of the O–H group. The ESI† provides the IR spectra of the prepared azo compounds (3 and (3a–c)), as depicted in Fig. S1–S4.† The spectra of compounds 3a–c reveal distinct bands in the range of 3116.31 to 3232.13 cm⁻¹ and 3006.51 to 3090.69 cm⁻¹, which are assigned to the ν(OH) and ν(Ar–H) stretching vibrations, respectively. The peaks observed between 1655.05 and 1668.25 cm⁻¹ and 1578.20 and 1578.76 cm⁻¹ correspond to the stretching vibrations of the ν(C=O) and ν(N=N) bonds, respectively. In the FT-IR spectra of 3a–c, discernible bands representing the (C–N) and (C–O) frequencies were identified in the range of 1377.49 to 1380.74 cm⁻¹ and 1153.39 to 1155.61 cm⁻¹, respectively. The ESI (Fig. S5–S8†) provides the ¹H NMR spectra for 3 and 3a–c, respectively. These spectra distinctly show signals that are exchangeable with D₂O. Notably, a signal appeared at 12.26 ppm, signifying the phenolic hydroxyl proton, while another notable signal was observed at 12.99 ppm, indicating the presence of the carboxylic proton in compound 3. Moreover, the synthesized compounds 3a–c displayed a singular singlet in the range of 11.30–11.96 ppm, which is attributed to the amide protons (C=ONH). Additionally, compound 3 exhibited a strong singlet at δ12.99 ppm, confirming the –OH proton in the carboxylic group. However, in derivatives 3a–c, this chemical shift disappeared and new peaks resonated at δ10.63–11.52 ppm, corresponding to the protons of the new synthesized amides. In the ¹³C NMR spectrum, compound 3 exhibited a resonant peak at 172.42 ppm, corresponding to the carbonyl carbon of the carboxylic group. In contrast, this peak shifted to 176.69–176.74 ppm in the molecules of derivatives 3a–c, confirming the formation of the synthesized amides (3a–c) and indicating an increase in their shifting due to the deshielding of the carbonyl carbon. The ESI (Fig. S13–S16†) displays the HRMS spectra of the newly synthesized thiazole-bearing amide moieties (3a–c), respectively. In the HR-MS spectra of molecules 3a–c, distinctive molecular ion peaks were observed, attributed to the [M–H]⁺ ions at m/z 332.02, 381.04 and 471.01 for 3a, 3b, and 3c, respectively. These values are consistent with their corresponding molecular weights of 331.019, 381.053, and 472.019, respectively. The resulting molecular ion peaks closely correspond to the calculated molecular weights of the prepared azo-bearing amides (3a–c).

Scheme 1 A schematic of the synthesis of compounds 3a–c.

3.2. UV-vis spectra and electronic properties

The UV-vis spectra of products 3 and 3a–c were recorded in the range of 200–900 nm in five organic solvents with varying polarities (ethanol, DMSO, DMF, benzene, and toluene) under ambient conditions, as shown in Fig. 1. The UV-vis absorbance patterns of 3 and 3a–c in polar aprotic solvents (DMSO and DMF) exhibited three distinct bands in the range of 293 to 477 nm (Fig. 2). The spectral peaks observed in the range of 293–302 nm and 389–433 nm are linked to the π → π* transitions taking place in the aromatic ring structure, indicating a shift towards longer wavelengths (bathochromic shift). The third absorption region, situated between 438 and 477 nm, can be ascribed to the intermolecular charge transfer interactions involving the compound and the solvent⁵⁴ (Table 1). This phenomenon arises from the existence of a modest intermolecular hydrogen bonding and an azo-aromatic chromophore in the structure, leading to n → π* transitions in the system. The presence of a hydroxyl group in molecule 3 causes a slightly more intense absorption spectrum, displaying a hyperchromic effect compared to similar analogs containing amide groups. This distinction is particularly evident in the case of 3c. The underlying reason for this phenomenon is the higher electron-donating capability of the core structure of molecule 3 in contrast to its derivatives (3a–c). This enhanced electron-donating ability is attributed to the presence of electron-rich hydroxyl groups. Consequently, it results in a more pronounced intermolecular charge transfer (ICT) and electron density effect toward the azo side of the molecule (Fig. 3). In the ethanol, benzene, and toluene solvents, the molecular arrangement (as illustrated in Fig. 1) distinctly exhibits two well-defined spectral bands. The initial band, observable in the wavelength range of 291–311 nm, originates from the π → π* transitions involving both the aromatic ring and the azomethine group. Simultaneously, a lower-energy shift (n → π*) becomes noticeable, falling in the spectral range of 384–388 nm. This transition can be attributed to the intricate interplay of electronic effects between the azo-aromatic chromophore and the phenomenon of intramolecular charge transfer. This interplay holds significance across the entirety of the meticulously crafted dye molecules. The attributes of these absorption bands are influenced by both the solvent employed and the substitutions introduced. In DMSO and DMF solvents, the transitions exhibited a shift towards shorter wavelengths (hypsochromic shift), accompanied by lower absorption intensities compared to benzene and toluene. When considering the n → π* transition, it is observed that hydrogen bonding with the ground states of molecules occurs more readily than with their excited states (Fig. 3). Consequently, there is an elevation in the energy of electronic transitions, resulting in a shift towards lower energy levels for the transitions. In the context of π → π* transitions, interactions involving dipole–dipole interactions with solvent molecules induce a more pronounced decrease in the energy of the excited state in comparison to the ground state. This phenomenon leads to the excited states exhibiting a greater level of polarity than the ground state, as elucidated in ref. 55–58. The modifications in the dipole moment occurring during the excited state or variations in the strength of hydrogen bonding in polar solvents are factors that contribute to the observed redshift, a phenomenon that becomes evident in the synthesized compounds.

Fig. 1 The UV-vis spectra of the synthesized molecules recorded in different solvents (a) 3, (b) 3a, (c) 3b and (d) 3c.

Fig. 2 The UV-vis spectra of compounds 3 and 3a–c recorded in (a) DMSO and (b) DMF solvents.

Table 1 The influence of alterations in the solvent conditions on the peak absorption wavelength (λ_max) of compounds 3 and 3a–c

Entry	Solvent	Absorption bands (nm)
		1st (π–π*)	2nd (π–π*, n–π*)	3rd (n–π*)
3	Ethanol	303	384	—
3a		303	401	—
3b		296	388	—
3c		291	394	—
3	DMSO	302	391	477
3a		303	433	459
3b		300	393	438
3c		295	400	468
3	DMF	301	422	468
3a		298	426	467
3b		298	396	470
3c		293	389	473
3	Benzene	310	386	—
3a		307	386	—
3b		309	388	—
3c		301	386	—
3	Toluene	311	388	—
3a		310	384	—
3b		309	386	—
3c		306	387	—

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Fig. 3 A schematic diagram of the solvation effect on the n–π* transitions.

3.3. Biological study

3.3.1. Antibacterial activity. In vitro bacterial resistance testing was conducted against isolated pathogens, including Gram-positive bacteria such as Bacillus cereus, Staphylococcus aureus and Staphylococcus epidermidis, as well as Gram-negative bacteria such as Escherichia coli, Stenotrophomonas maltophilia, Aeromonas sobria, Pseudomonas aeruginosa and Klebsiella pneumoniae. Standard established drugs (azithromycin) were employed for comparison.³² The effectiveness of azo-thiazole 3 and the newly developed thiazole-containing azo-thiazole compounds 3a–c in preventing microbial growth was assessed through qualitative and quantitative means. A see-through ruler was employed to gauge the width of the transparent zone of inhibition around 6 mm-wide paper discs. Furthermore, the minimum inhibitory concentration (MIC), denoting the smallest concentration of substances that can hinder bacterial growth, was ascertained (refer to Fig. S17–S20†), respectively.
3.3.1.1. Determination of inhibition zones. In addition to synthetic molecules 3 and 3a–c, it is important to highlight the significant inhibition of growth in the tested bacterial pathogens. As detailed in Table 2, compounds 3 and 3a–c displayed inhibitory zones, measured in millimeters, ranging from 8 ± 0.11 to 18 ± 0.26 mm against the microbial pathogens. The positive control, azithromycin, displayed values of 7 ± 0.14 and 7 ± 0.32 mm against Pseudomonas aeruginosa and Escherichia coli pathogens, respectively. In contrast, all the synthesized compounds (3 and 3a–c) exhibited enhanced antibacterial efficacy, ranging from 9 ± 0.00 to 10 ± 0.33 mm, against these pathogens. The antimicrobial test results are presented in Table 2 and visually represented in Fig. 4. Among the synthesized compounds, compound 3a demonstrated the most prominent antibacterial efficacy, manifesting a remarkable measurement of 18 ± 0.26 mm against the tested microorganism, Staphylococcus epidermidis. This heightened effectiveness can potentially be attributed to the presence of two thiazole groups in the core structure of compound 3a. Predominantly, compound 3c demonstrates enhanced antibacterial effectiveness against Staphylococcus aureus, Staphylococcus epidermidis, and Klebsiella pneumoniae, displaying inhibition zones measuring 16 ± 0.09, 12 ± 0.43, and 12 ± 0.11 mm, respectively. On the contrary, compound 3 displayed considerably diminished antibacterial effectiveness, leading to smaller zones of inhibition against Bacillus cereus (10 ± 0.03 mm) and Stenotrophomonas maltophilia (8 ± 0.11 mm). Moreover, looking at the bigger picture, the recently created compounds exhibited improved antibacterial potency against both Gram-positive Staphylococcus epidermidis and Gram-negative Escherichia coli, as well as pathogenic bacteria such as Pseudomonas aeruginosa. This antibacterial potential was compared to that of the widely used antibiotic drug azithromycin. Due to the ambiguous mechanism of action of organic compounds against bacteria, numerous researchers have undertaken investigations to explore their antibacterial impacts on microorganisms using diverse binding and interaction mechanisms.⁵⁹ Particularly, the observation of bonds being established between pharmaceutical compounds and bacterial cell walls, encompassing hydrogen bonds, has been linked to the initiation of cellular deterioration.⁶⁰ Furthermore, an identified element that contributes to the augmentation of antimicrobial effectiveness entails the existence of electron-rich moieties on pharmaceutical compounds. In the context of the synthesized compounds 3a–c, these functional groups equip them to function as potent antimicrobial agents.⁶¹

Table 2 The antimicrobial efficacy of the synthesized compounds (3 and 3a–c)

Entry	Zone of inhibition (mm)
	Gram-positive			Gram-negative
	^aB.c	^bS.a	^cS.e	^dK.p	^eE.c	^fS.m	^gA.s	^hP.a
a Bacillus cereus.b Staphylococcus aureus.c Staphylococcus epidermidis.d Klebsiella pneumoniae.e Escherichia coli.f Stenotrophomonas maltophilia.g Aeromonas sobria.h Pseudomonas aeruginosa.
3	10 ± 0.03	12 ± 0.23	14 ± 0.25	11 ± 0.31	9 ± 0.00	8 ± 0.11	10 ± 0.31	10 ± 0.33
3a	10 ± 0.23	13 ± 0.21	18 ± 0.26	13 ± 0.22	9 ± 0.33	9 ± 0.28	10 ± 0.15	9 ± 0.00
3b	10 ± 0.33	13 ± 0.58	14 ± 0.23	14 ± 0.28	9 ± 0.14	10 ± 0.04	10 ± 0.28	9 ± 0.00
3c	10 ± 0.13	16 ± 0.09	12 ± 0.43	12 ± 0.11	9 ± 0.16	9 ± 0.21	10 ± 0.33	9 ± 0.33
(+ve) azithromycin	11 ± 0.31	15 ± 0.09	11 ± 0.32	20 ± 0.26	7 ± 0.32	10 ± 0.02	18 ± 0.41	7 ± 0.14
(−ve) DMSO	0	0	0	0	0	0	0	0

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Fig. 4 The antimicrobial effects of compounds 3 and 3a–c were evaluated using the disc diffusion technique at a concentration of 1000 μg mL⁻¹.

3.3.1.2. Minimum inhibitory concentration (MIC). The antibacterial efficacy of the synthesized compounds, denoted as 3 and 3a–c, was scrutinized through minimum inhibitory concentration (MIC) analysis. Notably, these compounds displayed pronounced antimicrobial activity against Staphylococcus aureus and Aeromonas sobria, manifesting the most potent inhibition at remarkably low concentrations, ranging from 10 to 40 μg mL⁻¹. In contrast, their effectiveness against Bacillus cereus, Klebsiella pneumoniae, and Pseudomonas aeruginosa was comparatively modest, necessitating concentrations within the range of 40 to 200 μg mL⁻¹ to elicit discernible antibacterial effects. The MIC technique, conducted across a concentration gradient ranging from 10 to 1000 μg mL⁻¹ and documented in Table 3 and Fig. S17–S20,† provided insights into these trends, respectively. Particularly, it was noteworthy that compounds 3b and 3c exhibited exceptional antimicrobial potential against Escherichia coli, as evidenced by their notably lowest MIC value of 20 μg mL⁻¹ compared to the other synthesized compounds. These findings collectively underscore the compound-specific variations in the antibacterial efficacy across diverse bacterial strains, thereby delineating the potential of these synthesized compounds as candidates for further investigation as agents with targeted antibacterial activity.

Table 3 The minimum inhibitory concentrations of compounds 3 and 3a–c

Entry	MIC (μg mL^−1)
	Gram-positive			Gram-negative
	^aB.c	^bS.a	^cS.e	^dK.p	^eE.c	^fS.m	^gA.s	^hP.a
a Bacillus cereus.b Staphylococcus aureus.c Staphylococcus epidermidis.d Klebsiella pneumoniae.e Escherichia coli.f Stenotrophomonas maltophilia.g Aeromonas sobria.h Pseudomonas aeruginosa.
3	20	10	10	80	60	40	20	80
3a	100	10	80	200	80	60	40	60
3b	80	20	10	80	20	20	10	40
3c	200	10	40	100	20	40	40	100
Positive control (azithromycin)	80	20	80	60	20	40	20	100

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3.3.2. Burn healing assays. The burn healing assay provides valuable insights into the potential therapeutic effects of different compounds or treatments on burn injuries. In this study, an animal model was employed to assess the potential of these substances for facilitating burn healing in a living system. In the past few decades, Staphylococcus aureus has emerged as a prevalent pathogen isolated from burn patients. The heightened pathogenicity of S. aureus is attributed to its production of diverse exotoxins, which play a role in the persistence of non-healing wounds and the challenges encountered in achieving successful skin grafting.⁶² The active compounds 3a–c, which exhibited potent antibacterial activity against S. aureus in the in vitro studies, were further investigated in the form of a cream (1%). This investigation was conducted in comparison to Hamazine (1%), a standard drug. Rats with burn injuries were subjected to daily treatment with a single dose of approximately 2 mg administered over a 24 h period for the groups undergoing treatment, as outlined in Table 4. The progress of burn healing was monitored for each group, as depicted in Fig. S21–S26.† Specifically, the results pertaining to compound 3a are illustrated in Fig. 5.

Table 4 An elaboration on the milligram (mg) quantities employed for each treated group

Compounds	1% cream total weight (g)	Remaining post-treatment (g)	Cream employed for treatment	Day utilized for recovery	Cream per dose per day	Daily mg dosage of each compound
3a	8	3.8	4.2	26	0.161	1.61
3b	8	3.6	4.4	24	0.183	1.83
3c	8	4.1	3.9	27	0.145	1.45
Hamazine	24	12.4	11.6	28	0.414	4.14

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Fig. 5 Variations in the healing advancement of burns on day 1 (A), 3 (B), 12 (C), 14 (D), 17 (E), and 26 (F).

3.3.3. Acute toxicity. Compounds 3a, 3b, and 3c were subjected to initial acute parenteral toxicity testing on rats at concentrations ranging from 0.5 to 50 mg per kg body weight. The objective of this assessment was to establish the concentration at which 50% lethality occurs. Over the course of the study, no occurrences of mortality were noted, and the rats did not display any noteworthy signs of toxicity. The findings in Tables 5 and 6 indicate that the tested compounds were categorized as potentially non-toxic.⁶³ The rats utilized in this study were humanely euthanized, and their abdominal and thoracic organs were measured for weight. The observed modifications were not attributed to toxicological effects, given that there were no significant variations between the control group and the treated group (Fig. S27–S35†) (Table 5).

Table 5 The preparation of dosage and administration per rat

Conc. mg kg^−1	Ethanol (mL)	Syringe (mL)	No. of doses in 24 h	No. of used rats	Lethality
0.5	5	1	1	3	None
1	5	1	1	3	None
10	5	1	1	3	None
30	5	1	1	3	None
50	5	1	1	3	None

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Table 6 Acute toxicity hazard classifications and their corresponding classification system for approximate LD₅₀/LC₅₀ (mg kg⁻¹) values established based on OECD 1998b standards, with subsequent updates in OECD 2001

Acute toxicity route	Category 1 (very toxic)	Category 2 (toxic)	Category 3 (harmful)	Category 4 (low toxicity)
Parenteral administration
LD50/LC50 (mg kg^−1)	≤0.5	>0.5 and ≤5	>5 and ≤50	>50 and ≤300

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3.4. Computational studies

3.4.1. Frontier molecular orbital analysis. Frontier molecular orbitals (FMOs), recognized as one of the most fundamental components in comprehending chemical reactivity and predicting kinetics, are referred to as molecular orbitals⁶⁴ (Fig. 6). A substantial energy gap between FMOs signifies robust chemical structural stability and limited reactivity. Typically, the transition of electrons from the stable HOMO to the excited LUMO necessitates additional energy. Table 7 presents a comprehensive overview of various parameters, including the HOMO and LUMO energies, HOMO–LUMO gap (Δ), and other essential chemical descriptors. The combined analysis based on Table 7 and Fig. 6 unequivocally verified that compound 3c displays a substantial energy divergence of 1.82 eV, whereas compound 3a exhibits a comparably narrower energy difference of 1.66 eV in comparison to all the other derivatives. Moreover, it is noteworthy that compound 3c exhibited chemical hardness (η) and softness (S) scores of 0.91 eV and 1.09 eV, respectively, with its softness value standing out as the highest among the derivatives. This observation implies that molecules possessing elevated softness values are more predisposed to electronic alterations, rendering them readily participative in reactions involving electron transfer or electronic rearrangements. Soft molecules, by nature, manifest greater receptiveness and reactivity to external influences. Moreover, compound 3c with the highest chemical potential (μ) (−7.12 eV) and electronegativity (χ) (7.12 eV) values and lowest electrophilicity (ω) value exhibited good ionization potential or electron affinity and tendency to attract electrons.

Fig. 6 FMO orbitals and the energy gap between the HOMO and LUMO states in compounds 3a–c.

Table 7 Molecular descriptors of derivatives 3a–c

Entry	HOMO	LUMO	Gap (Δε)	η	S	μ	χ	ω
3a	−7.870	−6.210	1.66	0.83	1.20	−7.04	7.04	29.85
3b	−7.954	−6.168	1.78	0.89	1.12	−7.06	7.06	27.91
3c	−8.036	−6.213	1.82	0.91	1.09	−7.12	7.12	27.84

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3.4.2. Molecular electrostatic potential (MESP) analysis. The concept of MESP enables the identification of binding sites for ligands or proteins and establishes favorable locations for either electrophilic or nucleophilic attack.⁶⁵ The MESP is utilized to analyze the dispersion of positive and negative charges across the surface of a molecule, offering insights into its electronic distribution.⁶⁶ For all the derivatives 3a–c, the MESP was computed via geometry optimization with the B3LYP/3-21G basis set, as illustrated in Fig. 7. The MESP is of great importance due to its ability to visually represent the molecular size, shapes, and regions of positive, negative, and neutral electrostatic potentials through color gradients. This characteristic plays a pivotal role in investigating molecular structures and their complex associations with physicochemical characteristics.⁶⁷ The computation of MESP was utilized to predict possible reactive locations for nucleophilic and electrophilic reactions in the optimized configurations of derivatives 3a–c. In this context, the color code employed was red shade indicates regions of highest negativity, signifying favorable positions for electrophilic attacks; blue hue marks zones of highest positivity, conducive to nucleophilic attacks; and green tint corresponds to neutral potential regions.

Fig. 7 The molecular electrostatic potential surface of compounds 3a–c.

3.4.3. Analysis of predicted antimicrobial activities using the PASS approach. The web server PASS was employed to assess the antimicrobial potential of all the derivatives (3a–c). The PASS outcomes are represented by Pa and Pi values, and their detailed information is presented in Table 8. For derivatives 3a–c, the Pa values followed the order of 0.286 < Pa < 0.289 for anti-inflammatory activity, 0.234 < Pa < 0.328 for antibacterial activity, and 0.099 < Pa < 0.216 for antiviral activity. These findings indicate that these molecules displayed greater efficacy against bacterial pathogens compared to viral pathogens. The introduction of additional thiazole and aromatic groups led to an enhancement in the anti-inflammatory activity (Pa = 0.289) of 3b (compared to 3a, Pa = 0.286). However, the inclusion of the benzene group marginally reduced the antibacterial activity (3a, Pa = 0.328 and 3b, Pa = 0.285). Notably, derivative 3a, featuring a 4-amino-N-(thiazol-2-yl)benzenesulfonamide aromatic group, did not exhibit any anti-inflammatory activity. The antiviral parameters for these derivatives were also predicted.

Table 8 Predicted antimicrobial activity of compounds 3a–c

Entry	Anti-inflammatory		Antibacterial		Antiviral
	Pa	Pi	Pa	Pi	Pa	Pi
3a	0.286	0.174	0.328	0.050	0.216	0.184
3b	0.289	0.171	0.285	0.066	0.099	0.044
3c	—	—	0.234	0.093	0.106	0.038

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3.4.4. Analysis of pharmacokinetic profile and drug-likeness. Upon thorough analysis of the physicochemical and ADMET profiling data, it becomes evident that compound 3b exhibits remarkable characteristics. Notably, it displayed the highest clearance value (0.226) and the most pronounced negative water solubility value (−4.518). Furthermore, compound 3b demonstrates exceptional attributes, including maximum human intestinal absorption potential (99.813) and significantly enhanced skin permeability (measured at −2.802). Among the molecules examined, 3b and 3a exhibited the highest permeation across Caco-2 cells, registering values of 1.01 and 0.763, respectively. Noteworthy plasma protein binding was also observed for these compounds. Compound 3b displayed the maximum blood–brain barrier permeation with a value of −0.951, while compound 3c stood out with a distribution volume (V_d) of 0.025. Impressively, 3b achieved the highest log PS value of −1.925, indicating its substantial central nervous system (CNS) permeability (as detailed in Tables 9 and 10). Evaluating the physicochemical and ADMET data, it becomes evident that most of the molecules adhere to drug-likeness rules. Specifically, compounds 3a and 3b met all the defined criteria within the physicochemical and ADMET analyses.

Table 9 In silico prediction of the absorption of derivatives 3a–c

Entry	Water solubility (log mol L^−1)	Caco-2 permeability (log PAPP in 10^−6 cm s^−1)	Intestinal absorption (% absorbed)	Skin permeability (log Kp)
3a	−4.707	0.763	92.202	−2.93
3b	−4.518	1.01	99.813	−2.802
3c	−3.866	0.358	87.964	−2.743

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Table 10 Predicted in silico distribution and execration of derivatives 3a–c

Entry	Distribution				Execration
	VDss (human) (log L kg^−1)	Fraction unbound (human) (Fu)	BBB permeability (log BB)	CNS permeability (log PS)	Total clearance (log ml^−1 min^−1 kg^−1)	Renal OCT2 substrate
3a	−0.415	0.178	−1.146	−3.005	0.199	NO
3b	−0.172	0.056	−0.951	−1.925	0.226	NO
3c	0.025	0.079	−1.519	−3.169	−0.002	NO

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Table S1† demonstrates that the majority of 3a–c compounds do not exhibit inhibition of CYP2D6 and CYP2D6 enzymes. Instead, they undergo metabolism by CYP1A2, CYP2C19, and CYP2C9, with the exception of CYP3A4 in the case of compound 3a. The toxicity results of derivatives 3a–c are presented in Table S2,† revealing substantial LD₅₀ values (ranging from 2.324 to 2.546). This suggests that these analogs may pose lethality concerns only at exceptionally high doses. The negative AMES test results imply the non-mutagenic nature of the amide compound. Furthermore, the data indicates that it is improbable that the tested derivatives will inhibit the hERG channel or induce skin sensitivity.

3.4.5. Studies involving molecular docking. The synthesized compounds 3a–c were specifically chosen for molecular docking studies against the crystal structure of E. coli 24 kDa domain in complex with clorobiocin (1KZN), guided by their antibacterial properties (Fig. 8). It can be asserted that these compounds are snugly accommodated in the binding cavity of 1KZN, as evident from their orientation and binding energy (Table 11). All the compounds subjected to docking exhibited favorable interactions, with a notable emphasis on hydrogen bonding with the protein target. Upon visual inspection, it became apparent that compounds 3a and 3b, in particular, can potentially attain stability at the active site through hydrogen bonds involving the sulfur (S) atom of the thiazole moiety. Moreover, compounds 3a and 3c, which incorporate five-membered ring functional groups, are anticipated to engage in hydrogen bonding interactions through their pi bonds, thereby enhancing their binding energy. Among the candidates, compound 3a stood out as the most effective molecule for binding to E. coli 1KZN, exhibiting the lowest binding energy at −4.3 kcal mol⁻¹. Two hydrogen bonds are established between the 5-ring of one thiazole group and the sulfur atom of another thiazole group, interacting with the receptor amino acids GLU42 and MET25, respectively. In addition, compound 3c exhibited a distinctive hydrogen bond interaction with GLY117 (3.16 Å) and displayed the highest binding energy (−0.7 kcal mol⁻¹). The docking studies accurately anticipated the occupancy of the 1KZN binding site by these novel compounds (3a–c), thereby suggesting their potential as antibacterial agents.

Fig. 8 Explored binding modes in the active site of 1KZN and hydrogen bonds with antibacterial compounds (3a–c). Shown in 2D (left) and 3D (right).

Table 11 Docking studies of different synthesized substances (3a–c) with demonstrated antibacterial activity yielded noteworthy outcomes

Compound	Binding energy (kcal mol^−1)	Ligand	Receptor	Interaction	Distance (Å)
3a	−4.3	S 31	GLU 42	H-donor	3.37
	−0.8	5-Ring	MET 25	pi-H	4.48
3b	−1.8	S 24	PRO 171	H-donor	3.42
	−1.5	5-Ring	LYS 129	pi-H	3.79
3c	−0.7	O13 19	GLY 117	H-acceptor	3.16

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3.4.6. Deformability, B-factor, and covariance computations. The deformability of a ligand–protein complex (1KZN–3a–c) refers to the ability of the complex to undergo structural changes or deformations while maintaining its binding affinity and specificity.⁶⁸ This deformability can be essential for various biological processes, including ligand recognition, binding, and catalysis.⁶⁹ Understanding the deformability of ligand–protein complexes is crucial in drug discovery, molecular modeling, and the design of therapeutic agents (Fig. 9(a)). The obtained trajectories of compound 3a with protein 1KZN in the complex system reveal a promising and stable binding interaction. The binding of 3a to the target bacterial pathogen protein appears to be consistent and sustained over time, suggesting a strong and potentially biologically relevant interaction. Furthermore, the analysis of the hinge distortions indicates minimal deformation deviations ranging from approximately 0.18 to 0.85 Å. B-Factor investigations of a ligand–protein complex involve studying the temperature or thermal motion of atoms in the complex using B-factors (also known as Debye–Waller factors).⁷⁰ B-Factors provide information about the flexibility and vibrational motion of atoms in a crystal structure or molecular simulation.⁷¹ Analyzing B-factors in a ligand–protein complex can offer insights into various aspects of the behavior and interactions of the complex (Fig. 9(b)). The B-factor investigations in this study revealed that there is minimal atomic fluctuation within a very narrow range, specifically between approximately 0.15 to 0.8 Å. This limited fluctuation range suggests that the atoms in the system exhibit relatively stable and constrained behavior. Additionally, the use of normal mode analysis further confirms these findings by indicating minimal fluctuations. The Eigen score and variance in normal mode analysis represent the extent of atomic displacement along a given normal mode.⁷² A lower Eigen score means that there is less variance or fluctuation along that mode. Specifically, the complex is more stable and rigid along that specific vibrational direction (Fig. 9(c)). The Eigen score of this complex system, which was computed to be 3.493087 × 10⁻³, indicates the degree of variance or flexibility present in the normal mode analysis. This score is interpreted as a measure of the compactness of the interacting complex. Specifically, a lower Eigen score suggests a higher degree of compactness and rigidity in the complex. Covariance matrix analysis of ligand–protein complexes is a valuable approach to understand the correlated motions, interactions, and conformational changes that occur upon ligand binding.⁷³ It can provide mechanistic insights and guide drug design efforts by revealing functionally relevant dynamics within the complex (Fig. 9(d)). The covariance values illustrate the patterns of coupling between pairs of residues, with the colors red, blue, and white denoting the correlated, anti-correlated, and uncorrelated motions, respectively.⁴⁷ Complex 3a shows a strong correlation with a few instances of anticorrelation, primarily observed.

Fig. 9 The globular structure of 1KZN after binding with 3a: (a) deformability, (b) the B-factor, (c) the Eigen score, and (d) the covariance matrix.

3.4.7. Molecular dynamics simulations (MDS). The MDS was conducted to gain insights into the flexibility exhibited during various simulation periods. The root mean square deviations (RMSD) of the C-alpha atoms were employed for analyzing the complexes, aiming to elucidate their structural rigidity (depicted in Fig. 10). The analysis revealed an initial upward trend in flexibility for complexes 3a, 3b, and 3c. However, post 4 ns, the complexes reached a stabilized state and maintained this equilibrium throughout the simulation duration. For all the complexes, the average RMSD remained below 2.17 Å. The minor fluctuations in RMSD indicated the presence of stable conformations in the complexes (as illustrated in Fig. 10(a)). The protein–ligand complex root mean square fluctuation (RMSF) was graphed using a 100 ns molecular dynamics (MD) trajectory to assess the typical fluctuation and flexibility of each amino acid individually (Fig. 10). The RMSF plot illustrates that fluctuations in the amino acid residues occur in the protein while in the ligand-bound state, spanning various time intervals. The outcomes indicate that the interaction between the ligand and the protein results in a closer alignment of the protein chains, leading to a decrease in the distance between them, as demonstrated in Fig. 10(b). The concept of radius of gyration (R_g) is a fundamental metric in the field of structural biology and biophysics, often employed to assess the spatial distribution of mass within a macromolecule or complex. R_g quantifies the compactness or spatial extent of a molecular structure, providing insights into its conformational dynamics and flexibility.⁷⁴ The relationship between R_g and molecular flexibility is well-established. A lower R_g signifies that the mass of the molecule is closely distributed around its center, often implying a more constrained and less flexible structure. Conversely, a higher R_g indicates a broader spatial distribution of mass, and by extension a higher potential for conformational changes and flexibility.⁷⁵ The observation that complex 3c has a lower R_g value compared to complex 3b suggests that 3c is relatively more compact and structurally constrained, as shown in Fig. 10(c). This implies the specific conformation that complex 3c tends to adopt, possibly due to tighter interactions or constraints within the complex. Alternatively, the finding that complex 3a exhibits a higher R_g value compared to complex 4b indicates that 3a displays a greater degree of flexibility or conformational variability. This can be due to the weaker interactions, larger structural fluctuations, or potential for different binding modes. Furthermore, the characterization of molecular interactions extends to the solvent accessible surface area (SASA), a critical parameter in structural analysis within the realm of biophysical investigations.⁷⁶ The SASA metric serves to illuminate alterations in the accessible surface region, where an augmented SASA value corresponds to an expanded surface area, while a diminished SASA value indicates constrained or truncated complexes.⁷⁷ The temporal evolution of the average SASA over the 100 ns trajectory imparts noteworthy insights. Specifically, the SASA analysis revealed that complex 3b exhibits the lowest SASA trend, quantified at 986.4 Ų (Fig. 10(d)). This observation is consistent with the interpretation that complex 3b adopts more stable conformations in comparison to its counterparts, namely, compounds 3a and 3c, which exhibited larger average SASA values of 991.24 Ų and 995.97 Ų, respectively. The intricate hydrogen bond network significantly contributes to establishing the stability of the studied complexes.⁷⁸ In the examined complexes 3a, 3b, and 3c, the hydrogen bond pattern was scrutinized, revealing a range from zero to a maximum of five, six, and seven hydrogen bonds, respectively. Computation of their average values yielded 1.038, 1.32, and 1.93 hydrogen bonds, respectively (Fig. 10(e)). The average hydrogen bond count provides an insightful gauge of the frequency and robustness of these vital interactions. Remarkably, complex 3c exhibited a notably higher average hydrogen bond count (1.93) in comparison to complex 3a (1.038). This disparity implies that compound 3c forms a more intricate network of hydrogen bonds with the 1KZN protein. This heightened propensity for hydrogen bonding suggests a heightened level of interaction strength and extent between compound 3c and the protein.

Fig. 10 MD simulation trajectories over 100 ns: (a) the C-alpha atom RMSD, (b) C-alpha atom RMSF, (c) complex gyration radius, (d) solvent accessible surface area of the docked complex indicating the protein area change, (e) complex hydrogen bonds, and (f) binding energy.

3.4.7.1. Evaluation of MM-PBSA binding free energy. The application of the MM-PBSA method in evaluating the binding free energy provides valuable information about the potential interaction of a ligand with a receptor and the resulting thermodynamic stability of the formed complex. The stability of the protein–ligand complex formed is particularly crucial in establishing the desired effectiveness of the compound. Hence, we carried out computations of binding free energy for all the conformational states obtained from the 100 ns MD simulations. This process led to the determination of the overall binding free energy. Our analysis revealed that the average binding free energy of complex 3b is −36.07 kcal mol⁻¹, indicating a more robust interaction compared to complex 3a, which had a binding free energy of −11.46 kcal mol⁻¹. Notably, the binding free energy of complex 3c was the lowest at −124.78 kcal mol⁻¹ (as depicted in Fig. 10(f)). This discovery is supported by the MIC experimental data for 3c, where a minimal concentration of 20 μg mL⁻¹ was necessary to hinder the growth of E. coli colonies. This result highlights the potent inhibitory capability of complex 3c, which is attributed to its notably low binding free energy.

4 Conclusion

In this study, a novel series of azo-thiazole derivatives (3a–c) was synthesized and extensively characterized using various spectroscopic techniques. These compounds were evaluated for their antibacterial and anti-inflammatory properties, and an in silico analysis was conducted. Compounds 3a and 3c demonstrated significant antibacterial potency against Staphylococcus aureus, outperforming azithromycin. Compound 3b showed remarkable potential in promoting burn wound healing and exhibited strong inhibitory activity against bacterial pathogens. Molecular docking studies confirmed their strong binding affinity to a relevant protein, and their electrochemical characteristics were assessed using DFT calculations. These results highlight that compounds 3a–c are promising candidates as new active agents in antibacterial and anti-inflammatory applications.

Ethical statement

This work was approved by the Ethical Review Board of the Research Center with the access number (7-29-4964 in 2022). We ensured that all procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Data availability

Data will be made available on request.

Author contributions

The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript.

Conflicts of interest

The authors affirm that there are no recognized financial conflicts of interest or personal affiliations that might have seemed to affect the findings reported in this paper.

Acknowledgements

We extend our gratitude to the research center at the University of Raparin for furnishing us with facilities and necessary resources for conducting our research.

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Footnote

† Electronic supplementary information (ESI) available. See DOI: https://doi.org/10.1039/d3ra06469g

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