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. 2025 Sep 23;17(20):2453–2464. doi: 10.1080/17568919.2025.2561543

Design and evaluation of 2-(4-((2-(2-((2,6-dichloro-3-methylphenyl)amino)benzoyl)hydrazineylidene)methyl)phenoxy)acetic acid as a dual anti-inflammatory and anti-diabetic agent

Mohamed K Elgohary a,✉, Mahmoud S Elkotamy a, Mahmoud Abdelrahman Alkabbani b, Ahmed Mohamed El-Khatib c, Aya Mohamed Ahmed Ibrahim d, Ali Mohamed Alshabi e, Abdulrahman A Almehizia f, Ahmed M Naglah f,✉, Hazem A Ghabbour g, Hatem A Abdel-Aziz h,✉
PMCID: PMC12536780  PMID: 40985107

ABSTRACT

Aims

This study aimed to design, synthesize, and evaluate a novel meclofenamic acid derivative (7) for its potential as a dual-target therapeutic agent with anti-inflammatory, antidiabetic, antioxidant, and anticancer activities.

Materials & methods

Compound 7 was synthesized and subjected to in vitro, in vivo, and in silico evaluations. Anti-inflammatory activity was assessed using acute and chronic models, including IL-6 and NF-κB quantification and histopathology. Antidiabetic potential was evaluated through α-glucosidase inhibition, glucose tolerance, and alloxan-induced diabetic models. Antioxidant activity was tested against ascorbic acid, while cytotoxicity was assessed on MCF-7, T24, and A-549 cell lines. Molecular docking, ADME profiling, and pathway analyses were performed to predict drug-likeness and target interactions.

Results

Compound 7 exhibited potent anti-inflammatory activity (IC50 = 0.07 µM), reducing IL-6 and NF-κB by 62.99% and 59.13%, respectively. It demonstrated strong α-glucosidase inhibition (IC50 = 12.78 µM) and improved insulin regulation. Antioxidant activity was comparable to ascorbic acid. Cytotoxicity studies revealed moderate anticancer activity with synergistic enhancement when combined with cisplatin.

Conclusions

Computational and experimental findings suggest that compound 7 exhibits favorable drug-like properties and holds promise as a multi-target therapeutic candidate.

KEYWORDS: Chronic arthritis, antidiabetic, antioxidant, alloxan-induced model, chronic marker, bioinformatics

Graphical abstract

graphic file with name IFMC_A_2561543_UF0001_OC.jpg

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1. Introduction

Meclofenamic acid (N-(2,6-dichloro-m-tolyl)anthranilic acid) is a non-steroidal anti-inflammatory drug (NSAID) belonging to the fenamates class, widely recognized for its potent analgesic and anti-inflammatory effects. It is frequently prescribed for the treatment of osteoarthritis, rheumatoid arthritis, and other musculoskeletal disorders. Its primary mechanism of action involves inhibition of cyclooxygenase (COX) enzymes, resulting in reduced prostaglandin biosynthesis and subsequent alleviation of inflammation and pain. In addition to its COX-inhibitory effects, emerging evidence suggests that meclofenamic acid exerts diverse pharmacological actions by modulating ion channels and other cellular pathways independent of prostaglandin signaling, indicating its potential as a multifunctional therapeutic agent [1–3].

Recent studies have expanded the biological profile of meclofenamic acid, revealing moderate antibacterial activity, particularly against Gram-positive pathogens such as Staphylococcus aureus and Bacillus subtilis. However, it shows limited activity against Gram-negative bacteria. This spectrum of action and its anti-inflammatory properties position clofenamic acid as a strong candidate for drug repurposing in managing multifactorial diseases such as diabetes and cancer [4,5].

Diabetes mellitus (DM), a chronic metabolic disorder characterized by sustained hyperglycemia, poses a significant global health burden. Among its subtypes, type 2 diabetes mellitus (T2DM) is the most prevalent, marked by insulin resistance and progressive β-cell dysfunction. Chronic low-grade inflammation and oxidative stress are now widely acknowledged as key contributors to the pathogenesis and complications of T2DM [6]. Oxidative stress, driven by an imbalance between reactive oxygen species (ROS) production and antioxidant defenses, promotes the oxidation of cellular components, leading to inflammation, insulin resistance, and cellular damage [7]. These mechanisms contribute to hyperglycemia and vascular and metabolic complications such as atherosclerosis, retinopathy, and nephropathy [8].

Given the strong interplay between chronic inflammation, oxidative stress, and insulin dysregulation in diabetes, anti-inflammatory agents, particularly NSAIDs, have attracted interest for their potential in managing diabetic complications. In this context, developing dual-function molecules that combine anti-inflammatory and antidiabetic properties has emerged as a promising therapeutic strategy. Meclofenamic acid has been reported to exhibit mild antitumor activity, with in vitro antiproliferative effects against human cancer cell lines including MCF-7 (breast cancer), T24 (bladder cancer), and A-549 (non-small cell lung carcinoma), showing IC50 values of 63.1 ± 0.4 µM, 70.2 ± 0.3 µM, and 139.1 ± 0.7 µM, respectively [9].

In this study, we investigate the broad-spectrum biological potential of compound 7, a novel derivative of meclofenamic acid (Figure 1), specifically designed as a dual anti-inflammatory and antidiabetic agent. Previously synthesized and shown to possess potent anti-inflammatory activity, Compound 7 is further evaluated here in both acute and chronic inflammation models, including carrageenan-induced paw edema and rheumatoid arthritis. Its therapeutic efficacy is assessed through key inflammatory biomarkers such as Interleukin-6 (IL-6), Nuclear Factor kappa (NF-κB), and COX-2, supported by histopathological analysis. In addition, the compound’s antidiabetic potential is explored via in vitro α-glucosidase inhibition, and in vivo models of glucose intolerance and alloxan-induced diabetes, focusing on insulin regulation and metabolic control. Beyond its primary indications, Compound 7 is also assessed for antimicrobial activity and antiproliferative effects against selected human cancer cell lines, both as a monotherapy and in combination with standard chemotherapeutics, in direct comparison to the parent compound, meclofenamic acid. To further understand its mechanism of action and drug-likeness, in silico Absorption, Distribution, Metabolism, and Excretion (ADME) profiling and molecular docking studies are conducted to evaluate pharmacokinetic behavior and binding interactions with key biological targets.

Figure 1.

Figure 1.

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Structural elongation of meclofenamic acid for the synthesis of targeted compound 7.

2. Chemistry

This study represented the first attempt to synthesize meclofenamic acid hydrazide from its corresponding acid. Ester 2 was obtained through the esterification of the appropriate meclofenamic acid. In the subsequent step, hydrazide 3 was synthesized by refluxing the ethyl ester 2 with hydrazine hydrate for 24 h. The resulting acid hydrazide 3 was then refluxed in absolute EtOH with a few drops of acetic acid and p-substituted carboxylic acid 6 for 6 h, which led to the formation of the titled compound 7 (Scheme 1).

Scheme 1.

Scheme 1.

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Reagents and conditions: (i) absolute MeOH, H2SO4, reflux 48 hrs; (ii) MeOH, NH2NH2.H2O, reflux 24 hrs; (iii) EtOH, acetic acid, reflux 6 hrs; (iv) Ethyl chloroacetate, DMF/K2CO3, stir 12 hrs; (v) MeOH/NaOH, reflux 12 hrs.

3. Experimental

3.1. Synthesis of tilted compound (E)-2-(4-((2-(2-((2,6-dichloro-3-methylphenyl) amino) benzoyl)hydrazineylidene)methyl)phenoxy)acetic acid (7) [10]

A mixture of formyl phenoxy acetic acid derivative 6 and ((phenyl)amino)benzohydrazide derivative 3 were refluxed in 10 mL absolute EtOH with a few drops of acetic acid for 6 h. The final solid product was filtered and recrystallized from ethanol to afford the titled compound 7. Spectral data of compound 7 were mentioned in the supplementary file.

4. Material and methods

4.1. In vivo anti-inflammatory activity [11,12]

The study was conducted based on previously established and well-documented methodologies, building upon validated experimental protocols as prescribed in the supplementary file. The study protocol was reviewed and approved by the Research Ethics Committee of the Faculty of Pharmacy, Egyptian Russian University (Approval No.: ERUFP-PC-24-002, ERUFP-PC-25-001).

4.2. Antidiabetic [13,14]

The study was carried out using the methodology outlined in the supplementary file.

4.3. Effect of test compounds on postprandial glucose levels in diabetic rats [15]

The experimental protocol for evaluating the effect of test compounds on postprandial glucose levels in diabetic rats is outlined in the supplementary file.

4.4. Effect of test compounds on glucose tolerance in normoglycemic mice (OGTT) [16,17]

The methodology for assessing the effect of test compounds on glucose tolerance in normoglycemic mice using OGTT is provided in the supplementary file.

4.5. Antioxidant [18]

The experimental procedures were performed per the protocols outlined in the supplementary file.

4.6. Anticancer & antiproliferative studies [19–22]

Experimental procedures were conducted based on the protocols provided in the supplementary file.

4.7. Antimicrobial [23]

All experiments were performed according to protocols specified in the supplementary data.

4.8. Computational insights

4.8.1. Bioinformatics [24–27]

The experimental procedures were performed per the protocols outlined in the supplementary file.

4.8.2. ADME study & toxicity impact

ADME and toxicity profiles of the synthesized compounds were evaluated using various in silico platforms, including ADMETlab and Protox II (ProTox-3 mode). These computational tools provided predictive insights into the pharmacokinetic behavior and potential toxicological risks associated with the compounds, facilitating the early-stage assessment of their drug-likeness and safety profiles.

4.8.3. Docking protocol [28–31]

Molecular docking analyses of the candidate flavonoids with key antidiabetic enzymes α-amylase and α-glucosidase were performed using MGLTools v1.5.7. Docking simulations were carried out with a defined search grid encompassing the active sites of the target enzymes. For α-glucosidase, the grid box measured 17 × 17 × 17 with coordinates × = 21.1, y = −7.4, z = 24.2. All other parameters were maintained at default values. Discovery Studio v21.1.0.20298 was employed to visualize and analyze ligand – receptor interactions, with specific attention given to hydrogen bonding patterns, which are known to play a crucial role in receptor activation and binding stability.

5. Rational study & biological cascade

In this study, we aim to comprehensively evaluate the biological potential of Compound 7, a derivative of meclofenamic acid, based on the well-established pharmacological profile of its parent scaffold. Meclofenamic acid, a widely used NSAID, is known for its broad bioactivities, including anti-inflammatory, antimicrobial, antidiabetic, and anticancer effects. These properties highlight its potential as a versatile lead compound for developing novel multi-target therapeutics. Our previously published Compound 7, synthesized via structural modification of meclofenamic acid, has already demonstrated promising anti-inflammatory activity in preliminary models. In the current investigation, we expand the biological assessment of Compound 7 to include both acute and chronic inflammation models. In the acute phase, anti-inflammatory efficacy will be evaluated using the carrageenan-induced paw edema model, with additional assessment of COX-2 expression as a key inflammatory marker. For chronic inflammation, a rheumatoid-induced arthritis model will be employed, with therapeutic efficacy measured through clinical scoring, histopathological analysis, and quantification of pro-inflammatory cytokines such as NFKB and IL-1β. Beyond its anti-inflammatory potential, Compound 7 will be investigated for antidiabetic activity. In vitro assays will include α-glucosidase inhibition to elucidate its mechanism of action in glycemic control. In vivo studies will assess its effects on insulin regulation and glucose homeostasis using glucose intolerance and alloxan-induced diabetes models, supported by measurements of blood glucose levels. In addition, the antimicrobial properties of Compound 7 will be screened, and its cytotoxic effects will be tested against selected human cancer cell lines. Its efficacy will also be evaluated with standard chemotherapeutic agents to explore potential synergistic effects. This multi-target evaluation strategy aims to establish Compound 7 as a broad-spectrum therapeutic candidate with applications across inflammatory and metabolic diseases (Figure S1).

6. Biological cascade

6.1. In vitro anti-inflammatory assessment

In our previous study, Compound 7 demonstrated significantly greater inhibitory activity of the COX-2 enzyme with an IC50 equal to 0.07 µM compared to the reference drugs celecoxib and mefenamic acid, indicating its superior anti-inflammatory potential. Furthermore, Compound 7 significantly reduced paw edema in the carrageenan-induced inflammation model, demonstrating greater efficacy than celecoxib in mitigating acute inflammatory responses.

6.2. In vivo anti-inflammatory chronic assay

In light of these promising results, we have extended our investigation to assess the compound’s therapeutic potential in a chronic model of arthritis that appeared in rheumatoid markers.

6.3. Histopathological examination

Histopathological examination of the inflamed joints revealed distinct differences among the experimental groups. The normal control group showed preserved articular surfaces with no pathological changes, confirming the integrity of the joint architecture. In contrast, the arthritic control group displayed significant joint deterioration, including partial substitution of the articular surface with fibrous connective tissue, indicating severe cartilage degradation and inflammation consistent with carrageenan-induced arthritis [32–34]. Treatment with celecoxib mitigated joint damage, showing only mild fibrous tissue infiltration and minor surface irregularities, in line with its well-established anti-inflammatory profile in models of arthritis [35,36]. Notably, rats treated with compound 7 exhibited nearly normal joint histology, comparable to the untreated controls, with no marked pathological changes, suggesting a potent protective effect against carrageenan-induced joint damage.

These findings underscore the therapeutic potential of compound 7 in mitigating joint inflammation and preventing structural deterioration. The histological protection observed was comparable to, and potentially exceeded, achieved with celecoxib. This supports the notion that compound 7 could be a promising candidate for arthritis therapy. Its effect is consistent with prior studies demonstrating the superior anti-inflammatory activity of compound 7 in acute inflammation models, where it outperformed the established reference drug celecoxib (Figure 2).

Figure 2.

Figure 2.

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Representative photomicrographs of hematoxylin and eosin (H&E) stained joint sections from different experimental groups in the carrageenan-induced arthritis model. (A) The normal control group showed intact articular surfaces with no pathological alterations. (B) Arthritic control group displaying partial replacement of the articular surface with fibrous connective tissue (arrow). (C) The celecoxib-treated group exhibited mild fibrous tissue infiltration (black arrow) and slight roughening of the articular surface (blue arrow). (D) The compound 7-treated group showed preserved joint architecture with no notable pathological changes.

As shown in Figure S2, joint exudates from the arthritic control group exhibited statistically significant increases in IL-6 and NF-κB levels, with 426.02% and 329.75%, respectively, compared to the normal control group. Treatment with celecoxib significantly attenuated these increases, reducing IL-6 and NF-κB levels by 49.74% and 44.02%, respectively, relative to the arthritic group. Compound 7 produced even greater reductions, decreasing IL-6 and NF-κB levels by 62.99% and 59.13%, respectively, compared to the arthritic group. Furthermore, the reductions observed with compound 7 were 26.35% and 26.99% greater than those achieved with celecoxib for IL-6 and NF-κB, respectively.

These results align with prior findings demonstrating the anti-inflammatory efficacy of compound 7, particularly its ability to suppress pro-inflammatory mediators such as TNF-α and PGE2 in carrageenan-induced paw edema models. The current data further support the involvement of compound 7 in modulating key signaling pathways associated with chronic inflammation. IL-6 and NF-κB are pivotal mediators in the pathogenesis of chronic inflammatory diseases. IL-6 contributes to joint destruction by promoting synovial hyperplasia, osteoclast activation, and the expression of matrix metalloproteinases. At the same time, NF-κB acts as a master transcription factor regulating the expression of numerous pro-inflammatory genes, including cytokines, chemokines, COX-2, and adhesion molecules. Persistent activation of the IL-6/NF-κB axis has been strongly implicated in the progression of rheumatoid arthritis and other chronic inflammatory disorders [37]. The ability of compound 7 to significantly suppress both IL-6 and NF-κB suggests a broad anti-inflammatory potential that may extend to different models of chronic inflammation.

6.4. In vitro antidiabetic inhibition assay

This study assessed the target compound 7 for its antidiabetic potential through two in vitro enzymatic assays: α-amylase and α-glucosidase inhibition. The inhibitory effects were benchmarked against acarbose, a standard reference drug, which exhibited IC50 values of 11.29 ± 0.07 µM for α-glucosidase and 11.12 ± 0.15 µM for α-amylase inhibition [38]. The findings revealed that Compound 7 showed potent inhibitory activity against α-glucosidase, with an IC50 value of 12.78 ± 0.003 µM, indicating efficacy comparable to acarbose. This suggests that the compound may possess significant postprandial antihyperglycemic activity. However, it showed weak inhibition of α-amylase, with an IC50 value of 54.4 ± 0.003 µM (Table 1 and Figures S2–6).

Table 1.

Anti-diabetic activity of the target compound 7 through different enzymes.

  IC50 (µM)
Compounds α-amylase α-glucosidase
Acarbose 11.12 ± 0.15 11.29 ± 0.07
Comp. 7 54.4 ± 0.003 12.78 ± 0.003
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Data from three independent experiments were expressed as mean ± standard deviation (SD).

6.5. Effects of test compound 7 on postprandial glucose levels in diabetic rats

To investigate the antihyperglycemic potential of compound 7, its effects were evaluated in the alloxan-induced diabetic rat model and standardized against the standard antidiabetic drug vildagliptin. As shown in Table 2 and Figure S7, diabetic rats had significantly increased blood glucose levels throughout the study period. At 120 minutes post-treatment, the diabetic control group maintained significantly elevated glucose levels (336.67 ± 7.92 mg/dL) compared to the normal control (132.17 ± 3.97 mg/dL), representing a 154.73% increase.

Table 2.

Effect of compound 7 on postprandial blood glucose levels in alloxan-induced diabetic rats.

  Glucose (mg/dL)
0 Mins 30 Mins 60 Mins 90 Mins 120 Mins
Normal Control 81.17 ± 6.68 173 ± 3.74 164.33 ± 7.66 150.5 ± 7.64 132.17 ± 3.97
Diabetic Control 273.33 ± 7.5a 403.33 ± 9.58a 365.33 ± 6.06a 349.5 ± 3.02a 336.67 ± 7.92a
Vildagliptin 274.17 ± 7.52a 323.83 ± 7.73ab 307.5 ± 6.8ab 286.67 ± 7.55ab 284.17 ± 6.21ab
Compound 7‎ 279.67 ± 12.01a 300.33 ± 8.12abc 282.33 ± 6.65abc 230.33 ± 2.34abc 228.5 ± 7.42abc
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Data are presented as mean ± SD. Statistical analysis was performed using one-way ANOVA ‎followed by Tukey’s post hoc test. ap < 0.05 vs. normal control group; bp < 0.05 vs. diabetic ‎control group, cp < 0.05 vs. vildagliptin-treated group.

Administration of vildagliptin reduced blood glucose by approximately 15.59% at 120-min relative to diabetic controls. Compound 7 demonstrated a more pronounced antihyperglycemic effect, reducing glucose levels by 32.13% compared to the diabetic group and 19.6% relative to vildagliptin-treated rats. Significant improvements were evident as early as 60-min post-treatment and were sustained throughout the observation period, indicating a potent and time-dependent glucose-lowering effect.

These findings highlight the efficacy of compound 7 in ameliorating postprandial hyperglycemia and support its potential as a therapeutic candidate for diabetes. The observed effects are consistent with its in vitro inhibition of α-amylase and α-glucosidase, two enzymes critically involved in carbohydrate digestion and glucose absorption [39].

6.6. Effects of test compound 7 on glucose tolerance in normoglycemic mice

To further characterize the postprandial antihyperglycemic effect of compound 7, an OGTT was conducted in normoglycemic mice. Table S1 and Figure 3 show that the control group displayed a peak glucose level of 160.5 ± 6.16 mg/dL at 1-h post-feeding. Treatment with acarbose significantly blunted this rise, reducing glucose by 24.2% compared to control values at the 1-h mark.

Figure 3.

Figure 3.

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Postprandial glucose response during OGTT in normoglycemic mice treated with compound 7. Data are presented as mean ± SD. Statistical analysis was performed using one-way ANOVA ‎followed by Tukey’s post hoc test. ap < 0.05 vs. control group; bp < 0.05 vs. acarbose-treated group.

Compound 7 produced an even greater suppression of postprandial glycemia, achieving a 26.0% reduction at the same time relative to control and outperforming acarbose by an additional 2.3%. Importantly, this antihyperglycemic effect was sustained across the 4-h observation period, with glucose levels remaining significantly lower than both control and acarbose groups at each time point.

Food intake during the test did not differ significantly among groups (p > 0.05), confirming that altered feeding behavior did not confound the glucose-lowering effect. This supports a pharmacologically mediated effect, rather than a secondary result of reduced caloric intake. These results provide strong evidence for the antidiabetic efficacy of compound 7. The significant and sustained reduction in blood glucose levels observed in both diabetic rats and normoglycemic mice underscores its ability to modulate postprandial glucose excursions, likely through inhibition of key digestive enzymes. Compound 7 demonstrated superior efficacy compared to vildagliptin and acarbose, standard agents known for their roles in Dipeptidyl Peptidase-4 (DPP-4) inhibition and α-glucosidase inhibition, respectively [40].

6.7. Antioxidant assay

The antiradical activity of compound 7 was evaluated using the 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging assay, with results summarized in Table 3. The IC50value of compound 7 (21.73 ± 0.0031 µM) was compared to that of ascorbic acid (IC50 = 19.64 ± 0.0035 µM), which served as the standard reference. These findings indicate compound 7 exhibits potent antioxidant activity, closely comparable to ascorbic acid (Figure S8).

Table 3.

Anti-oxidant activity of target compound 7.

Compounds DPPH (µM) IC50
Ascorbic acid 19.64 ± 0.0035
Comp. 7 21.73 ± 0.0031
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Data from three independent experiments were expressed as mean ± standard deviation (SD).

6.8. Cytotoxicity against different cancerous cell lines

The MTT assay was employed to evaluate the anticancer activity of compound 7 against MCF-7, A459, and PC3 cells. The IC₅₀ values were determined and compared with cisplatin as a reference drug. The results, expressed as the median growth inhibitory concentration, confirmed the anticancer potential of the compound 7 against the three malignant cell lines.

Compared to cisplatin, the reference drug, which exhibited IC50 values of 22.85 ± 0.07 µM for MCF-7, 18.33 ± 0.60 µM for A549, and 27.73 ± 0.29 µM for PC3 cell lines, the target compound 7 displayed variable cytotoxic activity. It demonstrated IC50 values of 31.87 ± 1.82 µM for MCF-7, 15.99 ± 0.40 µM for A549, and 44.44 ± 1.70 µM for PC3, as presented in Table 4.

Table 4.

Anti-cancer activity against different cell lines for compound 7.

  IC50 (µM)
Compounds MCF-7 A459 PC3
Cisplatin 22.85 ± 0.07 18.33 ± 0.6 27.73 ± 0.29
Comp. 7 31.87 ± 1.82 15.99 ± 0.4 44.44 ± 1.7
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Data from three independent experiments were expressed as mean ± standard deviation (SD).

As illustrated in Table 4, compound 7 demonstrated moderate inhibitory activity against the MCF-7 cell line compared to the standard reference drug cisplatin, while exhibiting the most potent inhibitory effect against the A549 cancer cell line. In contrast, the compound displayed comparatively weak cytotoxic activity toward the PC3 cell line. These findings, supported by detailed results depicted in Supplementary material (Figures S9–S14), highlight the selective antiproliferative potential of compound 7 across different cancer cell types.

6.9. Combination therapy

The literature review indicates that combining NSAIDs with various anticancer agents enhances their cytotoxic effects [41]. Building on this, the present study aims to evaluate the cytotoxic effects of cisplatin and the newly designed compound 7, both as monotherapies and in combination, to explore their potential synergistic or enhanced therapeutic efficacy. As shown in Table S2 and Figure 4, the combination therapy of cisplatin and compound 7 exhibited significantly higher cytotoxic activity against MCF-7, A549, and PC3 cancer cell lines compared to either agent alone. These findings suggest that compound 7 may potentiate the anticancer effect of cisplatin and potentially overcome resistance mechanisms, thereby enhancing its overall therapeutic outcome (IC50 equal 0.69 ± 0.56 µM for MCF-7, 4.88 ± 1.13 µM for A549, and 6.59 ± 0.88 µM for PC3).

Figure 4.

Figure 4.

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Cytotoxic effect of cisplatin and compound 7 in monotherapy and in combination against different cell lines.

6.10. Antiproliferative assay

Table 5 summarizes the cytotoxicity assessment of compound 7 on the WI-38 normal lung fibroblast cell line, conducted to evaluate its safety profile compared to cisplatin as the reference drug with IC50 = 30.5 ± 0.01 µM [42]. Compound 7 exhibited an IC50 value of 74.71 ± 2.88 µM, indicating considerably lower cytotoxicity toward normal cells. These findings suggest compound 7 may possess a more favorable safety profile than cisplatin (Figure S15).

Table 5.

Anti-proliferative activity values of compound 7 toward the WI38 cell line.

Compounds WI38 IC50 (µM)
Cisplatin 30.5 ± 0.01
Comp. 7 74.71 ± 2.88
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Data from three independent experiments were expressed as mean ± standard deviation (SD).

6.11. Antibacterial assay

Recent investigations have revealed that meclofenamic acid possesses notable antibacterial properties, particularly against Gram-positive bacteria such as Staphylococcus aureus and Bacillus subtilis, while showing limited efficacy against Gram-negative strains. In contrast, our potent compound 7 does not exhibit significant antimicrobial activity against a broad spectrum of Gram-positive and Gram-negative bacteria, nor does it effectively target various fungal species (Table S3).

7. Computational insights for our target compound

7.1. Pharmacokinetic properties and drug-likeness

The pharmacokinetic properties of compound 7 were evaluated using ADMETlab 3.0. As depicted in Figure S16, the maximum values for the predicted physicochemical properties of compound 7 were all within the designated range for a compound to be drug-like. According to multiple factors, it was expected that it would not be able to cross the blood-brain barrier (BBB), which will direct our future studies to optimize the physicochemical properties of the target compound further.

7.2. Toxicity impact

The oral toxicity of compound 7 was predicted using the ProTox 3.0 model, which classified it as class 6 in the toxicity classification, with an LD50 of approximately 6500 mg/kg, indicating a relatively safe profile. According to the toxicity radar chart and the active toxicity cluster, compound 7 is predicted to have no probability of exerting a toxic effect on the BBB. In addition, the toxicity radar chart indicates compound 7 is associated with a low potential for clinical toxicity. However, it suggests possible activation of the thyroid hormone receptor alpha (THRα) and cytochrome CYP2C9 as depicted in Figure S17. Therefore, further structural optimization is required to mitigate toxicity and improve clinical outcomes.

7.3. Bioinformatics study

Bioinformatics analyses were employed to elucidate the molecular mechanisms underlying the antidiabetic effects of the synthesized benzofuran derivatives. This included target identification, protein – protein interaction (PPI) network construction, functional enrichment (GO and KEGG), and hub gene analysis to validate their engagement with key antidiabetic pathways.

7.3.1. Identification of overlapping targets and hub genes between active compound 7 and chronic arthritis-related targets

A total of 9332 arthritis-associated targets were retrieved from the GeneCards database. These were intersected with 100 predicted compound targets, resulting in 75 overlapping genes, as illustrated in the Venn diagram in Figure S18A. The shared 75 genes were then submitted to the STRING database to obtain protein – protein interaction (PPI) data (Figure S18B). The resulting network comprised 75 nodes and 106 edges, representing the functional associations among the intersecting targets.

These interaction data were used to construct a functional target – target interaction network, which was visualized in Cytoscape (Figure S19A). To identify key hub genes, the PPI network obtained from the STRING database was further analyzed and visualized through the Cytoscape App software (Figure S19B). The hub genes are selected based on their high scores in the degree algorithm ranking in the CytoHubba plugin Cytoscape. A total of 10 core targets were identified: (HSP90AA1, JAK2, FYN, LYN, ABL1, LCK, KDR, EPHA2, BTK, KIT), suggesting that compound 7 may treat several different autoimmune diseases, such as arthritis, through interaction with multiple molecular targets [43,44] (Figure S19C).

7.3.2. Functional annotation chart and pathway enrichment analysis

Among the significantly enriched KEGG pathways, the Fc epsilon RI signaling, Platelet activation Th17, cell differentiation, osteoclast differentiation, MAPK signaling, PI3K-Akt signaling, and Ras signaling pathways and NF-kappa B signaling pathways were notably identified with a moderate fold enrichment and a high FDR value (as indicated by the deep blue color in the enrichment plot), values and color coding in the enrichment plot that indicating their potential roles in Arthritis. Primary immunodeficiency showed a notably high fold enrichment with low FDR (Figure S20A). The CC analysis of overlapping genes showed that these genes were enriched in the integrin alpha2-beta complex with a low FDR value. Several other cellular components, including the receptor complex, membrane raft, and membrane microdomain, showed notable fold enrichment with a high FDR value (Figure S20B). MF terms were significantly enriched in protein tyrosine kinase activity, protein serine/threonine/tyrosine kinase activity, and protein kinase activity (Figure S20C). Additionally, the BP terms showed significant enrichment in peptidyl-tyrosine autophosphorylation with low FDR, and in protein autophosphorylation, peptidyl-tyrosine phosphorylation, and peptidyl-tyrosine modification with high FDR (Figure S20D).

7.3.3. Identification of overlapping targets and hub genes between active compound 7 and cancer-related targets

A total of 50,000 cancer-associated targets were retrieved from the GeneCards database. These were intersected with 100 predicted compound targets, resulting in 97 overlapping genes, as illustrated in the Venn diagram (Figure S21A). The shared 97 genes were then submitted to the STRING database to obtain protein – protein interaction (PPI) data (Figure S21B). The resulting network comprised 97 nodes and 139 edges, representing the functional associations among the intersecting targets.

These interaction data were used to construct a functional target – target interaction network, which was visualized in Cytoscape (Figure S22A). To identify key hub genes, the PPI network obtained from the STRING database was further analyzed and visualized through the Cytoscape App software (Figure S22B). The hub genes are selected based on their high scores in the degree algorithm ranking in the CytoHubba plugin Cytoscape. A total of 10 core targets were identified: (HSP90AA1, JAK2, ABL1, FYN, LYN, LCK, EPHA2, KDR, YES1, EPHA4), suggesting that compound 7 may play a central role in the diagnosis and prognosis of different cancers through interaction with multiple molecular targets (Figure S22C).

7.3.4. Functional annotation chart and pathway enrichment analysis

Among the significantly enriched KEGG pathways, Central carbon metabolism in cancer, EGFR tyrosine kinase inhibitor resistance, and Ras signaling pathways were notably identified with a high fold enrichment and a high FDR value (as indicated by the deep blue color in the enrichment plot), values and color coding in the enrichment plot that indicate their potential roles in cancer. MAPK signaling, PI3K-Akt signaling, Axon guidance, and Rap1 signaling pathway showed moderate fold enrichment with high FDR (Figure S23A). The CC analysis of overlapping genes showed that these genes were enriched in receptor complex with high fold enrichment and FDR value (Figure S23B). MF terms were significantly enriched in protein tyrosine kinase activity (Figure S23C). The BP terms showed significant enrichment in peptidyl-tyrosine phosphorylation and modification with high FDR (Figure S23D).

7.3.5. Identification of overlapping targets and hub genes between active compound 7 and antioxidant-related targets

A total of 5099 antioxidant-associated targets were retrieved from the GeneCards database. These were intersected with 100 predicted compound targets, resulting in 63 overlapping genes, as illustrated in the Venn diagram (Figure S24A). The shared 63 genes were then submitted to the STRING database to obtain protein – protein interaction (PPI) data (Figure S24B). The resulting network comprised 63 nodes and 89 edges, representing the functional associations among the intersecting targets.

These interaction data were used to construct a functional target – target interaction network, which was visualized in Cytoscape (Figure S25A). To identify key hub genes, the PPI network obtained from the STRING database was further analyzed and visualized through the Cytoscape App software (Figure S25B). The hub genes, which\are selected based on their high scores in the degree algorithm ranking in the CytoHubba plugin Cytoscape. A total of 10 core targets were identified: (HSP90AA1, JAK2, FYN, LYN, LCK, KDR, KIT, FGFR1, HCK, and MTOR), suggesting that compound 7 may play a role as an antioxidant through interaction with multiple molecular targets [45–47] (Figure S25C).

7.3.6. Functional annotation chart and pathway enrichment analysis

Among the significantly enriched KEGG pathways, Central carbon metabolism in cancer, EGFR tyrosine kinase inhibitor resistance, and were notably identified with a high fold enrichment and a moderate FDR value (as indicated by the deep blue color in the enrichment plot), values and color coding in the enrichment plot that indicate their potential roles in antioxidants. Ras signaling pathways, MAPK signaling, PI3K-Akt signaling, and Rap1 signaling pathways also showed moderate fold enrichment with high FDR (Figure S26A). The CC analysis of overlapping genes revealed that these genes were enriched in sorting endosome and receptor complex with a high FDR value (Figure S26B). MF terms were significantly enriched in protein tyrosine kinase activity (Figure S26C). The BP terms showed significant enrichment in protein autophosphorylation, peptidyl-tyrosine phosphorylation, and peptidyl-tyrosine modification with high FDR (Figure S26D).

Compound 7 demonstrated promising therapeutic potential by exhibiting significant anti-arthritic, anticancer, and antioxidant activities, as revealed through comprehensive bioinformatics analyses. The study identified its strong multi-target interactions within key biological pathways, including PI3K-Akt, MAPK, NF-κB, and tyrosine kinase signaling cascades. Additionally, protein – protein interaction (PPI) network mapping and hub gene analyses confirmed its engagement with critical molecular targets, underscoring compound 7‘s potential as a versatile lead candidate for further development in treating diabetes, arthritis, cancer, and oxidative stress-related disorders.

7.4. Molecular docking study

Electrostatic interactions stabilize the protein-ligand complex, including hydrogen bonds (from side chains and backbones), salt bridges, and π-π stacking. Hydrogen bonding stabilizes protein structures and facilitates selective interactions [48].

Computational docking, performed using AutoDock Vina (https://vina.scripps.edu/), estimates two key parameters: the optimal position and orientation of a compound within the binding site relative to the co-crystallized ligand, and the docking score, which quantifies binding energy. Docking studies were conducted to investigate antidiabetic activity and binding modes, with the preferred pose selected from ten possible conformations based on its similarity to the co-crystallized ligand.

The binding results of the potent compound against α-glucosidase (PDB code: 3A4A) revealed diverse interactions. Regarding α-glycosidase, compound 7 exhibited π-anion interactions between the phenyl ring and Arg315, while the phenoxy ring formed a π-cation interaction with Asp352. Additionally, π-alkyl interactions were observed with Tyr158 and Val216. The carboxylic moiety engaged in hydrogen bonding with Arg442 and Asp69 via the carbonyl group, and with His351 through the ether oxygen (Figure 5, Table S4, and Figure S27–S30).

Figure 5.

Figure 5.

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2d and 3d representations of the designed compound 7 against the alpha-glycosidase enzyme.

8. Conclusion

In this study, we aimed to design and synthesize a novel Compound 7 using meclofenamic acid 1 as the starting material. Meclofenamic acid 1 has been previously reported to exhibit diverse biological activities, including anti-inflammatory, antimicrobial (particularly against Gram-positive bacteria such as Staphylococcus aureus and Bacillus subtilis, with limited efficacy against Gram-negative strains), antidiabetic, and anticancer activities. Its anticancer potential has been demonstrated against three human cancer cell lines: MCF-7, T24, and A-549. Compound 7 was developed and evaluated for multiple pharmacological activities based on these findings. It demonstrated promising anti-inflammatory potential, particularly in managing chronic arthritis, supported by histopathological examination. In addition, it showed potent antidiabetic activity, with high inhibitory efficacy against α-glucosidase and relatively weak inhibition of α-amylase. Compound 7 underwent MTT assays for anticancer evaluation and displayed substantial cytotoxic activity. Compared to cisplatin (used as a reference drug), Compound 7 exhibited IC₅₀ values of 22.85 ± 0.07 µM for MCF-7, 18.33 ± 0.60 µM for A-549, and 27.73 ± 0.29 µM for PC3 cell lines. Notably, combined with cisplatin, the compound demonstrated synergistic effects, enhancing overall anticancer potency and exhibiting strong antiproliferative activity. Additionally, Compound 7 showed significant antioxidant activity, comparable to ascorbic acid, but retained no impact as a broad-spectrum antimicrobial agent. Importantly, these biological effects were achieved without signs of toxicity, making Compound 7 a compelling candidate for further development as a multi-target therapeutic agent.

Supplementary Material

Supplemental Material
IFMC_A_2561543_SM2370.docx (9.2MB, docx)

Acknowledgments

The authors are grateful to King Saud University, Riyadh, Saudi Arabia, for funding this work through the Ongoing Research Funding program (ORF- 2025-539).

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Funding Statement

This research was funded by King Saud University, Riyadh, Saudi Arabia, through the Ongoing Research Funding program (ORF-2025-539).

Article Highlight

  • Meclofenamic acid served as the starting scaffold for the synthesis of novel derivative 7.

  • Compound 7 emerged as the most biologically active derivative, demonstrating potent anti-inflammatory effects in both acute and chronic inflammation models.

  • It showed strong COX-2 inhibition with a high IC₅₀ value, indicating selective enzyme targeting.

  • The compound exhibited significant antioxidant activity in relevant assays.

  • Compound 7 significantly reduced blood glucose levels in alloxan-induced diabetic and glucose intolerance models.

  • It displayed moderate anticancer activity against three human cancer cell lines.

  • Synergistic cytotoxic effects were observed when compound 7 was combined with cisplatin.

  • Unlike meclofenamic acid, compound 7 lacked broad-spectrum antimicrobial activity.

Disclosure statement

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties

Writing assistance

No writing assistance was utilized in the production of this manuscript

Reviewer disclosure

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

CRediT authorship contribution statement

Mohamed K. Elgohary: Writing – original draft, Investigation, Methodology, Conceptualization Mahmoud S. Elkotamy: Writing – original draft, Investigation, Mahmoud Abdelrahman Alkabbani: Writing – original draft, Methodology, Ahmed Mohamed El-Khatib: Writing – original draft, Aya Mohamed Ahmed Ibrahim: Methodology, Writing – original draft, Methodology, Ali Mohamed Alshabi: Writing – original draft, Conceptualization, Funding acquisition, Abdulrahman A. Almehizia: Writing – original draft, Conceptualization, Funding acquisition. Ahmed M. Naglah: Resources, Writing – review & editing, Funding acquisition, Hazem A. Ghabbour: Supervision, Methodology, Formal analysis, Hatem A. Abdel-Aziz: Supervision, Project administration, Methodology, Formal analysis.

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/17568919.2025.2561543

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