UMYU Scientifica

A periodical of the Faculty of Natural and Applied Sciences, UMYU, Katsina

ISSN: 2955 – 1145 (print); 2955 – 1153 (online)

ORIGINAL RESEARCH ARTICLE

Phytochemical Profiling, Pharmacokinetics, and Antimicrobial Activity of Azadirachta indica Leaf Extracts: In Silico and In Vitro Evaluations

Khalid Musari Audu^1,2*, Zubairu Umar Darma¹, Kamaluddeen Kabir¹

¹Department of Microbiology, Umaru Musa Yaradua University, PMB 2218, Katsina, Nigeria

²Department of Biology Education, Federal College of Education Jama’are, Bauchi, Nigeria

*Corresponding Author: Khalid Musari Audu khaleedweb@gmal.com

Abstract

Antimicrobial resistance (AMR) is a critical global health threat, necessitated by the rise of multidrug-resistant "superbugs" and a lack of new antibiotic discovery. Plant-derived phytochemicals, particularly from Azadirachta indica (neem), offer a promising reservoir of bioactive molecules with broad-spectrum therapeutic potential. This study aimed to characterize the bioactive profiles of aqueous and methanolic leaf extracts and evaluate their therapeutic potential against viral, bacterial, and fungal targets. Dried A. indica leaves were processed into powder and subjected to three-day maceration in methanol and water. Phytochemicals were identified through qualitative screening and Gas Chromatography-Mass Spectrometry (GC–MS) using a SHIMADZU GCMS-QP2010 PLUS system. Pharmacokinetic profiles and drug-likeness were predicted via SwissADME and ADMETLab 3.0. Molecular docking simulations were performed using AutoDock Vina against nine pathogenic targets, while in vitro efficacy was determined through well/disk diffusion and MIC/MBC/MFC assays. The aqueous extract provided a significantly higher yield (10.78%) than the methanolic extract (10.58%, p = 0.013). GC-MS identified 17 compounds in the methanolic extract (linoleic acid dominant) and 21 in the aqueous extract (oleic acid dominant). Molecular docking revealed that Methyl linolelaidate had the highest affinity for HIV Reverse Transcriptase (-6.9 kcal/mol), while Monopalmitin and Linoleoyl chloride showed strong binding to fungal and bacterial targets (-6.0 kcal/mol). Antimicrobial testing confirmed concentration-dependent activity, with the methanolic extract achieving a 15.6 mm zone of inhibition against S. epidermidis. ADMET analysis identified monopalmitin, resorcinol, and methyl caprate as the most viable drug candidates. A. indica is a potent source of bioactive molecules capable of disrupting microbial membranes and inhibiting key enzymes. While the findings support the therapeutic potential of these compounds, predicted nephrotoxicity for methyl vaccenate and methyl caprate underscores the need for further experimental validation to ensure clinical safety.

Keywords: Azadirachta indica, GC-MS, ADMET, Molecular docking, Antimicrobial resistance, Phytochemicals, Lipinski’s rule of five.

INTRODUCTION

Antimicrobial resistance (AMR) has emerged as a defining global health crisis of the twenty-first century, accounting for an estimated 1.27 million deaths in 2019 alone (World Health Organisation, 2023). The inappropriate and excessive use of antimicrobials across human, veterinary, and agricultural sectors continues to accelerate resistance, with the most severe clinical and economic burdens borne by low- and middle-income countries (Jindal et al., 2015). AMR threatens the stability of modern medicine by complicating routine infections and escalating risks associated with major surgeries and oncology treatments—a challenge compounded by a stagnant antibiotic development pipeline (Jindal et al., 2015; Ahmed et al., 2024). Projections suggest that unabated resistance could impose an additional USD 1 trillion in healthcare costs by 2050 and cause substantial losses in global gross domestic product (World Bank, 2024).

The declining efficacy of conventional therapies has intensified the search for alternative agents, particularly plant-derived phytochemicals, which serve as prolific reservoirs of structurally diverse antimicrobials (Abdallah et al., 2023). These natural products often exert broad-spectrum activity by destabilizing microbial membranes and disrupting electrochemical gradients, mechanisms that significantly lower the risk of resistance development (Nourbakhsh et al., 2022; Li et al., 2024). Among medicinal flora, Azadirachta indica L. (neem) is distinguished by its extensive ethnomedicinal heritage and a rich array of bioactive constituents, including triterpenoids, phenolics, and flavonoids (Orwa et al., 2009; Wylie and Merrell, 2022). Limonoids such as azadirachtin and nimbolide, alongside leaf flavonoids like quercetin and β-sitosterol, have demonstrated potent antimicrobial, anti-inflammatory, and antioxidant activities, reinforcing neem’s relevance in bridging traditional knowledge and modern drug discovery (Saleem et al., 2018; Bello et al., 2021; Nagini et al., 2021).

In modern pharmacological research, the efficiency of phytochemical recovery is known to be strongly influenced by solvent polarity, necessitating systematic comparisons of extraction strategies to optimize bioactive yields (Momodu et al., 2022; Patel et al., 2024). While Gas Chromatography–Mass Spectrometry (GC–MS) remains indispensable for the comprehensive characterization of these complex plant matrices (Abubakar and Lubabatu, 2025), contemporary discovery pipelines now integrate in silico ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) profiling to accelerate early-stage development and reduce clinical attrition (Ameji et al., 2023; Parvathi et al., 2022).

Despite the extensive literature on A. indica, there remains a scarcity of research that adopts a holistic framework linking extraction chemistry with predictive pharmacokinetics and experimental validation. This study addresses this deficiency by systematically investigating the influence of solvent polarity—specifically comparing aqueous and methanolic extracts—on the chemical profile and therapeutic potential of A. indica. By integrating advanced GC–MS characterization with in silico ADMET evaluations and molecular docking, we aim to provide a unified assessment of the herb’s efficacy against a diverse panel of viral, bacterial, and fungal pathogens, thereby streamlining the path from traditional use to evidence-based therapeutic application.

METHOD

2.1 Extraction procedure of Azadirachta indica

A. indica leaves were shade dried and then crushed to fine powder with a clean, dry mortar and pestle. The powdered leaves were filtered through no. 45 sieve and stored in an airtight container until extraction.

Then fifty grams (50g) of the powdered sample was weighed into two places, which were placed in two separate bottles for extraction with two different solvents. Then plant material were macerated using methanol and aqueous (water) respectively. After closing the two bottles, they were allowed to stand for three days, shaking occasionally were done to achieve full extraction (Abubakar and Haque, 2020). After extraction, methanol solvent was removed by rotary evaporator and the aqueous extract was evaporated in water bath. The samples were then placed in a desiccator to completely dry.

2.2 Phytochemical Screening of A. indica

Phytochemical screening was performed on the methanol and aqueous extracts, following the procedures described by Dubale et al. (2023); and Abubakar and Haque (2020). The methods were used to screen the presence of saponins, cardiac glycosides, flavonoid, steroids and alkaloids.

2.3 Gas Chromatography-Mass Spectrometry (GC-MS) Analysis of A. indica

A. indica (both methanolic and aqueous) extracts were dried in the oven at 105°C, ground, and extracted with n-hexane prior to GC-MS analysis. Analysis was performed using a SHIMADZU GCMS-QP2010 PLUS Gas chromatography-mass spectrometry. A Perkin Elmer Elite-5 capillary column (30 m × 0.25 mm) with 0.25 μm film thickness composed of 95% dimethyl polysiloxane was used. Gas chromatography (GC) was performed using a gas chromatograph (Agilent 7890B) connected to a mass spectrometer (Agilent MSD5977A) with an HP-5MS column (30 m × 0.25 mm × 0.25 μm). Helium was used as the carrier gas (flow rate 0.5 ml/min; injection volume 1 μl), and the inlet temperature was set to 250°C. The oven temperature was held at 80°C for 4 min, then increased to 200°C and ramped to 280°C at a rate of 20°C/min, maintaining that temperature for 5 min. Overall time was 25 minutes (Omale et al., 2017; Hamisu and Salisu, 2025; Salisu et al., 2025; Usman et al., 2025).

The transfer line of the mass spectrometer (MS) was maintained at 200°C, while the source temperature was set at 180°C, and the GC-MS analysis was carried out with electron impact ionization at 70 eV. Total ion count (TIC) was used for detecting and quantifying compounds. Spectra of individual components were compared to those from the GC-MS library of known compounds (Taylor, 2015).

2.4 ADMET Prediction

The absorption distribution metabolism excretion and toxicity (ADMET) profiles of the specific phytocompounds of A. indica revealed by GC-MS analysis, were predicted using two reliable webservers: SwissADME and ADMETLab 3.0 (Xiong et al., 2021; Daina et al., 2017). Both webservers were used to evaluate drug-likeness of these compounds and compliance with Lipinski’s rule of five.

SwissADME, accessed via https://www.swissadme.ch, was employed to predict properties such as water solubility, gastrointestinal absorption, blood-brain barrier penetration, and Lipinski's rule of five compliance. ADMETLab 3.0, accessed via https://admetlab3.scbdd.com, was used to assess drug-induced liver injury (DILI) and nephrotoxicity for all phytocompounds.

2.5 Molecular Docking Studies

Molecular docking was performed to predict the binding orientations of A. indica phytochemicals (identified via GC-MS) against key pathogenic targets. Following the methodology of Butt et al. (2020) with modifications, protein structures were retrieved from the RCSB PDB: HIV targets (Reverse Transcriptase, 5VZ6; Integrase, 6WC8; Protease, 4Z4X), S. epidermidis ClpP (8QYF), S. aureus DNA Gyrase (7FVT), E. coli DNA Gyrase (7DPS), P. aeruginosa DNA Gyrase (7PTG), C. albicans Chitin Synthase 2 (7STN), and T. rubrum KDNase (7P1V).

Proteins were prepared by removing non-complexed ions, adding hydrogen atoms, and applying Gasteiger charges. Ligand 3D structures were sourced from PubChem (SDF format) and refined under identical parameters. Docking simulations were executed using AutoDock Vina within UCSF Chimera, centered on a grid box encompassing known active sites. Binding affinities were recorded, and molecular interactions (e.g., hydrogen bonding) were visualized in 2D using BIOVIA Discovery Studio.

2.6 Antimicrobial Susceptibility Testing (AST)

The antimicrobial efficacy of methanolic and aqueous A. indica extracts was evaluated against S. aureus, S. epidermidis, E. coli, P. aeruginosa, C. albicans, and T. rubrum. Isolate identities were confirmed using standard microbiological protocols (Cheesbrough, 2005). Inocula were standardized to a 0.5 McFarland turbidity (approx. 1.5 x 10⁸ CFU/mL) in normal saline, prepared by mixing 0.05 mL of 1% BaCl₂ with 9.95 mL of 1% H₂SO₄ (Wasihun et al., 2023). Extracts were prepared at a 200 mg/mL stock in DMSO and serially diluted to 100, 50, and 25 mg/mL (Ibrahim and Kebede, 2020).

2.6.1 Antibacterial and Antifungal Assays

Antibacterial activity was determined via the well diffusion method on Mueller-Hinton agar. Plates were inoculated with 0.5 mL of standard culture, and wells were charged with varying extract concentrations before incubation at 37°C for 24 hours (Wasihun et al., 2023).

Antifungal activity was assessed using the disk diffusion method. Sterile 6 mm filter paper disks were saturated with extracts and placed onto Sabouraud Dextrose Agar (SDA) plates inoculated with C. albicans and T. rubrum. Results were recorded as zones of inhibition (mm) after incubation at 30°C for 48 hours (Berkow et al., 2020).

2.6.2 Determination of MIC, MBC, and MFC

The Minimum Inhibitory Concentration (MIC) was determined using the broth dilution method, defined as the lowest extract concentration showing no visible growth after 24 hours at 37°C (Ibrahim and Kebede, 2020). To determine the Minimum Bactericidal Concentration (MBC) and Minimum Fungicidal Concentration (MFC), aliquots from tubes showing no growth were sub-cultured onto Nutrient Agar or SDA. The MBC/MFC was recorded as the lowest concentration yielding no colony formation after appropriate incubation.

2.7 Statistical analysis

All statistical analyses were performed with Python (version 3.13.1) and Microsoft Excel (version 2016).

RESULT

3.1 Percentage yields of methanolic and aqueous extracts from the leaves of Azadirachta indica

The yield percentages obtained from both methanolic and aqueous extracts of the plant were compared as shown in Table 1. The percentage yield of aqueous extract was 10.78% (5.39g), and was found to be slightly higher and statistically significant than that of methanol extract with 10.58% (5.29g) (t = -4.30, p = 0.013).

Table 1: Comparison of percentage yields from methanolic and aqueous extracts of A. indica

3.2 Phytochemical profile of methanolic and aqueous extracts

The results of the phytochemical screening indicated that several bioactive chemical constituents are present in both methanolic and aqueous extracts of A. indica. Saponins, cardiac glycosides, flavonoid, steroids and alkaloids were detected in both methanolic extract and aqueous extract (Table 2). This indicates that both solvents resulted in the successful extraction of all tested phytochemicals.

Table 2: Phytochemical profile of methanolic and aqueous extracts from A. indica

Key

+ = Present

- = Absent

3.3 Gas chromatography-mass spectrometry (GC-MS) result

The GC-MS analysis of the methanolic and aqueous extracts of A indica revealed the presence of diverse phytochemical compounds, including fatty acids, alcohols, sugars, and aromatic compounds, indicating the chemical complexity of the plant's bioactive constituents. In the methanolic extract, a total of 17 compounds were identified (Table 3). The most abundant compounds were Linoleic acid (27.38%), and Resorcinol (15.37%). Other notable constituents included Methylglucose (9.50%), 6-Ethoxy-6-methyl-2-cyclohexenone (8.79%), and Sucrose (2.49%), contributing to the extract’s potential bioactivity.

In the aqueous extract, 21 compounds were identified (Table 4). Oleic acid (37.80%) was the most abundant, followed by Z,E-3,13-Octadecadien-1-ol (11.55%). The aqueous extract also contained Glycerin (3.46%) and 3-Methylglucose (7.00%). Additionally, Resorcinol (4.62%) was present in both extracts, though in a higher concentration in the methanolic extract.

Resorcinol, methyl linolelaidate, methyl vaccinate, methyl caprate, linoleoyl chloride and monopalmitin are common compounds identified in both extract. The GC-MS chromatograms of both methanolic and aqueous extracts is shown as Figures 1 and 2 respectively.

Table 3: Phytochemical constituents of methanolic extract identified by GC-MS

Table 4: Phytochemical constituents of aqueous extract identified by GC-MS

Figure 1: GC–MS chromatographic profile of A. indica methanolic extract

Figure 2: GC–MS chromatographic profile of A. indica aqueous extract

3.4 ADMET and drug-likeness predictions result

Table 5 shows the ADMET and drug-likeness predictions of the 6 common phytocompounds obtained in the GC–MS of the plant, indicating varied pharmacokinetic properties. The water solubility varied between moderate and high, while resorcinol was highly soluble (Table 5). The GI absorption was mostly found to be high, with the exception of Linoleoyl chloride, which had a low absorption rate (Table 5). Monopalmitin, resourcinol and methyl caprate were the three phytocompounds that were predicted to penetrate the blood-brain barrier (BBB) (Table 5).

With regards to the Lipinski rule of five, three compounds met all of its criteria; however, Linoleoyl chloride, Methyl linolelaidate, and Methyl vaccenate were exceptions with one violation (high partition coefficient, MLogP > 4.15) (Table 5). The hepatotoxicity risk (DILI) was found to be low for all candidate compounds, with Linoleoyl chloride showing no fit in, while Methyl caprate had the highest DILI value (0.179) (Table 5). Nephrotoxicity scores were diverse: Methyl vaccenate presented the highest nephrotoxicity risk (0.429), on the contrary Linoleoyl chloride scored the lowest (0.054) (Table 5).

Table 5: ADMET and drug-likeness predictions of the phytocompounds from A. indica

Table Legend: ADMET and Drug-likeness Predictions of the Phytocompounds

1. S/N: Serial Number of the compounds in the list.

2. Compound: Name of the phytochemical compound under investigation.

3. Water Solubility: Indicates the ability of the compound to dissolve in water, categorized as poorly, moderately, highly, or very soluble.

4. GI Absorption: Predicts the absorption of the compound through the gastrointestinal (GI) tract, classified as high or low.

5. BBB Penetration: Indicates whether the compound can cross the blood-brain barrier (BBB), with "Yes" meaning it penetrates the BBB and "No" meaning it does not.

6. Lipinski Rule: Evaluates drug-likeness based on Lipinski’s rule of five. A violation (e.g., MLogP > 4.15) suggests reduced likelihood of good oral bioavailability.

7. DILI: Drug-Induced Liver Injury (DILI) risk prediction, with higher values indicating increased likelihood of hepatotoxicity.

8. Nephrotoxicity: Predicts the potential of the compound to cause kidney toxicity, with higher values indicating greater risk.

3.5 Molecular Docking Results

3.5.1 HIV Protein Docking

Molecular docking of six A. indica phytocompounds against HIV enzymes revealed varying binding affinities, measured in kcal/mol (Table 6). Methyl linolelaidate exhibited the highest binding affinity for Reverse Transcriptase with a binding energy of -6.9 kcal/mol, followed by Linoleoyl chloride and Methyl caprate at -6.5 kcal/mol. Monopalmitin showed the weakest affinity for this target at -4.3 kcal/mol.

For Integrase, Methyl linolelaidate and Methyl vaccenate recorded the strongest binding energies of -4.8 kcal/mol, while Monopalmitin displayed the weakest affinity at -3.4 kcal/mol. In the case of Protease, Linoleoyl chloride showed the highest interaction (-4.7 kcal/mol) and Resorcinol recorded the lowest affinity (-4.0 kcal/mol).

3.5.2 Bacterial and Fungal Protein Docking

Against bacterial targets (Table 6), Linoleoyl chloride demonstrated the most consistent and strongest binding, specifically -4.9 kcal/mol for S. aureus gyrase, -5.7 kcal/mol for S. epidermidis ClpP, -5.5 kcal/mol for E. coli gyrase, and -5.4 kcal/mol for P. aeruginosa gyrase. Methyl linolelaidate also showed significant binding to E. coli gyrase at -5.4 kcal/mol.

Regarding fungal targets (Table 6), Linoleoyl chloride and Monopalmitin shared the highest affinity for C. albicans chitin synthase 2 (-6.0 kcal/mol). For T. rubrum KDNase, Monopalmitin and Resorcinol exhibited the strongest binding energy at -4.9 kcal/mol.

3.5.3 Residue-Level Interaction Profiles

Detailed interaction analysis (Figures 3, 4 & 5) identified specific amino acid residues and bond types involved in ligand-protein complexes (Table 7):

Methyl linolelaidate interacted with Reverse Transcriptase via a π–σ bond (TRP226) and multiple Alkyl bonds (LYS220, PHE224, VAL105, LEU231, TYR185, LEU97, PRO92). Its interaction with Integrase involved a π–σ bond (TRP76) and van der Waals forces (GLU40).

Linoleoyl chloride formed Hydrogen bonds with VAL417 in S. epidermidis ClpP and SER121 in E. coli gyrase. It also showed an unfavorable bump with residue HF6301 in E. coli gyrase.

Monopalmitin established Hydrogen bonds with ARG397, GLU395, and TRP439 in C. albicans chitin synthase 2, and with ASP62, ASN60, ARG61, and ARG364 in T. rubrum KDNase.

Table 6: Molecular docking scores (kcal/mol) of selected Azadirachta indica phytocompounds against HIV enzymes and representative bacterial and fungal target proteins.

Table 7: Residue-level interaction profiles of Azadirachta indica phytochemicals with viral, bacterial, and fungal target proteins, showing hydrogen bonding, π–σ, alkyl, van der Waals, and unfavorable contacts.

Figure 3: 2D representation of molecular interactions of Methyl Linolaidate (an A. indica phytochemical) with key HIV proteins

Figure 4: 2D representation of molecular interactions of Linoleoy Chloride (an A. indica phytochemical) with various bacterial proteins

Figure 5: 2D representation of molecular interactions of Monopalmitin (an A. indica phytochemical) with fungal proteins

3.6 Antimicrobial Susceptibility Results

3.6.1 Antibacterial Activity

The maximum zone of inhibition recorded (Figure 6) was 15.6 mm against S. epidermidis using 200 mg/mL of methanolic extract. For the aqueous extract, the highest activity was 14.1 mm against P. aeruginosa at the same concentration. No activity was observed at 25 mg/mL across all organisms.

Three-way ANOVA indicated that extract concentration had a highly significant effect on the zone of inhibition (F(3, 32) = 21.02, p < 0.001). Organism type also showed a significant effect (p = 0.039), but extract type (aqueous vs. methanol) did not (p = 0.475). Post-hoc analysis using Tukey’s HSD confirmed that antibacterial activity differed significantly with decreasing concentration (p = 0.0004), though no significant differences were found between specific bacterial species.

MIC and MBC values showed that methanolic extracts (Figure 7) generally had lower inhibitory concentrations, with P. aeruginosa exhibiting the lowest MBC (50 mg/mL). One-way ANOVA revealed no statistically significant differences in MIC or MBC values between bacterial species (p = 0.314 and p = 0.258, respectively) or extract types.

Figure 6: Antibacterial Activity of Methanolic and Aqueous Extracts of A. indica against Selected Bacteria: SA = Staphylococcus aureus; SE = S. epidermidis; PA = P. aeruginosa; EC = E. coli

Figure 7: Minimum Inhibitory Concentration (MIC) and Minimum Bactericidal Concentration (MBC) of A. indica Against Various Isolates

3.6.2 Antifungal Activity

The methanolic extract achieved a 14 mm zone of inhibition against C. albicans at 200 mg/mL, while the aqueous extract reached 10 mm. T. rubrum was not inhibited by the methanolic extract at any concentration but showed sensitivity to the aqueous extract (11.6 mm at 200 mg/mL) (Figure 8).

Two-way ANOVA for antifungal zones of inhibition showed no significant main effects for organism type (p = 0.170) or extract type (p = 0.818). However, a significant moderate positive correlation (r = 0.6238, p = 0.0098) was found between extract concentration and the zone of inhibition.

For C. albicans, the MIC of the methanolic extract was 50 mg/mL and the MFC was 200 mg/mL. For T. rubrum, the aqueous extract revealed both MIC and MFC at 100 mg/mL (Figure 9). Statistical analysis showed no significant main effects for fungi type or extract type regarding MIC and MFC values.

Figure 8: Antifungal Activity of Methanolic and Aqueous Extracts of A. indica against Selected Fungi

Figure 9: Minimum Inhibitory Concentrartion (MIC) and Minimum Fungicidal Concentrartion (MFC) of A. indica against Selected Fungi

DISCUSSION

The results of this study demonstrate that the aqueous extract of A. indica produced a significantly higher percentage yield (10.78%) than the methanolic extract (p = 0.013). This aligns with previous reports by Sadat et al. (2018), who noted a similar advantage for water as an extraction solvent (14.4% aqueous vs. 9.4% methanolic). While the yield in the current study was slightly lower than that of Sadat et al. (2018), this discrepancy may be attributed to their use of ultrasonic-assisted extraction (UAE) compared to the conventional methods employed here. Furthermore, while Francine et al. (2015) and Hikaambo et al. (2022) reported varying yields, ranging from 8.5% to 22.2% for aqueous extracts—the collective evidence reinforces that water is a highly effective solvent for A. indica. These variations likely reflect differences in plant source, leaf state (fresh vs. dried), and environmental factors.

Phytochemical screening revealed the presence of saponins, cardiac glycosides, flavonoids, steroids, and alkaloids in both extracts. While Ramadass and Subramanian (2018) reported an absence of terpenoids and steroids in ethanol and chloroform extracts, our study successfully identified these compounds, suggesting that solvent polarity and extraction methodology are critical to the resulting profile. These findings are consistent with Khanal (2021), who emphasized that the phytochemical composition of A. indica varies significantly depending on the plant part used.

GC-MS analysis further identified bioactive compounds with established antimicrobial and antiviral relevance, such as linoleoyl chloride, methyl caprate, and resorcinol (An et al., 2021). Although both solvents yielded similar qualitative profiles, the methanolic extract showed higher abundances of phenolic and moderately nonpolar constituents, such as resorcinol (Hrichi et al., 2020). Conversely, methyl vaccenate was more abundant in the aqueous extract. Compounds like methyl caprate and monopalmitin have demonstrated the ability to disrupt microbial lipid membranes, particularly in Gram-positive bacteria, making them potential candidates for antiviral adjuvants (Jahanger et al., 2022).

GC–MS analysis further revealed several phytochemicals with established antimicrobial relevance, with variations in composition and abundance reflecting solvent polarity effects (Sun et al., 2025). Compounds such as linoleoyl chloride, methyl caprate, methyl linolelaidate, methyl vaccenate, monopalmitin, and resorcinol have been previously associated with antimicrobial and antiviral activities (An et al., 2021). Six compounds were common to both extracts, though resorcinol and fatty acid derivatives were more abundant in the methanolic extract, suggesting more efficient extraction of phenolic and moderately nonpolar compounds by methanol (Hrichi et al., 2020). This may partly explain the comparatively enhanced antimicrobial activity observed for the methanolic extract.

Several identified compounds, including methyl caprate and monopalmitin, are known to disrupt microbial lipid membranes and exhibit antibacterial effects, particularly against Gram-positive organisms. Although evidence for their antiviral activity remains largely theoretical or computational, their lipid-based structures suggest potential roles as antiviral agents or adjuvants against enveloped viruses (Olaleye et al., 2018; Jahanger et al., 2022).

ADMET and drug-likeness analyses provided insights into the pharmacokinetic and toxicity profiles of the selected compounds. Water solubility, a key determinant of oral bioavailability, was higher for compounds such as resorcinol and methyl caprate, which correlated with improved predicted absorption profiles (Jiang et al., 2016; Rocha et al., 2023; Huang et al., 2023). Poorly soluble compounds, including linoleoyl chloride, may require formulation strategies to enhance bioavailability (Yu et al., 2020). Predicted gastrointestinal absorption suggested that several compounds could be suitable for oral administration, while limited blood–brain barrier penetration restricted the CNS applicability of some phytochemicals.

Lipinski’s Rule of Five analysis indicated that highly lipophilic compounds, such as linoleoyl chloride and methyl linolelaidate, violated standard drug-likeness thresholds, potentially affecting oral absorption (Elkamili et al., 2023). However, known therapeutic agents that similarly violate these criteria demonstrate that such limitations do not necessarily preclude clinical relevance (Reese et al., 2023).

Toxicity predictions suggested generally low hepatotoxic risk, though moderate nephrotoxicity scores observed for methyl vaccenate and methyl caprate indicate the need for caution. As these findings are based on in silico models, experimental validation remains essential to confirm safety and therapeutic viability.

Therefore, ADMET profiling identified monopalmitin, resorcinol, and methyl caprate as promising candidates for further drug development due to favorable absorption and drug-likeness properties. Nonetheless, potential toxicity concerns and limited BBB penetration underscore the need for further optimization and experimental validation before clinical application.

The molecular docking analysis demonstrates that A. indica–derived phytocompounds possess appreciable binding affinities toward key viral, bacterial, and fungal targets, indicating their potential to inhibit pathogen replication and growth. The ligands showed favorable interactions with HIV reverse transcriptase, integrase, and protease, with Methyl linolelaidate exhibiting the strongest overall affinity. In reverse transcriptase, Methyl linolelaidate formed a π–σ interaction with TRP226 and multiple alkyl contacts with LYS220, PHE224, VAL105, LEU231, TYR185, LEU97, and PRO92. Against integrase, it established a π–σ interaction with TRP76, alkyl interactions with ALA42, ALA73, LEU46, and TYR43, and a van der Waals contact with GLU40. In protease, its binding was dominated by alkyl interactions with ALA127, VAL146, LEU175, ILE131, LEU153, and VAL183. Collectively, these interaction patterns indicate a stable hydrophobic binding mode across HIV targets, supporting the potential inhibitory role of Methyl linolelaidate.

These findings are consistent with earlier reports that neem phytochemicals possess multitarget therapeutic potential with comparatively lower toxicity and added antioxidant and immunomodulatory benefits (Kai et al., 2023; Mohanty et al., 2023). Nonetheless, challenges remain, particularly for HIV, where latent reservoirs (Cossarini et al., 2023) and high mutation rates (Gardner, 2020) complicate durable therapeutic success. Moreover, translation from in silico and in vitro efficacy to in vivo and clinical application is resource-intensive (Bailon et al., 2022; Frattari et al., 2023). Overall, this study establishes moderate-to-high binding of A. indica phytocompounds to viral, bacterial, and fungal targets, with Methyl linoleate, Linoleoyl chloride, and Monopalmitin emerging as promising leads warranting further in vivo and clinical evaluation.

The computational predictions were supported by antimicrobial susceptibility testing. Both methanolic and aqueous extracts of A. indica exhibited concentration-dependent antibacterial activity, with maximal inhibition at 200 mg/mL. The methanolic extract showed the highest overall activity (e.g., 15.6 mm against S. epidermidis), while the aqueous extract was most effective against P. aeruginosa (14.1 mm). These trends align with Hikaambo et al. (2022), who reported enhanced activity at higher concentrations and greater efficacy of aqueous extracts against P. aeruginosa. Variability across studies persists; Gupta et al. (2013) and Susmitha et al. (2013) reported greater potency of ethanolic extracts against E. coli, whereas no significant differences between extract types were observed here, underscoring the influence of extraction solvent and strain-specific susceptibility. Consistent with Herrera-Calderon et al. (2019) and Altayb et al. (2022), the present findings confirm the broad-spectrum and dose-dependent antibacterial activity of neem, attributed to bioactive constituents such as limonoids, triterpenoids, and flavonoids.

Regarding antifungal activity, methanolic extracts were most effective against C. albicans (≥14 mm at 200 mg/mL), while aqueous extracts produced moderate inhibition (10 mm). These observations accord with Mahmoud et al. (2011) and Herrera-Calderon et al. (2019). In contrast, T. rubrum was resistant to methanolic extracts but moderately susceptible to aqueous extracts (maximum 11.6 mm at 200 mg/mL), consistent with the strain-specific responses reported by Noites et al. (2023). The lack of methanolic activity against T. rubrum may reflect differential fungal susceptibility and extraction-dependent bioavailability, as suggested by Hashem et al. (2024).

Collectively, these results validate the antibacterial and antifungal potential of A. indica, particularly against C. albicans, while highlighting variable efficacy against T. rubrum. The observed concentration–response relationship further substantiates neem’s antimicrobial promise and supports its development as a natural alternative to synthetic agents.

CONCLUSION

This study demonstrates that A. indica is a rich source of bioactive compounds with significant antimicrobial potential. Both aqueous and methanolic extracts contained key secondary metabolites, with the aqueous extract yielding slightly more material. GC–MS analysis identified shared compounds, among which monopalmitin, resorcinol, and methyl caprate exhibited favorable drug-likeness properties, although predicted nephrotoxicity in some candidates warrants caution. In silico analyses revealed that methyl linolelaidate, linoleoyl chloride, and monopalmitin possess strong and target-specific affinities toward HIV enzymes, bacterial proteins, and fungal enzymes, respectively. These computational predictions were corroborated by in vitro assays, which confirmed broad-spectrum, concentration-dependent antibacterial and antifungal activity, with methanolic extracts showing superior efficacy against bacterial strains and Candida albicans. Collectively, these findings position A. indica as a promising source of antimicrobial leads and underscore the need for further in vivo and clinical studies to validate safety, pharmacokinetics, and therapeutic efficacy.

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