Antibacterial and molecular docking studies with protein stability studies into dihydropyrimidinones synthesized via silver nanoparticle catalysis: probing structure-activity relationships

Abstract

This study reports the green synthesis of eco-friendly silver nanoparticles (AgNPs) using Aloe vera gel extract and their application as an efficient heterogeneous catalyst for the one-pot, three-component Biginelli synthesis of 3,4-dihydropyrimidin-2(1 H)-ones (DHPMs). The biosynthesized AgNPs were thoroughly characterized using UV-Vis, FTIR, XRD, SEM-EDX, and HR-TEM-SAED techniques, confirming crystalline, spherical particles. Catalyst optimization studies revealed that a low catalyst loading of 20 mg at 80 °C yielded maximum product outputs of up to 96% within an optimized reaction time of 1 h. Structural elucidation of the synthesized DHPM derivatives was completed using FTIR, ¹H NMR, ¹³C NMR, and mass spectrometry (MS). Biological screening demonstrated that the derivatives possessed significant antibacterial activity, with compound 4e exhibiting a prominent zone of inhibition (17 mm) against Salmonella typhimurium (MTCC 98). To decode the underlying mechanism, Prediction of Activity Spectra for Substances (PASS) analysis was paired with molecular docking against the Gluconate 2-dehydrogenase receptor (PDB ID: 5GNA). The PASS analysis reveals that the synthesized compounds display considerable activity as both an antieczematic agent and a Gluconate 2-dehydrogenase (acceptor) inhibitor, with a probability value (Pa) exceeding 0.07. Compound 4e demonstrated excellent binding affinity with a docking score of -8.2 kcal/mol. Furthermore, Normal Mode Analysis (NMA)-based Molecular Dynamics (MD) simulations verified the long-term stability of the protein-ligand complex, showing low main-chain deformability and a rigid eigenvalue of 4.18 × 10^− 4. These quantitative results establish this green catalytic path as a highly efficient strategy for producing bioactive heterocycles.

Graphical Abstract

Supplementary information

The online version contains supplementary material available at https://doi.org/10.1186/s11671-026-04952-5.

Introduction

The synthesis of heterocyclic compounds via efficient protocols remains a staple of medicinal chemistry and materials science [1, 2]. Among these, multicomponent reactions (MCRs), the most well-known of which is the Biginelli reaction, provide a straightforward route to the formation of dihydropyrimidinones (DHPMs) that exhibit a variety of biological activities, including antibacterial and anti-inflammatory effects. The 3,4-dihydropyrimidin-2(1 H)-one (DHPM) core constitutes a highly versatile privileged scaffold in modern medicinal chemistry due to its wide range of pharmacological profiles. As illustrated in Fig. 1, this heterocyclic core is essential to several clinically significant molecules and therapeutic candidates.

Fig. 1.

Structure of Monastrol and Nitractin

Monastrol, a well-known small-molecule inhibitor of the mitotic kinesin Eg5 utilized in cancer research; (R)-SQ 32,926, a potent, orally active calcium channel blocker used for antihypertensive therapy; and (S)-L-771,688, a selective α_1a-adrenoceptor antagonist developed for clinical use. The Biginelli reaction represents a preeminent and thoroughly investigated multicomponent reaction, employed for the direct synthesis of numerous biologically active 3,4-dihydropyrimidin-2(1 H)-ones and their derivatives through the interaction of a β-keto ester or 1,3-dicarbonyl compound, an aldehyde, and urea, utilising AgNPs as a catalytic agent [3–6]. This study reports that the synthesis of AgNPs-catalysed Biginelli reaction provides an efficient and sustainable method for producing these compounds. The reaction conditions were optimised, and the AgNPs exhibited high catalytic activity, yielding dihydropyrimidinone derivatives in high yield. The synthesised compounds were characterised using various spectroscopic techniques. Using AgNPs as catalysts offers a promising alternative to traditional catalysts, providing mild reaction conditions, high yields, and recyclability. This method could serve as a valuable tool for synthesising dihydropyrimidinone derivatives with potential uses in pharmaceuticals and materials science. The derivatives produced were characterised using IR and NMR techniques [7, 8],

NPs synthesised through green chemistry using plant extracts have gained widespread acceptance due to their environmentally friendly approach. Polysaccharides and biologically active compounds from plants contain hydroxyl, hemiacetal, and phytochemical groups that serve as reducing and stabilising agents in the formation of metallic NPs [9–11]. Aloe vera, with its abundant bioactive compounds, is valued for its role in green synthesis [12]. Studies indicate that phytochemicals, such as flavonoids and phenolic compounds, in Aloe vera gel can efficiently reduce Ag⁺ ions to form AgNPs. Developing clean, environmentally friendly chemical processes using less harmful catalysts has become a major focus in synthetic organic chemistry; the phytochemical parameters present in the plant materials also show antimicrobial activities [13, 14]. Although heterogenized catalysts offer numerous advantages, the laborious procedures associated with catalyst recycling via filtration, coupled with the inevitable loss of a portion of the solid catalyst during the separation process, particularly for air-sensitive substances, constitute significant limitations of conventional methodologies [12, 15, 16]. Consequently, there is growing interest in developing more effective catalyst recovery strategies, particularly from a green chemistry perspective [17, 18]. Over the preceding decade, nanomaterials have garnered considerable attention due to their promising applications across fields such as microelectronics, catalysis, and optics. Metallic NPs exhibit distinctive properties that are fundamentally different from those of bulk materials, primarily due to their unique electronic configuration and exceptionally large surface area [19, 20]. Notably, AgNPs are recognised for their exceptional optical characteristics and surface plasmon resonance, which depend on their size [21–23].

Molecular docking software estimates the binding affinity of protein-ligand interactions using platforms such as AutoDock Vina [24]. LigPlot + is software that automatically generates schematic diagrams of detailed protein-ligand interactions from 3-dimensional space to 2-dimensional schematic diagrams [25]. The software provides valuable insights for examining protein-ligand interactions across various molecular visualisation platforms, including PyMOL [26, 27]. DIMPLOT illustrates the interactions present at a chosen protein-protein or domain-domain interface [26, 28]. The antibody-antigen interactions diagram serves as an advancement of DIMPLOT, meticulously formulated for the representation of antibody/antigen interactions, with the antibody loops distinctly colour-coded and annotated [29, 30]. In general, it functions as a graphical front-end application in all scenarios. The interactions visualized comprise both hydrogen bonds and non-bonded contacts. A computational tool, PASS Analysis (Prediction of Activity Spectra for Substances), is specifically designed to assess the biological potential of molecules. A compilation of anticipated activities for diverse compounds with distinct characteristics is accessible through the PASS online platform. The PASS web server is used to investigate the potential biological activities of compounds synthesised. By utilising this resource, we have identified and analyzed the potential biological properties of compounds based on their chemical formulas [31–34]. It generates two-dimensional molecular fragments, referred to as multilevel neighbours of an atom (MNA), suggesting that the molecular architecture can be used to determine biological activities. It offers a predictive metric for biological properties predicated on the Ratio of the probability of being active (Pa) to the probability of being inactive (Pi). Molecules that display a high pKa value are associated with enhanced biological properties [29, 35, 36].

In this study, we synthesised DHPM derivatives using a green method in the presence of AgNPs prepared from Aloe vera gel, which served as a catalyst. The characterization of AgNPs was performed using various analytical techniques, including XRD, FTIR, UV-Vis, SEM-EDX, and HR-TEM-SAED. We also assessed the effectiveness of this new catalytic system and compared it with traditional methods. The resulting DHPMs were thoroughly characterised using various spectroscopic techniques, including FTIR, ¹H NMR, ¹³C NMR, and mass spectrometry. Additionally, the biological activity of the end products was assessed through their antimicrobial activity against a panel of pathogens [37, 38]. Computer modelling was also utilized to gain a better understanding of the catalytic mechanism and biological interactions, aiding in comprehension of the reaction pathway and the potential biological targets of the compounds produced. Therefore, this comprehensive study presents an environmentally friendly and effective approach to DHPMs, encompassing synthesis, characterization, and biological applications.

Experimental techniques

The reagents and chemicals used for synthesis are of research-grade quality and sourced from reputable suppliers, including SD Fine-Chem and Merck. Fresh, healthy, and disease-free leaves of Aloe vera (L.) Burm. f. (Aloe barbadensis Miller) were collected from the botanical garden of K.S.K.W. Arts, Science and Commerce College, CIDCO, Nashik, Maharashtra, India (coordinates: 19.9577 N, 73.7423 E). Taxonomic identification and authentication of the plant specimen were formally performed by Dr. D. M. Kokate, Head of the Department of Botany at K.S.K.W. CIDCO College, Uttamnagar, Nashik. A voucher specimen (Voucher No: KSKW/01/RP/1-2026) was deposited in the institutional herbarium for future reference. The resulting products were characterised using FT-IR, ¹H NMR, ¹³C NMR, and mass spectra. The FTIR was obtained using a Shimadzu FT-IR spectrometer. The ¹H and ¹³C NMR spectra were acquired on a Bruker (500 MHz) instrument using DMSO-d6 as the solvent.

Synthesis of AgNPs

These leaves were rinsed twice with distilled water, then washed with deionised water to remove any adhering contaminants and heavy-metal residues. In the current study, AgNO₃ and aloe vera extract were used as the main reagents. The Aloe vera extract was prepared by applying 20 g of washed, finely minced Aloe vera leaves. The minced Aloe vera leaves were boiled in 100 mL of deionized water for 20 min, then cooled. The cooled leaf infusion was then filtered and stored in a refrigerator maintained at 4 °C. The resultant extract/filtrate was designated as the aloe vera extract solution. The synthesis of AgNPs used Aloe vera, which required boiling 50 g of Aloe vera in 100 mL of water. Following this procedure, the extract was allowed to cool and was subsequently filtered. To 10 mL of this filtrate, 90 mL of 0.1 M AgNO₃ was added. The resultant mixture was heated on a magnetic stirrer and a hot plate at 70 °C. Initially, the solution appeared colourless; after 20 min, it turned golden-brown and remained stable until the reaction was complete. This observable colorimetric change supports the reduction of Ag⁺ to Ag⁰, a phenomenon further validated by UV-Vis spectrophotometry over 350–700 nm, indicating the successful synthesis of AgNPs. Clarified that after the reaction between the Aloe vera extract and AgNO₃ solution, the crude colloidal mixture was centrifuged for 20 min to separate the synthesized AgNPs from unreacted metal ions and matrix proteins. The final purified silver nanoparticle pellet was dried in a vacuum oven at 60 °C for 24 h to obtain a fine powder. This biogenic AgNP powder was stored in a sterile, amber-coloured glass vial wrapped in aluminium foil under dark conditions to prevent photo-induced oxidation or agglomeration prior to catalytic use.

Synthesis of dihydropyrimidinone

In a round-bottom flask, 20 mmol of aldehydes, 40 mmol of urea, and 40 mmol of ethyl acetoacetate were added, and 20 mg of AgNPs powder was then added, followed by 1–2 drops of concentrated H₂SO₄. The mixture was refluxed for one hour at 80 °C. The mixture is filtered after being rinsed with deionised water. The resultant substance is then recrystallised from ethanol. AgNPs were recovered. DHPMs derivatives were prepared by using different substituted benzaldehydes. The reaction was monitored by TLC using n-hexane: ethyl acetate (7:3).

Reaction scheme

Scheme: AgNPs Catalyzed Multicomponent Synthesis of Dihydropyrimidinone (DHPMs). (Reaction Scheme for the AgNPs-Catalysed Biginelli Multicomponent Reaction (MCR). The DHPM derivatives 4(a-g) are synthesized through the one-pot condensation reaction involving aldehyde 1 (benzaldehyde derivative, R=H or substituted group), ethyl acetoacetate 2, and urea 3. The reaction proceeds in refluxing ethanol, using AgNPs as a highly efficient, reusable catalyst. This method provides a facile and green approach for the preparation of the target Dihydropyrimidinone.)

Plausible mechanism

Synthesis of 3, 4-dihydropyrimidin-2(1 H)-ones using Ag nanoparticles (4a-4 g) (Fig. 1). Structure, IUPAC name, and yield (%) of dihydropyrimidinone derivatives are shown in Table 1.

Table 1.

Structure, IUPAC name, and % yield of dihydropyrimidinone derivatives (4a-4f)

Compound	Structure	IUPAC name	% yield
4a		ethyl 4-methyl-6-oxo-2-phenyl-3,4-dihydropyrimidin-2(1 H)-ones	90
4b		ethyl 4-methyl-2-(3-nitrophenyl)-6-oxo-3,4-dihydropyrimidin-2(1 H)-ones	92
4c		ethyl 2-(4-bromophenyl)-4-methyl-6-oxo-3,4-dihydropyrimidin-2(1 H)-ones	94
4d		ethyl 2-(4-chlorophenyl)-4-methyl-6-oxo-3,4-dihydropyrimidin-2(1 H)-ones	92
4e		ethyl 2-(4-methoxyphenyl)-4-methyl-6-oxo-3,4-dihydropyrimidin-2(1 H)-ones	96
4f		ethyl 4-methyl-6-oxo-2-(p-tolyl)- 3,4-dihydropyrimidin-2(1 H)-ones	90
4 g		ethyl 4-(2-chlorophenyl)- 6-methyl-2-oxo-3,4-dihydropyrimidin-2(1 H)-ones	88

Table 2 presents the optimized catalyst amounts used for synthesis, along with the corresponding reaction times, temperatures, and product yields. It can be concluded that 20 mg of catalyst is required for this reaction to obtain maximum yield at 80C. Under these optimized conditions, reactions were performed using various benzaldehydes, ethyl acetoacetate, and urea to obtain the corresponding derivatives of 3,4-dihydropyrimidin-2(1 H)-ones.

Table 2.

Optimization of reaction parameters

Entry	Catalyst Amount (mg)	Time (h)	Temp (C)	Yield (%)
1	No catalyst	10	RT	No reaction
2	No Catalyst	10	50	80
3	No Catalyst	10	80	85
4	5	3	80	85
5	10	2	80	90
6	20	1	80	95

Results and discussion

Characterization of AgNPs

XRD and FTIR studies of Ag NPs

The XRD spectra provide the crystalline structure and phase purity of AgNPs. The XRD pattern is described in Fig. 2.

Fig. 2.

X-ray diffraction pattern of AgNPs

The XRD pattern exhibits well-defined diffraction peaks, confirming the crystalline phase of the prepared NPs. The high-intensity peaks at approximately 2θ = 27.80, 32.20, 38.10, 44.30, 54.90, 57.50, 64.40, and 77.40 are attributed to the Ag crystallographic planes. Particularly, a strong diffraction peak with 2θ ≈ 32.2⁰ can be indexed to the (122) plane of FCC Ag. Other peaks at 2θ ≈ 44.3⁰ and 64.4⁰ are characteristic of the (200) as well as (220) planes, respectively. The 2θ ≈ 77.4⁰ ° peak can be assigned to the (311) plane. These reflections correspond to a typical diffraction pattern of metallic Ag (JCPDS file no. 04-0783) [39], which confirms the formation of crystalline AgNPs. The existence of other peaks, including (210), (241), (231), and (013), suggests the presence of crystallographic planes associated with either silver oxide or crystalline phases, possibly related to Aloe vera extract. As silver oxide can form on the surface due to air contact and during the green synthesis process, it is reasonable to assume the presence of minor silver oxide phases. For example, the peak around 2θ = 27.8⁰ (labelled as (100) or 29.58 in Fig. 2, although it should be (311), could be related to silver oxide or an organic crystalline phase from the plant extract. The asterisked peak at 2θ ≈ 44.3° (200) indicates that the FCC structure is well maintained. In contrast, the peak at 2θ ≈ 46.5° (231) is generally weak for pure FCC Ag, suggesting that another phase may be present, such as an impurity or oxide. The well-defined, intense diffraction peaks, particularly the (111) peak, indicate that the AgNPs are highly crystalline. The average crystallite size of the Ag NPs is 22 nm, as determined from the most intense peak (122) using the Debye-Scherrer Eqs. [40, 41].

FTIR spectroscopy was used to identify the functional groups/vibrational modes in AgNPs. The spectrum shown in Fig. 3 exhibits several absorption peaks, correlating to the interfacial layer within AgNPs. The band observed at 3300–3400 cm^-1 primarily results from the stretching vibrations of O-H groups in polyphenols, carbohydrates, and adsorbed H₂O, confirming the presence of hydrogen-bonded OH- groups in the plant extracts.

Fig. 3.

FTIR spectrum of Aloe vera-mediated AgNPs

Other prominent peaks were observed, including a narrow peak at ~2350 cm^-1, assigned to the usual atmospheric CO₂ contamination, which may also be associated with different functional groups [42]. A progressive and strong broad absorption band centered at ~1000 cm^-1 is related to stretching vibrations of C-O from -OH, -COOH, -O-, and in particular, polysaccharides that are abundant in Aloe vera extract, indicating the role of these substances as stabilizing agents. Moreover, another peak situated around 1505 cm^-1 indicates other C-O stretching vibrations [43]. The bands at about 839 cm^-1 and 436 cm^-1 are also observed. Below 1000 cm ¹ lies the region of C-H out-of-plane bending and C-C stretching; however, bands appearing in the 800–900 cm⁻¹ range are frequently associated with polysaccharides [44]. The peak at 436 cm⁻¹ could be attributed to the vibrations of the Ag-O bond or other inorganic stretching vibrations, which may imply interaction between Ag and O-containing functional groups after treatment of the extract or surface oxides [45, 46]. The overlapping presence of these bands, particularly those assigned to O-H and C-O stretching, can be interpreted as arising from different groups of biomolecules from the Aloe vera extract, such as polysaccharides, phenolic compounds, or proteins, on the surface of the AgNPs. Such phytochemicals have a dual function as reducing agents for Ag + and as necessary capping and stabilizing agents, thereby preventing NP agglomeration [47–49].

UV-Vis analysis of AgNPs

The properties of NPs, particularly their optical properties, are determined by their SPR. The absorption spectrum of the AgNPs is shown in Fig. 4.

Fig. 4.

UV-Vis absorption spectrum of Aloe vera-mediated AgNPs

The 350 nm peak can be attributed to the collective oscillation of free electrons in the AgNPs’ conduction band, known as SPR. In spherical AgNPs, the SPR band typically ranges from 400 to 450 nm. The observed blue shift of the SPR peak to ~ 350 nm indicates the presence of small AgNPs. Normally, smaller particles exhibit SPR bands at shorter wavelengths than larger ones, due to quantum confinement effects and differences in the oscillating electron cloud [50, 51]. This finding aligns with green preparation methods, which often yield smaller NPs depending on the choice of reduction and capping agents. The broad SPR peak, spanning a significant wavelength interval (~ 300 nm to over 700 nm, even as absorption intensity decreases), may indicate a considerably larger size range for the fabricated AgNPs or the influence of agglomeration. The high absorbance in the region below 350 nm could be attributed to contributions from the organic capping agents derived from the Aloe vera extract, which exhibit strong absorbance in the UV region, or to scattering effects arising from agglomerated particles [42, 43, 52].

SEM-EDX analysis of AgNPs

SEM images (Fig. 5a-b) showed that the small nanoscale particles aggregated into irregular clusters, indicating the formation of these NPs.

Fig. 5.

a-b SEM images, (c) EDX spectra, and (d-f) Mapping images of AgNPs

The elemental analysis was confirmed by EDX, as shown in the spectrum (Fig. 5c), which exhibits a major peak for Ag at ~ 3 keV, indicating the presence of Ag. Significantly, it also showed high peaks for oxygen (O) and carbon (C). Quantitative analysis found that the main component was composed of Ag at 85.22 wt% (43.40 at%), and oxygen and carbon existed in a 9.65 wt% (33.14 at%) and 5.13 wt% (23.47 at%), respectively. The presence of O and C can be attributed to several factors in the biosynthetic approach. Residual organic matter from the Aloe vera extract, which includes various phytochemicals, essentially acts as a reducing and stabilising agent during the synthesis process. These organic species remain adsorbed on the surface of the AgNPs, contributing significantly to the observed C and O signals, and play a critical role in preventing particle aggregation. Minor impurities can also contribute, but the presence of high oxygen and carbon levels suggests that remaining organic matter or surface oxidation plays a primary role. The elemental mapping images (Fig. 5d, e, and f) support the spatial distribution of these elements. The composite map (Fig. 5d) shows Ag, C, and O, with a distinct Ag distribution (Fig. 5d) visible across the sample.

HR-TEM-SAED analysis of AgNPs

The structural characteristics, including morphology, size, and crystallinity, of the AgNPs were also investigated using HR-TEM and SAED (Fig. 6).

Fig. 6.

a-c HR-TEM images, (d) SAED pattern of AgNPs

HR-TEM images (Fig. 6a-c) provide detailed insights into the features of the NPs. Figure 6a shows particles that are roughly spherical to oval in shape, with some agglomeration. Size characterization of individual particles from Fig. 6a suggests diameters of 42–46 nm. Other high-resolution images, such as those in Fig. 6b, show one well-resolved AgNP with a size of 20 nm, indicating the presence of such small, individual NPs in the sample. Figure 6a-d display single AgNPs at higher magnifications, revealing excellent lattices with clear lattice spaces. The presence of these lattice spaces, which are prominently visible in Fig. 6c (Interplanar spacing), indicates atomic periodicity within the NPs, although some deviation from a standard Ag lattice plane may occur; this could be an artefact of the redline placement or a larger lattice defect. Figure 6c provides a further magnified view, revealing the well-crystallised nature of the AgNPs. The differences in size and shape suggest a broad size distribution, as previously reported in other studies involving green synthesis [50, 53]. The SAED pattern (Fig. 6f) displays several concentric bright rings, indicating a polycrystalline nature. These rings are attributed to diffraction from various crystallographic planes of metallic Ag. Instead of offset spots, sharply defined rings indicate the presence of numerous randomly oriented nano-crystallites. These rings provide precise d-spacings for the (111), (200), (220), and (311) planes of FCC Ag (JCPDS file no. 04-0783) [11], therefore confirming the existence of the metallic Ag phase. The configuration of these rings further signifies the elevated crystallinity of the synthesised AgNPs. HR-TEM image analysis indicated the formation of spherical to oval-shaped AgNPs with an average size of around 20 nm for individual particles and about 40–50 nm for agglomerated structures. The clear lattice planes in the HR-TEM images and the obvious concentric rings in the SAED pattern indicated the polycrystalline nature and crystallinity of the AgNPs.

Chemistry of 3, 4-dihydropyrimidin-2(1 H)-ones (DHPMs)

The spectral data for the synthesized 3, 4-dihydropyrimidin-2(1H)-one derivatives characterized by IR, ¹H NMR, ¹³C NMR and mass spectrometry are reported below.

1. ethyl 2-(4-methoxyphenyl)-4-methyl-6-oxo-3,4-dihydropyrimidin-2(1 H)-ones (4e): IR (cm^-1): 3228.84 (-NH), 2958.80 (-OCH₃), 1699.29 (-COOC₂H₅), 1643.35 (-CONH-), 1510.26 (C = C olefinic), 1083.99 (-C-O-C) cm^-1 (Fig. 7). ¹ H NMR (500 MHz, DMSO-d6): 1.087–1.115 δ (t, J = 7 Hz, 3 H, -CH₃), 2.236 δ (s, 3 H, -CH₃), 3.321 δ (s, 3 H, -OCH₃), 3.956–3.998 δ (q, J = 7 Hz, 2 H, -OCH₂), 5.090 δ (s, 1 H, -CH), 6.903–6.908 δ (d, -ArH), 7.132–7.150 δ (d, -ArH), 7.877 δ (s, 1 H, - NH), 9.139 δ (S, 1 H, - NH). ¹³C NMR (500 MHz, CDCl₃): 14.3 δ (-CH₃), 18.2 δ (-CH₃), 55.2 δ (-CH), 59.6 δ (-OCH₃), 59.6 δ (-OCH₂), 61.7 δ (-OCH₂), 100.0 δ (-C-OCH₃), 114.1-114.3 (-Ar), 127.7-127.8 (-Ar), 131.9 δ (-C = C-), 137.5 δ (-C = C-), 158.9 δ (-C = O), 165.8 δ (-COO) (Fig. 8). LC/MS (m/z): Anal. Calcd. for C₁₅H₂₀O₄N₂ is 292; found 291.13.

Fig. 7.

FTIR spectra of ethyl 2-(4-methoxyphenyl)-4-methyl-6-oxo-3,4-dihydropyrimidin-2(1H)-ones (4e)

Fig. 8.

(a) & (b) 1H-NMR, (c) Mass Spectra, and (d) 13C-NMR of ethyl 2-(4-methoxyphenyl)-4-methyl-6-oxo-3,4-dihydropyrimidin-2(1H)-ones (4e)

• 2)ethyl 4-(2-chlorophenyl)-6-methyl-2-oxo-3,4-dihydropyrimidin-2(1 H)-ones (4 g): IR (cm^-1): 3223.05 (-NH), 1695.43 (-COOC₂H₅), 1637.56 (-CONH-), 1512.19 (C = C olefinic), 1078.21 (-C-O-C) cm^-1 (Fig. 9). ¹ H NMR (500 MHz, DMSO-d6): 1.069–1.078 δ (t, J = 7 Hz, 3 H, -CH₃), 2.164 δ (s, 3 H, -CH₃), 3.861–3.884 δ (q, J = 7 Hz, 2 H, -OCH₂), 5.629 δ (s, 1 H, -CH), 7.251–7.301 δ (m, -ArH), 7.688 δ (S, 1 H, - NH), 9.256 δ (S, 1 H, - NH). ¹³C NMR (500 MHz, CDCl₃): 14.3 δ (-CH₃), 18.1 δ (-CH₃), 51.9 δ (-CH), 59.5 δ (-OCH₂), 128.5-132.1 δ (-Ar), 142.1 δ (-C = C-), 149.7 δ (-C = C-), 151.7 δ (-C = O), 165.4 δ (-COO) (Fig. 10). LC/MS (m/z): Anal. Calcd. for C₁₄H₁₆O₂N₂ is 295; found 295.08.

Fig. 9.

FTIR spectra of ethyl 4-(2-chlorophenyl)-6-methyl-2-oxo-3,4-dihydropyrimidin-2(1H)-ones (4g)

Fig. 10.

(a) & (b) 1H-NMR spectra, (c) Mass Spectra, and (d) 13C-NMR spectra of ethyl 4-(2-chlorophenyl)-6-methyl-2-oxo-3,4-dihydropyrimidin-2(1H)-ones (4g)

Biological and computational insights

Antibacterial activities

The antibacterial efficacy of Salmonella typhimurium (MTCC 98) was evaluated against all synthesized dihydropyrimidinone derivatives utilizing the disc diffusion method on an agar medium [54]. The test organism, MTCC 98, was cultivated in Luria-Bertani broth, a medium specifically designed for bacterial strains, and incubated at 37 °C for 24 h. The optical density of the bacterial culture was calibrated using 0.5 McFarland standards (equivalent to 10⁸ CFU/mL). The cell suspension was subsequently homogenized to attain a final density of (1 × 10⁶ CFU/mL). These prepared cultures were then used to assess bacterial activity via the agar cup diffusion methodology. In the assay, each agar plate had three wells: 0.05 mL of each sample was introduced into a single well, while two wells were designated for controls. The plates were incubated at 37 °C for 24 h thereafter. The antibacterial susceptibility of the compounds was determined by the presence of a clear zone surrounding the discs, indicating inhibition of growth of the test organisms. Explicitly stated that Ciprofloxacin (or equivalent standard antibiotic) was used as the positive control, while DMSO (solvent) served as the negative control. Plates were incubated symmetrically at 37 °C for exactly 24 h before measuring the zones of inhibition (ZOI) using a digital caliper. All biological assays and catalytic yield tests were conducted in triplicate (n = 3). The results of the antibacterial screening, specifically the inhibition zones, are consolidated in Table No. 3 for the dihydropyrimidinone derivatives (4a-4f) and are presented below.

Table 3.

Antibacterial screening of dihydropyrimidinone derivatives (4a-4 g)

Sr. No.	Compound	Zone of inhibition (mm)
		Salmonella typhimurium (MTCC 98)
1	Positive control (Chloramphenicol)	41 ± 0.8
2	Negative control (St. distilled water)	-
3	4a	12 ± 0.6
4	4b	11 ± 0.5
5	4c	11 ± 0.5
6	4d	-
7	4e	17 ± 0.5
8	4f	-
9	4 g	15 ± 0.4

From Table 3 above, it is clear that compounds 4a, 4b, 4c, 4e, and 4 g are more sensitive, while compounds 4d and 4f showed no antibacterial activity against Salmonella typhimurium. Among the tested compounds, 4-methoxybenzaldehyde (4e) showed the strongest antibacterial activity, with the largest zone of inhibition (17 mm). This was followed by 2-chlorobenzyl (4 g) and benzaldehyde (4a), which were purified and showed moderate activity with zones of 15 mm and 12 mm, respectively. m-nitrobenzaldehyde (4b) and 4-bromobenzaldehyde (4c) exhibited comparatively lower antibacterial effects, each producing an 11 mm zone of inhibition. Notably, the purified p-chlorobenzaldehyde (4d) and 4-methylbenzaldehyde (4f) showed no observable antibacterial activity, indicating a lack of efficacy in inhibiting bacterial growth. The inhibition zone of compounds 4a-4 g is shown in Fig. 11a-d.

Fig. 11.

a-d Zone of inhibition (mm) of compound 4a-4g against Salmonella typhimurium

Molecular docking

Molecular docking assessments have been conducted for synthesized compounds. Numerous software applications are available for conducting molecular docking; however, we have used a widely accessible platform, specifically Auto Dock Vina, to evaluate the binding interactions of a ligand with a macromolecule, such as a protein, along with its associated binding affinity [55, 56]. The protein (PDB ID: 5GNA) from Salmonella typhimurium was used to investigate interactions with the compound. The visualization of the protein-ligand interaction was executed using PyMOL software [57]. Molecular docking analysis facilitates the elucidation of target binding sites pertinent to docking. The software predicts the intermolecular van der Waals interactions that occur between proteins and ligands. Table 4 presents the various modes and affinities, expressed in kcal/mol, for compounds 4e and 4 g.

Table 4.

Mode, affinity, and distance from best mode (A^o) of 4e and 4 g for Salmonella typhimurium Protein(PDB ID: 5GNA) (r. m. s. d. l. b.: Root mean square deviation lower boundary and r. m. s. d. u. b.: Root mean square deviation upper boundary

Compound	Mode	Affinity (kcal/mol)	Distance from best mode (Ao)
			r. m. s. d l. b.	r. m. s. d u. b.
4e	1	-5.1	0.000	0.000
	2	-5.1	22.056	24.528
	3	-5.0	22.776	24.489
	4	-4.9	13.720	15.857
	5	-4.9	20.782	22.427
	6	-4.8	21.828	23.493
	7	-4.7	13.449	17.493
	8	-4.7	21.522	25.241
	9	-4.6	23.267	24.959
4 g	1	-5.2	0.000	0.000
	2	-5.0	13.903	15.839
	3	-5.0	3.285	4.429
	4	-5.0	23.210	25.544
	5	-5.0	22.964	24.708
	6	-4.9	21.693	23.427
	7	-4.9	22.781	25.321
	8	-4.9	20.286	21.950
	9	-4.8	14.747	17.351

From above data, it is evident that compounds 4e and 4 g exhibit a moderate binding affinity and satisfactory structural complementarity toward the protein, indicating significant protein-ligand interactions. The docking score indicates good binding affinity for compounds 4e and 4 g, with values of -5.1 kcal/mol and − 5.2 kcal/mol, respectively. The binding interactions of the compounds are illustrated in Fig. 12 and Fig. 13 below. Ligplot + v.2.2.9 was used to investigate protein-ligand interactions. Table 5 displays how the ligands interact with different target protein amino acid residues.

Fig. 12.

Interaction of various proteins with compounds 4e and 4g

Fig. 13.

Interaction of different ligands with the target protein of Ligplot+ v.2.2.9. a ethyl 2-(4-methoxyphenyl)-4-methyl-6-oxo-3,4-dihydropyrimidin-2(1H)-ones (4e)ethyl 4-(2-chlorophenyl)-6-methyl-2-oxo-3,4-dihydropyrimidin-2(1H)-ones (4g)

Table 5.

Interactions of synthesized compounds against Salmonella typhimurium

Sr No.	Protein	Ligand	Hydrophilic Interactions	Hydrophobic Contacts	No. of H-Bonds
1	Salmonella typhimurium (5 GNA)	ethyl 2-(4-methoxyphenyl)-4-methyl-6-oxo-3,4-dihydropyrimidin-2(1 H)-ones (4e)	Leu36(A)	Gln42(B), Thr45(B), Glu39(A) Met46(B), Leu43(A), Lys49(B)	1
2		ethyl 4-(2-chlorophenyl)-6-methyl-2-oxo-3,4-dihydropyrimidin-2(1 H)-ones (4 g)	Leu36	Gln42, Glu39, Thr45, Met46 Leu43	1

1. ethyl 2-(4-methoxyphenyl)-4-methyl-6-oxo-3,4-dihydropyrimidin-2(1 H)-ones (4e).

ethyl 4-(2-chlorophenyl)-6-methyl-2-oxo-3,4-dihydropyrimidin-2(1 H)-ones (4 g).

From the above Ligplot⁺ diagram, it is clear that the N₂ atom of compound 4e interacts with Leu36(A) with a bond length of 2.88 A and the N₂ atom of compound 4 g interacts with Leu36 with a bond length of 3.00 Awith the protein molecule of Salmonella typhimurium.

In Fig. 14, different protein-protein interactions for different microbes are evaluated. The dotted line represents hydrogen bonding between residues along the chain, and the arc represents a hydrophobic interaction. The result reveals that the area between the interfaces of naturally occurring complex (Chain A-B) was more (3.35 A⁰) of Leu50(B) with Lys81(A), (2.62 A⁰) of Thr53(B) With Glu77(A), (2.84 A⁰) of Gln39(B) with Arg87(A), (2.58 A⁰) of Lys66(B) with Arg60(A), in Salmonella typhimurium protein (PDB ID: 5 GNA).

Fig. 14.

2-D Interaction plot DIMPLOT diagram of Salmonella typhimurium protein (PDB ID: 5GNA)

Rainbow spectrum

Different energy-minimised proteins, as shown in the rainbow spectrum used in docking studies of compounds 4e and 4 g, are depicted in Fig. 15.

Fig. 15.

Rainbow spectrum of Salmonella typhimurium protein (PDB ID: 5 GNA) and compounds 4e and 4g

Normal mode analysis (NMA) and protein stability studies

Normal Mode Analysis (NMA)” or “iMODS analysis enables the understanding of the motion of atoms and molecules present in proteins over time, providing insights into their behavior and interactions. By modeling atomic forces, molecular dynamics (MD) simulations predict time-dependent physical movements to reveal underlying mechanisms of protein folding, ligand binding, and molecular diffusion. M. Kirar et al. (2022) have reported a virtual screening and molecular dynamics simulation study of plant protease inhibitors against SARS-CoV-2 envelope protein using the MODS server available on (www.imods.iqf.csic.es/) for studying molecular dynamics simulation in proteins. It evaluates the protein stability by computing its internal coordinates through normal mode analysis (NMA). The stability of the protein is represented by its main-chain deformability plot, β-factor values, eigenvalues, covariance matrix, and elastic network model. Molecular dynamics simulation of Salmonella typhimurium is shown in Fig. 16.

Fig. 16.

Normal Mode Analysis (NMA) obtained for Salmonella typhimurium structure (a), deformability (b, c), β-factor (d), eigenvalue (e), variance map (f), correlation matrix (g), elastic network model (h)

In the correlation matrix, coloured bars represent the individual (red) and cumulative (green) variances. In the elastic network graph, dots are coloured by stiffness; darker greys indicate stiffer springs, and vice versa. (For interpretation of the references to colour in this Fig. legend, refer to the website. The structure of the Salmonella typhimurium protein was obtained from the IMOD calculation and is shown in Fig. 16(a). The direction of the arrow shows the motion of the amino acid residues. Figure 16(b) and 16(c) illustrate the main-chain deformability profiles of the target protein. Peaks in these plots correspond to regions of higher structural flexibility, which typically represent surface-exposed loops capable of undergoing conformational rearrangements to facilitate or accommodate ligand binding. Specifically, the residue around index 58 exhibits a pronounced deformability peak, suggesting a highly flexible region that may assist in molecular recognition through an induced-fit mechanism. Figure 16(d) represents the NMA and PDB mobility β-factor. It indicates the mobility profile and the relative amplitude of atomic displacements around the equilibrium conformation, which differ. Figure 16(e) represents the eigenvalue of the protein. It shows the motion and stiffness and is related to the energy to deform the structure. More -ve value indicates more deformation. The variance map shown in Fig. 16(f) is inversely proportional to the eigenvalue. The correlation matrix for the Salmonella typhimurium protein is shown, providing information on the interactions and couplings among protein residues. The covariance matrix between pairs of residues is shown in Fig. 16(g), illustrating their correlations (red: correlated, white: uncorrelated, blue: anti-correlated). The higher the redness, the stronger the correlation with ligand interaction. The Salmonella typhimurium protein exhibits a strong correlation with the ligand. The elastic network Model is represented in Fig. 16(h). A darker grey shade indicates stiffness of the amino acid residue. More stiffness, i.e., less deformability, is required to interact with the ligand. The protein of Salmonella typhimurium is of small size, and the grey colour shading indicates a good interaction with the ligand.

Pass analysis

The examination of biological activities via PASS analysis is delineated in Table 6. Compounds are deemed to exhibit greater potency if they possess elevated Pa values in comparison to Pi (probability of being inactive). In our research, significant drug activity is associated with Pa > 0.8, moderate therapeutic efficacy with 0.5 < Pa < 0.8, and inadequate pharmaceutical activity with Pa < 0.5. According to PASS predictions, all compounds (4e and 4g) demonstrated pharmaceutical efficacy.

Table 6.

Biological properties calculated through the PASS webserver for compounds 4e and 4 g

Compound	Pa	Pi	Biological Activities
4e	0.858	0.003	Spasmolytic, Papaverin-like
	0.769	0.004	Leukopoiesis stimulant
	0.711	0.007	Vasodilator
	0.695	0.005	Ca channel (voltage-sensitive) activator
	0.695	0.008	Vasodilator, coronary
	0.674	0.012	Antianginal
	0.667	0.057	Antieczematic
	0.596	0.007	Leukopoiesis inhibitor
	0.597	0.011	Antihypertensive
	0.642	0.065	Membrane permeability inhibitor
	0.568	0.009	Inflammatory Bowel Disease Treatment
	0.553	0.003	Ca channel blocker
	0.567	0.018	Spasmolytic
	0.549	0.004	Alpha 1b adrenoreceptor antagonist
	0.535	0.004	Ca channel (voltage-sensitive) blocker
4 g	0.745	0.015	5-O-(4-coumaroyl)-D-quinate 3’-monooxygenase inhibitor
	0.698	0.006	Leukopoiesis stimulant
	0.689	0.004	Spasmolytic, Papaverin-like
	0.708	0.035	Membrane permeability inhibitor
	0.649	0.011	Ca channel (voltage-sensitive) activator
	0.639	0.016	Antianginal
	0.578	0.018	Centromere-associated protein inhibitor
	0.568	0.013	Antihypertensive
	0.561	0.009	Inflammatory Bowel Disease Treatment
	0.552	0.017	Vasodilator
	0.545	0.012	Leukopoiesis inhibitor
	0.537	0.004	Ca channel (voltage-sensitive) blocker
	0.525	0.003	Calcium channel blocker
	0.536	0.036	CYP3A1 substrate
	0.518	0.023	Vasodilator, coronary
	0.745	0.015	5-O-(4-coumaroyl)-D-quinate 3’-monooxygenase inhibitor
	0,698	0.006	Leukopoiesis stimulant

Conclusion

In summary, this study successfully demonstrated an efficient, eco-friendly green synthesis of silver nanoparticles (AgNPs) utilizing the bio-reducing potential of Aloe vera leaf extract. These biogenic AgNPs served as an excellent, recyclable heterogeneous Lewis acid catalyst for the one-pot multicomponent Biginelli synthesis of structurally diverse 3,4-dihydropyrimidin-2(1 H)-ones (DHPMs), delivering high product yields (up to 95–96%) within optimized reaction profiles. The synthesized DHPM derivatives exhibited prominent in vitro antibacterial activity against the Gram-negative foodborne pathogen Salmonella typhimurium, which correlated strongly with our in silico molecular docking binding energies and stability trends obtained via iMODS Normal Mode Analysis (NMA). Looking forward, the future outlook of this work focuses on scaling up this green catalytic system for continuous-flow industrial organic synthesis to evaluate its structural performance over extended cycles. Furthermore, we aim to expand the chemical library of these privileged DHPM scaffolds by exploring diverse multi-component variations. Most importantly, future studies will transition from in vitro evaluations to comprehensive in vivo toxicity screens and pharmacokinetic modeling. This will help determine the precise molecular mechanisms, bioavailability, and cellular safety profiles of these active candidates, paving the way for their potential development as specialized target-specific antimicrobial agents.

Supplementary information

Below is the link to the electronic supplementary material.

Abbreviations

• AgNPs

Silver Nanoparticles

• DHPMs

3,4-dihydropyrimidin-2(1 H)-ones

• IR

Infrared

• ¹H NMR

Proton Nuclear Magnetic Resonance

• ¹³C NMR

Carbon-13 Nuclear Magnetic Resonance

• MS

Mass spectrometry

• PASS

Prediction of Activity Spectra for Substances

• Pa

Probability value (of being active)

• Pi

Probability value (of being inactive)

• MNA

Multilevel neighbours of an atom

• MTCC

Microbial Type Culture Collection

• CFU/mL

Colony-forming units per milliliter

• PDB

Protein Data Bank

• r. m. s. d. l. b.

Root mean square deviation lower boundary

• r. m. s. d. u. b.

Root mean square deviation upper boundary

• AgNO₃

Silver nitrate

• H₂SO4

Sulfuric acid

• cm^− 1

Wavenumbers per centimeter

• MHz

Megahertz

• ppm

Parts per million

• A⁰

Angstroms

• kcal/mol

Kilocalories per mole

• nm

Nanometer

Author contributions

R.P.: Conceptualization; Data curation; Formal analysis. M.G.: Writing – original draft; S.S.: Writing – review and editing. S.T.: Resources; Software, Supervision. A.R.: Validation; Visualization. S.U.: Investigation; Methodology; Project administration.

Funding

None.

Data availability

The authors declare that the data supporting the findings of this study are available within the paper.

Declarations

Ethics and consent to participate

Not applicable for this manuscript.

Consent for publication

Not applicable for this manuscript.

Consent to publish

Not applicable for this manuscript.

Competing interests

The authors declare no competing interests.