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. 2025 Sep 12;13(3):132. doi: 10.1007/s40203-025-00425-2

Benzylidene Oxazolo[3,2-a]pyrimidine derivatives as promising anti-inflammatory agents: synthesis, quantum simulations, and molecular Docking

Abdalla Ali Amin 1,2, Ali Rasw Hamad 3, Yousif Hussein Azeez 4, Karzan Mahmood Ahmed 5, Rebaz Obaid Kareem 4, Rzgar Faruq Rashid 6, Khdir Ahmed Othman 1, Rebaz Anwar Omer 1,✉
PMCID: PMC13631196  PMID: 42828030

Abstract

This study reports the successful synthesis of a novel series of bicyclic benzylidene oxazole pyrimidine derivatives namely (Z)-6-benzoyl-2-benzylidene-5,7-diphenyl-5H-oxazolo[3,2-a]pyrimidin-3(2H)-one (C1), (Z)-6-benzoyl-2-(3,4-dimethoxybenzylidene)-5,7-diphenyl-5H-oxazolo[3,2-a]pyrimidin-3(2H)-one (C2), and (Z)-6-benzoyl-2-(4-fluorobenzylidene)-5,7-diphenyl-5H-oxazolo[3,2-a]pyrimidin-3(2H)-one (C3) via a one-pot Hantzsch heterocyclization and Knoevenagel condensation. The compounds were characterized by FTIR, 1H-NMR, and 13C-NMR spectroscopy, supported by theoretical calculations. Quantum chemical simulations using B3LYP/6-311G + (d,p) provided insights into electronic properties, including HOMO–LUMO gaps, MEP surfaces, Fukui functions, and topological parameters. Monte Carlo (MC) simulations evaluated adsorption behavior on Fe(110) and Cu(111), with C2 exhibiting the strongest binding affinity. Drug-likeness and toxicity assessments classified the compounds in the 2nd toxicity class, with C1 being BBB toxic, C2 immunotoxic, and C3 neurotoxic and BBB toxic. Molecular docking (MD) studies indicated C1 as a potent COX-2 inhibitor (− 10.137 XP GScore), stabilized by π⋅⋅⋅π interactions, while C2 showed strong hydrogen bonding in the NF-κB pathway. Molecular dynamics simulations confirmed the stability of the COX-2-C1 complex, highlighting key ligand–protein interactions. These findings suggest C1 as a promising COX-2 inhibitor and C2 as a potential NF-κB modulator, offering insights for future drug development.

Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1007/s40203-025-00425-2.

Keywords: Bicyclic benzylidene oxazole, DFT, MC, ADMET, Corrosion inhibition, Drug-likeness and toxicity prediction

Introduction

The synthesis of heterocyclic compounds remains a central area of research in organic chemistry due to their wide-ranging biological activities (Katritzky et al. 2010). Among these, five- and six-membered oxen and nitrogen-containing rings are the most frequently employed in pharmaceutical development, followed by oxygen, nitrogen, and sulfur-containing heterocycles such as oxazole and pyrimidine derivatives (Joule 2020; Gholap et al. 2004; Yernale et al. 2025). Notably, nitrogen and oxen-rich heterocyclic structures are particularly significant in drug design (Rippel et al. 2024). The incorporation of both oxazole and pyrimidine a motif within a single molecular framework has gained interest, with ongoing investigations aimed at developing hybrid structures that merge these components. Oxazole rings, which are commonly found in natural compounds and therapeutic agents, are recognized for their chemical stability and diverse bioactive properties, including antibacterial, anti-diabetic, antifungal, antiviral, anti-HIV, antioxidant, and anticancer effects (Asiri et al. 2024; Liu et al. 2019; Kim et al. 2012; Rathwa et al. 2018; Mohamed et al. 2013; Fesatidou et al. 2020; Kumar and Goel 2022; Kerru et al. 2020; Zhao et al. 2019). Similarly, pyrimidine derivatives are crucial due to their role in nucleic acid biosynthesis and their broad pharmacological applications.

Current research emphasizes the structure–activity relationships (SAR) of these compounds to enhance their chemical utility. Multi-component reactions (MCRs) play an essential role in combinatorial chemistry by enabling the efficient synthesis of compounds in a single step, under simplified reaction conditions, and with minimal purification requirements (Toure and Hall 2009; Rezaeifard et al. 2024; Shahi et al. 2024). This methodology optimizes the Biginelli reaction by incorporating all reagents into the final product (Kappe 1993; Khasimbi et al. 2021; Fadlan et al. 2025). Furthermore, Density Functional Theory (DFT) serves as a computational technique that accurately predicts molecular properties at a relatively low computational cost (Parr 1989). It is employed to examine frontier orbitals, identify nucleophilic and electrophilic sites, and assess molecular kinetics and thermodynamics (Becke 1993). Additionally, DFT facilitates molecular structure optimization, infrared (IR) spectral simulations, and the evaluation of Frontier Molecular Orbitals (FMOs), which provide insights into a molecule’s electronic configuration and reactivity (Cohen et al. 2012; Pereira et al. 2017; Geerlings et al. 2003; Nakliang et al. 2021; Bhatia 2024; Townsend and Grayson 2020).

The aim of this study is to synthesize and characterize a novel series of bicyclic benzylidene oxazole pyrimidine derivatives (C1, C2, and C3) (Scheme 1) using a one-pot Hantzsch heterocyclization and Knoevenagel condensation. The study explores their electronic properties through quantum chemical simulations, adsorption behavior on Fe(110) and Cu(111) via Monte Carlo simulations, and biological potential through drug-likeness, toxicity, molecular docking, and molecular dynamics studies.

Scheme 1.

Scheme 1

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Synthesis of benzylidene oxazole pyrimidine compounds

Experimental and methods

The melting points of the samples were measured using an electrothermal apparatus without applying a temperature correction. Infrared (IR) spectra were recorded on a Perkin-Elmer spectrometer, utilizing potassium bromide (KBr) as the supporting matrix. Proton nuclear magnetic resonance (1H and 13C NMR) spectra were acquired on a Varian Mercury 400 MHz spectrometer, with dichloromethane (DCM-d6), and dimethyl sulfoxide (DMSO) serving as the solvent and tetramethyl silane (TMS) as the internal reference for chemical shift calibration, expressed in δ ppm. Thin-layer chromatography (TLC) was employed for monitoring all reactions, using DC Alufolien Kieselgel 60F 254 Merck plates and a Camag TLC lamp (254/365 nm).

5-benzoyl-4,6-diphenyl-3,4-dihydropyrimidin-2(1H)-one (4a)

The synthesis of compound 4a was a reaction mixture comprising 1,3-diphenyl-1,3-propanedione (4.8 mmol), benzaldehyde (5 mmol), and urea (5 mmol) in 15 mL of glacial acetic acid was subjected to reflux for 24 h in the presence of a few drops of concentrated hydrochloric acid (HCl). Subsequently, the reaction mixture was allowed to cool and left to stand at room temperature for 12 h. The resulting precipitate was then collected via filtration and purified through recrystallization using ethanol, affording the desired product a yield of 92% with a melting point of 264 °C.

General procedure for synthesis of compounds C(1–3)

Compound 4a (1 mmol), acetic anhydride (2 ml), bromoacetic acid (1mmol), anhydrous sodium acetate (1 mmol), and aryl-aldehyde derivatives (1.2 mmol) in glacial acetic acid (12 ml), was refluxed for 10 h. The reaction mixture was continuously stirred until the spot of the compound completely disappeared from the TLC plate. Subsequently, the reaction solution cools to room temperature, leading to the direct crystallization of the product at the bottom of the round-bottom flask. The resulting solid was then filtered, and the precipitate was purified through recrystallization using an appropriate solvent.

(Z)-6-benzoyl-2-benzylidene-5,7-diphenyl-5H-oxazolo[3,2-a]pyrimidin-3(2H)-one (C1)

Yield (95%), Melting point: 267 °C. IR (cm−1): 3186–3057 (sp2 C–H), 2926–2893 cm−1 (sp3 C–H), 1676 cm−1 (C=O), 1639 cm−1 (C=N), 1614 and 1446 cm−1 (C=C). 1H-NMR (DMSOd6/δ ppm): δ 9.468 (s, 1H,=CH), 8.048–6.999 (m, 20Harom), 5.389 (s, 1H, C18-H). 13C-NMR (DMSOd6/δ ppm): 195.31 (C=Obenzoyl), 164.72 (C=OOxazolopyrimidine-3(2H)-one), 153.15, 148.72, 144.57, 140.05, 133.91, 131.11, 130.17, 130.11, 128.95, 128.22, 127.88, 127.83, 126.95, 109.84, 55.99 (C18) (Supporting information S1, S2 and S3). Molecular weight (C32H22N2O3): 482.16 g/mol.

(Z)-6-benzoyl-2-(3,4-dimethoxybenzylidene)-5,7-diphenyl-5H-oxazolo[3,2-a]pyrimidin-3(2H)-one (C2)

Yield (91%), Melting point: 262 °C. IR (cm−1): 3196–3080 (sp2 C–H), 2918 cm−1 (sp3 C–H), 1697 cm−1 (C=O), 1666 cm−1 (C=N), 1625 and 1444 cm−1 (C=C). 1H-NMR (DMSOd6/δ ppm): δ 12.015 (s, 1H,=CH), 9.453–8.031 (m, 3Hbenzilidine ring), 7.482–6.993 (m, 20Harom), 5.379 (s, 1H, C18-H), 1.931 (s, 1H, OCH3). 13C-NMR (DMSOd6/δ ppm): 195.30 (C = Obenzoyl), 172.54 (C=OOxazolopyrimidine-3(2H)-one), 153.13, 148.70, 144.56, 140.05, 133.90, 131.10, 130.16, 130.10, 128.94, 128.21, 127.87, 127.82, 126.95, 109.83, 55.99 (C18), 21.54 (OCH3) (Supporting information S4, S5 and S6). Molecular weight (C34H26N2O5): 542.18 g/mol.

(Z)-6-benzoyl-2-(4-fluorobenzylidene)-5,7-diphenyl-5H-oxazolo[3,2-a]pyrimidin-3(2H)-one (C3)

Yield (93%), Melting point: 278 oC. IR (cm−1): 3196–3061 (sp2 C–H), 2902 cm−1 (sp3 C–H), 1697 cm−1 (C=O), 1666 cm−1 (C=N), 1624 and 1446 cm−1 (C=C). 1H-NMR (DMSOd6/δ ppm): δ 12.033 (s, 1H, =CH), 9.478–8.059 (dd, 4Hbenzilidine ring), 7.501–7.000 (m, 15Harom), 5.406 (s, 1H, C18-H). 13C-NMR (DMSOd6/δ ppm): 195.32 (C = Obenzoyl), 172.57 (C = OOxazolopyrimidine-3(2H)-one), 153.20 (C4-F), 148.67, 144.56, 140.05, 133.91, 131.11, 130.17, 130.10, 128.95, 128.22, 127.87, 127.84, 126.96, 109.87, 56.02 (C18) (Supporting information S7, S8 and S9). Molecular weight (C32H21FN2O3): 500.15 g/mol.

Study of DFT

GaussView 6.0 was used to visualize the molecular structures of compounds C1, C2, and C3 compounds. The geometries were optimized in the gas phase using the B3LYP/6-311G + (d,p) method implemented in Gaussian 09, Revision D.01. Additionally, GaussView 6.0 generated HOMO, LUMO, and molecular electrostatic potential (MEP) surfaces, as well as Fukui functions, topological parameters, and the Drug-likeness model score from MolSoft for the optimized title molecules (Azeez et al. 2024; Roopa et al. 2023).

Target selection and molecular docking

Molecular docking of two studied compounds was conducted using the Maestro docking suite (Schrödinger) to assess their binding affinities with Human Cyclooxygenase-2 (COX-2) an enzyme involved in inflammation and pain regulation and the NF-κB signaling (A20 ZnF4), a zinc-finger protein that regulates immune responses (Ahmad et al. 2023). The protein crystal structures were retrieved from the RCSB Protein Data Bank (PDB). Preprocessing involved the removal of bound ligands and water molecules, the addition of missing hydrogen atoms and residues, and ensuring correct protonation states. The ligands molecules C(1–3) were prepared by adding hydrogen atoms, neutralizing charges, and creating tautomeric forms. GLIDE was used to prepare the grids for each protein, which determined the interaction sites for docking. Docking calculations were carried out using Extra Precision (XP) mode in Glide to determine the most suitable binding conformations (Sardar 2023; Mathada et al. 2024). The results were analyzed using GlideScore, Glide eModel, and interaction energies such as hydrogen bonds (H-Bond), hydrophobic interactions (PhobEn), and electrostatic interactions (Electro). The highest binding-affinity docking poses were noted and examined using Maestro. It gave information about the potential binding of compounds with the target proteins. The most favorable docking complexes, in terms of Glide docking score as well as shape, were taken for further Molecular Dynamics Simulations (MDS).

In silico drug-likeness analysis

ADMET properties were evaluated using the SwissADME (Ahmad et al. 2023), BOILED-Egg (Sardar 2023), and ProTox-II (Banerjee et al. 2018) tools.

Execution of molecular dynamics simulations

Molecular dynamics simulations of the COX-2–1 complex were conducted using the Desmond Maestro docking suite (2023) (Schrödinger). Each system was inserted in an orthorhombic box with a TIP3P solvent model, and charge neutralization was achieved by adding Na+ and Cl– ions according to the requirements of the system (Gupta et al. 2015). The initial step was the relaxation of steric clashes in all systems through energy minimization. Equilibration of systems was performed with NPT ensembles using the SHAKE algorithm, and the system temperature at 300 K and pressure at 1 bar was maintained. After equilibration, a molecular dynamics simulation of 50ns was performed for the complex (Kumar et al. 2016). At the end of the simulation, complex trajectory files were used to calculate protein and ligand root-mean-square deviation (RMSD), the protein and ligand root-mean-square fluctuation (RMSF), protein–ligand interaction, ligand torsion, and properties.

Result and discussion

FTIR spectroscopy

The DFT results of the FTIR measurements made on compounds C1, C2, and C3 are presented in Fig. 1, and the B3LYP/6-311G + (d,p) technique was utilized to produce predictions regarding the vibrational frequencies of our materials (Hamad et al. 2023). According to the FT-IR findings, the vibration peak was detected as C–H bending at1657, symmetric stretching at 3200, asymmetric stretching at 3209, O–H stretching at 1702, 1832, C=C stretching at 1719, and symmetric stretching of benzene ring at 3209 cm−1 for compound C1. Also, the vibration peak was detected in C–H bending at 1657–1654, symmetric stretching at 3157, asymmetric stretching at 3174–3243, O–H stretching at 1830, C═C stretching at 1744, CH3 symmetric stretching at 3031, CH3 asymmetric stretching 3154–3106 and symmetric stretching of benzene ring at 3218 cm−1 for compound C2. The vibration peak was detected as C–H bending at 1639, 1656, symmetric stretching at 3226, 3209, asymmetric stretching at 3180–3203, O–H stretching at 1833, C═C stretching at 1746, and symmetric stretching of benzene ring at 3209 cm−1 for compound C3 (Fig. 1).

Fig. 1.

Fig. 1

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FT-IR spectra of the C1, C2, and C3 compounds were analyzed using the DFT approach

Nuclear magnetic resonance (NMR) spectroscopy

Nuclear Magnetic Resonance (NMR) calculations play a crucial role in obtaining structural information about the molecules under investigation. Additionally, NMR is a valuable technique for understanding the relationship between molecular structure and electronic properties. By analyzing the behavior of nuclei in a magnetic field, it is possible to determine the skeletal framework of a molecule. This analysis provides unique resonance signals for the nuclei of C1, C2, and C3 compounds (Fig. 2, Table 1) (Yılmaz and Kebiroglu 2022, 2024).

Fig. 2.

Fig. 2

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The theoretical NMR chemical shifts for compounds C1, C2, and C3

Table 1.

NMR chemical shifts of mentioned title compounds C1, C2, and C3

C1 C2 C3
Elements Shielding (ppm) Elements Shielding (ppm) Elements Shielding (ppm)
7-C 182.737 7-C 182.623 7-C 182.7658
29-C 144.8982 29-C 144.814 24-C 149.969
2-C 138.644 36-C 142.6286 29-C 144.825
4-C 138.2683 35-C 139.885 4-C 138.4081
11-C 126.227 2-C 138.7693 2-C 137.3291
28-C 125.4095 4-C 138.3571 11-C 126.5979
10-C 124.886 11-C 126.3391 28-C 125.3679
8-C 123.2342 10-C 124.9717 8-C 123.3151
38-C 120.1167 28-C 124.8697 10-C 120.8922
14-C 118.4671 8-C 123.1557 38-C 120.154
33-C 117.876 14-C 118.4216 22-C 118.712
36-C 116.8553 12-C 116.5396 14-C 118.5831
34-C 116.4723 34-C 116.4133 26-C 118.017
12-C 116.4353 22-C 116.3383 33-C 117.7979
22-C 116.4006 16-C 115.5843 36-C 116.8587
16-C 115.536 26-C 115.4107 34-C 116.4268
26-C 115.365 18-C 115.3142 12-C 116.3095
18-C 115.3164 24-C 115.2932 16-C 115.5878
24-C 115.2785 33-C 115.2861 18-C 115.3501
21-C 115.2476 21-C 115.1836 21-C 114.9431
35-C 114.8249 19-C 114.3988 35-C 114.8383
37-C 114.4795 38-C 114.1921 37-C 114.5847
19-C 114.4085 25-C 113.9572 19-C 114.3621
25-C 113.9345 15-C 113.7328 15-C 113.9069
15-C 113.7897 20-C 113.35 20-C 113.3981
20-C 113.3595 17-C 113.34 13-C 113.2843
17-C 113.3303 13-C 113.2231 17-C 113.041
13-C 113.2342 23-C 112.6813 1-C 108.7243
23-C 112.7162 37-C 111.3143 31-C 103.9991
1-C 108.8358 1-C 108.7604 25-C 102.1173
31-C 103.8489 31-C 103.0935 23-C 100.5778
6-C 53.4481 6-C 53.3522 6-C 53.4533
42-C 48.1622
40-C 47.8707
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The experimentally 1H-NMR spectrum of compound C1 recorded in DMSO-d₆ reveals key proton environments. The singlet at δ 9.468 ppm corresponds to a one hydrogen of (=CH). The multiples in the δ 8.048–6.999 ppm range (20H) represents the aromatic protons, suggesting the presence of multiple benzene rings contributing to a complex splitting pattern due to various electronic environments. The singlet at δ 5.389 ppm is assigned to C18-H. In the C2 a downfield singlet at δ 12.015 ppm corresponds to the deshielded = CH proton. The aromatic region exhibits two multiplets: one spanning δ 9.453–8.031 ppm (3H), attributed to protons on the benzylidene ring, and another broader signal at δ 7.482–6.993 ppm (20H), corresponding to multiple aromatic protons within the molecular core. A distinct singlet at δ 5.379 ppm represents the C18-H proton, indicating a possibly sterically constrained environment. Additionally, a singlet at δ 1.931 ppm is assigned to the OCH₃ group, suggesting its shielding by adjacent electronegative atoms. The 1H-NMR spectrum of compound C3, recorded in DMSO-d₆, reveals key proton environments corresponding to its structural framework. A singlet at δ 12.033 ppm corresponds to the = CH proton. The doublet of doublets (dd) in the range δ 9.478–8.059 ppm is attributed to the four protons of the benzylidene ring, reflecting their deshielded nature due to conjugation and electron-withdrawing effects. The multiplet appearing between δ 7.501–7.000 ppm, integrating for 15 aromatic protons, suggests the presence of multiple substituted benzene rings contributing to a complex aromatic region. Finally, a singlet at δ 5.406 ppm corresponds to the C18-H proton, likely associated with a sp3-hybridized carbon, potentially adjacent to an electronegative group. The overall spectral data align well with the expected structure of C3, confirming the presence of conjugated and aromatic functionalities.

The experimentally 13C-NMR spectra of compounds C1, C2, and C3 in DMSO-d6_66​ exhibit characteristic signals corresponding to their structural frameworks. All three compounds display a prominent signal around 195.30–195.32 ppm, attributed to the benzoyl carbonyl (C=O), and a peak in the range of 164.72–172.57 ppm, assigned to the oxazolopyrimidine-3(2H)-one carbonyl (C=O). The aromatic region is well-represented by multiple signals between 153.13 and 126.95 ppm, indicating various substituted and unsubstituted benzene carbons. The C18 carbon appears consistently around 55.99–56.02 ppm. Notably, C2 exhibits an additional peak at 21.54 ppm, attributed to the methoxy (-OCH3_33​) group, distinguishing it from C1 and C3. Meanwhile, C3 shows a slight shift in the C4 carbon (153.20 ppm), likely due to fluorine substitution. These spectral variations provide valuable insights into the electronic environments and functional groups present in each compound.

The computed chemical shift values of the examined compounds are provided in Table 1, and Fig. 2. The carbon (C) atoms that are present in compounds C1, C2, and C3 are identical.

Optimization shape

An increasing number of quantum chemical computations, including the HOMO–LUMO energy analysis, are being utilized to forecast the efficiency, reactivity, and stability of corrosion inhibition. The outcomes of these computations indicate the inhibitor's ability to both donate (HOMO) and accept (LUMO) electrons from the metal surface. This, in turn, has an effect on the formation of protective layers and, ultimately, the efficiency of corrosion inhibition. In particular, the HOMO–LUMO energy levels and the link between those levels and the entire quantum chemical properties were emphasized more than anything else. The existence of these properties sheds significant insight into the ability of the compounds to donate and absorb electrons, which may affect the reactivity and chemical behavior of the compounds (Azeez et al. 2024, 2025). Through the use of the B3LYP/6-311G + (d,p) technique, the optimal geometrical shape was optimized in the gas phase for compounds C1, C2, and C3 (Fig. 3).

Fig. 3.

Fig. 3

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Optimized molecular structure of Compound C1, C2, and C3

It was revealed that compounds C2 possess the highest values of dipole moment about ~ 4.0 Debye of the, which is characterized by the highest overall imbalance in the charge from one side of a title compound to the other side within the studied compound C2. In contrast, compounds C1, and C3 exhibit similar dipole moments, while compound C3 exhibits the lowest dipole moment values from approximately ~ 3.350 Debye, because of this molecule's very symmetrical shape (Table 2) (Azeez et al. 2024; Omer et al. 2024).

Table 2.

Dipole moment, frontier molecular orbitals, gap values, descriptors, molecule-to-metal electron charge transfer, and total negative charge for the optimized structures of the studied compounds

Parameters C1 C2 C3
μD (Debye) 3.4382 3.8279 3.3481
μx (Debye) 0.5750 1.6669 1.3866
μy (Debye) 1.4232 1.4602 0.3854
μz (Debye) 3.0765 3.1212 3.0230
EHOMO (eV) − 5.863 − 5.772 − 5.906
ELUMO (eV) − 2.254 − 2.203 − 2.305
ΔELUMO – HOMO = ELUMO – EHOMO (eV) 3.609 3.569 3.601
Ionization energy, I = –EHOMO (eV) 5.863 5.772 5.906
Electron affinity, A = –ELUMO (eV) 2.254 2.203 2.305
Electronegativity, χ = (I + A)/2 (eV) 4.059 3.988 4.106
Chemical potential, μ = –χ (eV) − 4.059 − 3.988 − 4.106
Global chemical hardness, η = (I – A)/2 (eV) 1.805 1.785 1.801
Global chemical softness, S = 1/(2η) (eV–1) 0.277 0.280 0.278
Back donation =—η /4 (eV) − 0.451 − 0.446 − 0.450
Global electrophilicity index, ω = μ2/(2η) (eV) 4.564 4.455 4.681
Molecule-to-metal electron charge transfer, ΔN1 = (Ф – χ)/(2η)a
  Fe 0.211 0.233 0.198
  Cu 0.239 0.261 0.226
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It was recorded that the HOMO and LUMO values for compounds C1, C2, and C3are very similar with minor differences. The HOMO and LUMO of compound C2 are lower than 3.569, and 5,772 eV, as well lowest energy gap ~ 3.600 eV (implies a good electron acceptor). Notably, this is a crucial point since it indicates the corrosion inhibition efficiency and reactivity, and less stable compound (Table 2). According to, electronegativity, softness, hardness, energy gap, and back donation, signifying their strong potential inhibitors under computed, a reactivity have ordered in a manner consistent with the theoretical data derived: C2 > C3 > C1. Finally, all of the C1, C2, and C3 compounds under study possess electrophilicity index values that are noticeably > 1.5 eV, demonstrating their potent electrophilic (Omer et al. 2024).

As seen in Table 2; C1, C2, and C3 compounds were computed as corrosion inhibitors for each mentioned molecule. To determine the asses of charge transfer and surface adsorption we used the most accurate formula that includes the work function (ϕ) on Fe, Cu metals surface (Michaelson 1977; Hamad et al. 2025). According to the shown Table 2, every C1, C2, and C3 compounds possess the ability to transfer electron charge from the metal to the molecule of the substance (positive charge transfer values revealed that electrons are being transferred from the inhibitor molecules to the Cu, and Fe metals surface) (Table 2).

The EHOMO and ELUMO of mentioned title compounds C1, C2, and C3 are located almost on the whole molecule C1, C2, and C3 with some minor differences (Fig. 4). The calculated molecular electrostatic potential (ESP) map of compounds C1, C2, and C3 assessed the Carbon–Oxygen-Carbon (C–O–C), Carbon–Oxygen (C–O), Carbon–Hydrogen (C–H), and Carbon–Fluorine (C–F) atoms, followed by the hydrogen (H) atoms were shown as the most remarkable electrophilic centers, while Oxygen atom shown as the most remarkable nucleophilic centers (Fig. 5). Thus, areas of negative electrostatic potential, which are linked to nucleophilic behavior (Carbon–Oxygen-Carbon (C–O–C)), and Carbon–Oxygen (C–O), are usually represented by the red zones. These areas show a high electron density, which increases the likelihood that the atom or molecule will give electrons (be a nucleophile) (Fig. 5).

Fig. 4.

Fig. 4

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The HOMO, LUMO energy representation

Fig. 5.

Fig. 5

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MEP maps for studied molecules

The Fukui function is a valuable parameter for evaluating insights into molecular reactivity, and its use in potential corrosion inhibition is crucial. Effective potential corrosion inhibitors efficiency are electron donors, thus, regions with a larger fk− value are more efficient in giving electrons to the positively charged on the metal surface. An electron donation ability establishes a protective layer preventing corrosion resistance (Yılmaz and Kebiroglu 2024; Azeez et al. 2025; Omer et al. 2024). The highest fk − values were revealed for O9 in C1, C2, and C3. This revealed that O9 in C1, C2, and C3 compounds are more likely to donate electrons as nucleophilic (Table 3) (Omer et al. 2024; Azeez et al. 2025).

Table 3.

The Fukui functions (Fk +  = q(N + 1) − q(N), Fk −  = q(N) − q(N − 1), and dual descriptor (Δ F = [Fk +  − Fk −]) for C1, C2, and C3 optimized structures

C1 C2 C3
Atoms Inline graphic Inline graphic Δ f Atoms Inline graphic Inline graphic Δ f Atoms Inline graphic Inline graphic Δ f
C (1) 0.054 0.031 − 0.023 C (1) 0.045 0.029 − 0.016 C (1) 0.053 0.031 − 0.022
C (2) 0.026 0.020 − 0.006 C (2) 0.012 0.025 0.013 C (2) 0.026 0.019 − 0.007
N (3) 0.050 0.037 − 0.013 N (3) 0.049 0.030 − 0.019 N (3) 0.049 0.038 − 0.011
C (4) 0.029 0.035 0.006 C (4) 0.017 0.038 0.021 C (4) 0.028 0.035 0.007
N (5) 0.011 0.000 − 0.011 N (5) 0.011 − 0.001 − 0.012 N (5) 0.011 0.000 − 0.011
C (6) − 0.012 − 0.011 0.001 C (6) − 0.012 − 0.010 0.002 C (6) − 0.011 − 0.011 0.000
C (7) 0.015 0.023 0.008 C (7) 0.010 0.027 0.017 C (7) 0.015 0.023 0.008
C (8) − 0.004 − 0.007 − 0.003 C (8) − 0.004 − 0.008 − 0.004 C (8) − 0.004 − 0.007 − 0.003
O (9) 0.081 0.045 − 0.036 O (9) 0.054 0.049 − 0.005 O (9) 0.080 0.044 − 0.036
C (10) − 0.002 − 0.007 − 0.005 C (10) − 0.004 − 0.008 − 0.004 C (10) − 0.002 − 0.007 − 0.005
C (11) − 0.008 − 0.016 − 0.008 C (11) − 0.009 − 0.016 − 0.007 C (11) − 0.008 − 0.016 − 0.008
C (12) − 0.001 0.001 0.002 C (12) − 0.001 0.001 0.002 C (12) − 0.001 0.001 0.002
C (13) 0.003 0.002 − 0.001 C (13) 0.002 0.002 0.000 C (13) 0.003 0.002 − 0.001
C (14) 0.011 0.011 0.000 C (14) 0.008 0.012 0.004 C (14) 0.011 0.010 − 0.001
C (15) 0.007 0.004 − 0.003 C (15) 0.004 0.003 − 0.001 C (15) 0.007 0.004 − 0.003
C (16) 0.002 0.006 0.004 C (16) 0.001 0.007 0.006 C (16) 0.002 0.006 0.004
C (17) − 0.006 − 0.009 − 0.003 C (17) − 0.006 − 0.009 − 0.003 C (17) − 0.006 − 0.009 − 0.003
C (18) 0.005 0.004 − 0.001 C (18) 0.004 0.004 0.000 C (18) 0.005 0.004 − 0.001
C (19) 0.009 0.007 − 0.002 C (19) 0.007 0.006 − 0.001 C (19) 0.009 0.007 − 0.002
C (20) 0.007 0.005 − 0.002 C (20) 0.005 0.004 − 0.001 C (20) 0.006 0.004 − 0.002
C (21) − 0.002 − 0.004 − 0.002 C (21) − 0.002 − 0.004 − 0.002 C (21) − 0.002 − 0.004 − 0.002
C (22) 0.007 0.005 − 0.002 C (22) 0.004 0.005 0.001 C (22) 0.007 0.005 − 0.002
C (23) 0.005 0.003 − 0.002 C (23) 0.003 0.003 0.000 C (23) 0.005 0.003 − 0.002
C (24) 0.017 0.014 − 0.003 C (24) 0.011 0.015 0.004 C (24) 0.017 0.013 − 0.004
C (25) 0.007 0.004 − 0.003 C (25) 0.005 0.004 − 0.001 C (25) 0.007 0.004 − 0.003
C (26) 0.007 0.004 − 0.003 C (26) 0.003 0.006 0.003 C (26) 0.007 0.004 − 0.003
O (27) 0.025 0.011 − 0.014 O (27) 0.019 0.011 − 0.008 O (27) 0.025 0.011 − 0.014
C (28) 0.002 0.024 0.022 C (28) 0.027 0.014 − 0.013 C (28) 0.003 0.025 0.022
C (29) 0.011 0.047 0.036 C (29) 0.012 0.044 0.032 C (29) 0.011 0.047 0.036
O (30) 0.036 0.070 0.034 O (30) 0.040 0.065 0.025 O (30) 0.036 0.070 0.034
C (31) 0.040 0.064 0.024 C (31) 0.021 0.065 0.044 C (31) 0.038 0.064 0.026
H (32) 0.029 0.037 0.008 H (32) 0.032 0.036 0.004 H (32) 0.029 0.038 0.009
C (33) − 0.002 − 0.009 − 0.007 C (33) 0.012 − 0.012 − 0.024 C (33) − 0.001 − 0.009 − 0.008
C (34) 0.012 0.024 0.012 C (34) 0.014 0.019 0.005 C (34) 0.012 0.025 0.013
C (35) 0.007 0.007 0.000 C (35) 0.025 0.016 − 0.009 C (35) 0.012 0.012 0.000
C (36) 0.022 0.034 0.012 C (36) 0.035 0.036 0.001 C (36) 0.024 0.038 0.014
C (37) 0.007 0.008 0.001 C (37) 0.013 0.006 − 0.007 C (37) 0.013 0.014 0.001
C (38) 0.014 0.019 0.005 C (38) 0.024 0.024 0.000 C (38) 0.014 0.019 0.005
H (39) 0.032 0.023 − 0.009 O (39) 0.036 0.021 − 0.015 H (39) 0.031 0.023 − 0.008
H (40) 0.000 − 0.002 − 0.002 C (40) − 0.021 − 0.017 0.004 H (40) 0.001 − 0.001 − 0.002
H (41) 0.025 0.019 − 0.006 O (41) 0.029 0.012 − 0.017 H (41) 0.024 0.019 − 0.005
H (42) 0.032 0.027 − 0.005 C (42) − 0.020 − 0.015 0.005 H (42) 0.031 0.026 − 0.005
H (43) 0.031 0.026 − 0.005 H (43) 0.026 0.022 − 0.004 H (43) 0.030 0.025 − 0.005
H (44) 0.020 0.017 − 0.003 H (44) − 0.003 0.001 0.004 H (44) 0.020 0.017 − 0.003
H (45) − 0.002 − 0.004 − 0.002 H (45) 0.018 0.020 0.002 H (45) − 0.002 − 0.004 − 0.002
H (46) 0.023 0.020 − 0.003 H (46) 0.024 0.028 0.004 H (46) 0.023 0.020 − 0.003
H (47) 0.029 0.026 − 0.003 H (47) 0.024 0.027 0.003 H (47) 0.029 0.026 − 0.003
H (48) 0.028 0.024 − 0.004 H (48) 0.015 0.018 0.003 H (48) 0.028 0.024 − 0.004
H (49) 0.015 0.012 − 0.003 H (49) − 0.005 − 0.004 0.001 H (49) 0.014 0.012 − 0.002
H (50) 0.011 0.009 − 0.002 H (50) 0.019 0.019 0.000 H (50) 0.011 0.009 − 0.002
H (51) 0.030 0.025 − 0.005 H (51) 0.025 0.026 0.001 H (51) 0.029 0.024 − 0.005
H (52) 0.036 0.030 − 0.006 H (52) 0.024 0.024 0.000 H (52) 0.035 0.029 − 0.006
H (53) 0.032 0.025 − 0.007 H (53) 0.012 0.012 0.000 H (53) 0.032 0.025 − 0.007
H (54) 0.018 0.010 − 0.008 H (54) 0.007 0.009 0.002 H (54) 0.018 0.010 − 0.008
H (55) 0.005 0.019 0.014 H (55) 0.023 0.025 0.002 H (55) 0.006 0.019 0.013
H (56) 0.025 0.036 0.011 H (56) 0.027 0.030 0.003 H (56) 0.025 0.035 0.010
H (57) 0.033 0.044 0.011 H (57) 0.023 0.026 0.003 H (57) 0.031 0.039 0.008
H (58) 0.031 0.040 0.009 H (58) 0.008 0.012 0.004 H (58) 0.024 0.032 0.008
H (59) 0.024 0.032 0.008 H (59) 0.032 0.027 − 0.005 F (59) 0.029 0.034 0.005
H (60) 0.031 0.026 − 0.005
H (61) 0.020 0.014 − 0.006
H (62) 0.029 0.025 − 0.004
H (63) 0.022 0.015 − 0.007
H (64) 0.022 0.015 − 0.007
H (65) 0.029 0.022 − 0.007
H (66) 0.018 0.014 − 0.004
H (67) 0.017 0.009 − 0.008
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Topological parameters

The Quantum Theory of Atoms in Molecules (QTAIM) provides significant insights into the structure of mentioned title compounds C1, C2, and C3 and the interactions between atoms, both of which are necessary for comprehending the prevention of potential corrosion. The adsorption sites and compounds stability may be assessed by considering the electron density ρ(r), the Laplacian of the electron density (∇2ρ(r), the overall energy H(r), the local electron potential V(r), and the bond energy EHB = V(r)/2. Effective adsorption on metal surfaces is made easier by the presence of strong intramolecular hydrogen bonding (H-bond) (Table 4) (Tang and Zhu 2021; Jumabaev et al. 2023; Rozas et al. 2000).

Table 4.

Topological parameters (all in a.u) at the bond critical point (BCP) of title compound [Electron density (ρ (r)), Laplacian of electron density (Inline graphic, and Ellipticity ( Inline graphic], The units of V, G, and H are in au, and Energy (kcal/mol)

Bonds ρ (r) Inline graphic ɛ V G H E
C1
C16—H44 0.288 − 1.058 0.012 − 0.343 0.039 − 0.304 107.627
C7—H50 0.009 0.034 0.474 − 0.004 0.007 0.002 1.405
C12—H40 0.288 − 1.047 0.013 − 0.344 0.041 − 0.303 107.954
C14—H42 0.285 − 1.025 0.013 − 0.339 0.041 − 0.298 106.353
C15—H43 0.285 − 1.021 0.017 − 0.339 0.042 − 0.297 106.347
C19—H47 0.285 − 1.021 0.016 − 0.339 0.042 − 0.297 106.368
C17—H45 0.283 −  −  −  0.043 − 0.295 105.919
C21—H49 0.286 − 1.032 0.015 − 0.340 0.041 − 0.299 106.660
C20—H48 0.285 − 1.024 0.016 − 0.339 0.042 − 0.298 106.438
C23—H51 0.285 − .021 0.017 − 0.339 0.042 − 0.297 106.433
C24—H52 0.285 − 1.021 0.015 − 0.339 0.042 − 0.297 106.345
C25—H53 0.284 − 1.019 0.017 − 0.339 0.042 − 0.297 106.305
C31—H32 0.285 − 1.039 0.017 − 0.340 0.040 − 0.300 106.830
O27—H55 0.013 0.047 0.050 − 0.010 0.011 0.001 3.011
C34—H55 0.289 − 1.069 0.016 − 0.347 0.040 − 0.307 108.912
C36—H57 0.285 − 1.026 0.014 − 0.339 0.041 − 0.298 106.491
C37—H58 0.285 − 1.024 0.016 − 0.339 0.042 − 0.298 106.455
C38—H59 0.284 − 1.019 0.016 − 0.339 0.042 − 0.297 106.307
C6—H39 0.289 − 1.067 0.029 − 0.341 0.037 − 0.304 107.142
C13—H41 0.285 − 1.021 0.017 − 0.339 0.042 − 0.297 106.435
C18—H46 0.284 − 1.019 0.017 − 0.339 0.042 − 0.297 106.334
C22—H50 0.286 − 1.034 0.017 − 0.342 0.042 − 0.300 107.364
C26—H54 0.287 − 1.048 0.015 − 0.343 0.040 − 0.302 107.570
C35—H56 0.285 − 1.026 0.016 − 0.339 0.042 − 0.298 106.492
C2
C7—H54 0.009 0.034 0.497 − 0.004 0.007 0.002 1.398
C12—H44 0.288 − 1.048 0.013 − 0.344 0.041 − 0.303 107.980
C14—H46 0.285 − 1.024 0.013 − 0.339 0.041 − 0.298 106.346
C16—H48 0.288 − 1.058 0.012 − 0.343 0.039 − 0.304 107.630
C15—H47 0.285 − 1.021 0.017 − 0.339 0.042 − 0.297 106.343
C17—H49 0.283 − 1.008 0.017 − 0.338 0.043 − 0.295 105.928
C23—H55 0.285 − 1.021 0.017 − 0.339 0.042 − 0.297 106.423
C24—H56 0.285 − 1.021 0.015 − 0.339 0.042 − 0.297 106.337
C25—H57 0.284 − 1.019 0.017 − 0.339 0.042 − 0.297 106.304
C31—H32 0.286 − 1.040 0.017 − 0.341 0.040 − 0.300 106.872
O27—H61 0.013 0.047 0.053 − 0.010 0.011 0.001 2.981
C38—H61 0.289 − 1.070 0.018 − 0.347 0.040 − 0.307 108.975
C21—H53 0.286 − 1.032 0.015 − 0.340 0.041 − 0.299 106.669
C13—H45 0.285 − 1.021 0.017 − 0.339 0.042 − 0.297 106.432
C18—H50 0.284 − 1.019 0.017 − 0.339 0.042 − 0.297 106.324
C19—H51 0.285 − 1.021 0.016 − 0.339 0.042 − 0.297 106.357
C20—H52 0.285 − 1.023 0.016 − 0.339 0.042 − 0.298 106.431
C22—H54 0.286 − 1.035 0.017 − 0.342 0.042 − 0.300 107.367
C26—H58 0.287 − 1.048 0.015 − 0.343 0.040 − 0.302 107.569
C34—H59 0.284 − 1.023 0.019 − 0.338 0.041 − 0.297 106.202
O41—H63 0.013 0.044 0.233 − 0.009 0.010 0.001 2.896
C37—H60 0.285 − 1.030 0.019 − 0.339 0.041 − 0.298 106.411
C40—H62 0.287 − 1.048 0.047 − 0.339 0.038 − 0.300 106.298
C40—H63 0.287 − 1.052 0.043 − 0.339 0.038 − 0.301 106.341
C40—H64 0.283 − 1.012 0.047 − 0.332 0.039 − 0.292 104.058
C42—H65 0.287 − 1.047 0.046 − 0.338 0.038 − 0.300 106.196
O39—H66 0.011 0.039 0.316 − 0.008 0.009 0.001 2.397
C42—H66 0.286 − 1.041 0.044 − 0.337 0.038 − 0.298 105.648
C42—H67 0.283 − 1.010 0.046 − 0.331 0.039 − 0.292 103.941
C3
C16—H44 0.288 − 1.058 0.012 − 0.343 0.039 − 0.304 107.594
C7—H50 0.009 0.035 0.303 − 0.005 0.007 0.002 1.423
C12—H40 0.287 − 1.047 0.013 − 0.344 0.041 − 0.303 107.897
C14—H42 0.285 − 1.026 0.013 − 0.339 0.041 − 0.298 106.385
C15—H43 0.285 − 1.022 0.017 − 0.339 0.042 − 0.297 106.374
C19—H47 0.285 − 1.022 0.016 − 0.339 0.042 − 0.297 106.381
C17—H45 0.283 − 1.007 0.017 − 0.337 0.043 − 0.295 105.875
C21—H49 0.286 − 1.032 0.015 − 0.340 0.041 − 0.299 106.661
C20—H48 0.285 − 1.024 0.016 − 0.339 0.042 − 0.298 106.449
C23—H51 0.284 − 1.028 0.021 − 0.339 0.041 − 0.298 106.495
C25—H52 0.284 − 1.025 0.021 − 0.339 0.041 − 0.298 106.377
C31—H32 0.286 − 1.040 0.017 − 0.341 0.040 − 0.300 106.832
O27—H54 0.013 0.047 0.051 − 0.010 0.011 0.001 2.998
C34—H54 0.289 − 1.068 0.016 − 0.347 0.040 − 0.307 108.899
C36—H56 0.285 − 1.027 0.014 − 0.339 0.041 − 0.298 106.503
C37—H57 0.285 − 1.024 0.016 − 0.339 0.042 − 0.298 106.469
C38—H58 0.285 − 1.019 0.016 − 0.339 0.042 − 0.297 106.325
C6—H39 0.289 − 1.066 0.029 − 0.341 0.037 − 0.304 107.127
C13—H41 0.285 − 1.022 0.017 − 0.339 0.042 − 0.297 106.445
C18—H46 0.284 − 1.019 0.017 − 0.339 0.042 − 0.297 106.340
C22—H50 0.287 − 1.045 0.016 − 0.343 0.041 − 0.302 107.626
C26—H53 0.288 − 1.059 0.014 − 0.344 0.040 − 0.304 107.874
C35—H55 0.285 − 1.026 0.016 − 0.339 0.041 − 0.298 106.502
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Based on the atoms in molecules (AIM) quantum theory, when (∇2ρ > 0 and H > 0 it reveals a weak covalent interaction bond (strong electrostatic bond). Also, (∇2ρ < 0 and H < 0 values denote a strong covalent bond. While the H < 0 and (∇2ρ > 0 denote the medium strength or partially covalent interaction bond. The data in Table 4 revealed compounds with weak covalent interaction bond (strong electrostatic bond): C7—H50, O27—H55 in C1, O27—H61, O41—H63, O39—H66 in C2, and C7—H50, O27—H54 in C3 bond energies. The results of this study indicate that hydrogen bonding has a significant influence on the overall molecular stability and has the potential to reduce potential corrosion. Finally, almost another kind of bond is strong covalent bond interactions as seen in Table 4 (Louis et al. 2022). The bond ellipticity (ε), is a valuable parameter useful to predict the structure stability of interactions. High values of ε (a.u.) (ε > 1) denote structural instability, and lower values of ε denote structural stability of the interactions (ε < 1). According to evaluate our investigation, the ellipticity (ε) values for our compounds C1, C2, and C3 are mostly structural stability (Table 4) (Louis et al. 2022; Ahmed et al. 2025).

Monte Carlo (MC) simulations

With crucial indicators like adsorption energy, total energy, binding energy, and deformation energy indicating their potential as corrosion inhibitors (Othman et al. 2025), Monte Carlo (MC) simulations provide a comprehensive understanding of the adsorption prosperity and stability of the investigated compounds on Fe (110), Cu (111) on the metal surfaces mentioned title compounds C1, C2, and C3 (Fig. 6). Compound C2 has the greatest adsorption energy (Fe; − 234.761 kcal/mol), (Cu; − 120.712 kcal/mol) and strong metal binding energy (Fe, 234.761 kcal/mol), and (Cu; 120.712 kcal/mol). According to this demonstration, the higher desorption energy (Table 5), are agree smaller HOMO–LUMO energy gap in (Table 2) characterized by strong C–O–C, and C–O fragments (as cited above quantum chemical parameters in), indicating increased reactivity and electron donation.

Fig. 6.

Fig. 6

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The most stable low-energy configurations were calculated using the Monte Carlo simulation for the adsorption of the studied compounds on the Fe (110) and Cu (111) surfaces

Table 5.

The outputs and descriptors (kcal/mol) calculated using the Monte Carlo simulation and binding energies for adsorption of the studied compounds on the Fe (110) surface

Compound Total energy Adsorption energy Rigid adsorption Deformation energy dEad/dNi Binding energy
Fe (110)
C1 − 303.247 − 203.360 − 234.077 30.717 − 203.360 203.360
C2 − 309.134 − 234.761 − 266.237 31.477 − 234.761 234.761
C3 − 305.617 − 226.992 − 235.325 8.332 − 226.992 226.992
Cu (111)
C1 − 187.028 − 87.140 − 96.379 9.238 − 87.140 87.140
C2 − 195.085 − 120.712 − 128.163 7.451 − 120.712 120.712
C3 − 190.115 − 88.156 − 101.409 13.253 − 88.156 88.156
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Toxicity Model Report

Online services were employed to predict possible biological and medical activities of C(1–3). Compounds C(1–3) belong to the 2nd class of toxicity (Table 6). Compound C1 was predicted to be bbbtoxic, and C2 was predicted to be immunotoxic, and C3 was predicted to be neuro and bbbtoxic (Fig. 7).

Table 6.

Oral toxicity prediction results

C1 C2 C3
Predicted LD50 (mg/kg) 68 68 68
Predicted Toxicity Class 2 2 2
Average similarity (%) 31.13 32.42 31.03
Prediction accuracy (%) 23 23 23
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Fig. 7.

Fig. 7

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Toxicity Model Report for the studied compounds: Molecule C1 (left), molecule C2 (middle), and molecule C3 (right). The colors represent inactive and active toxicity following the probability score ranging from 0 to 1

The radar of bioavailability revealed nearly the same properties for C(1–3) and all the studied compounds are prominent in polarity, and flexibility, and are poor in instauration, lipophility, size, and insolubility (Fig. 8). The BOILED-Egg method revealed C1 and C3 can potentially penetrate the blood–brain barrier and can be absorbed by the gastrointestinal tract (Fig. 8).

Fig. 8.

Fig. 8

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(left) The radar of bioavailability for molecules C1 (red), C2 (green), and C3 (yellow). (right) the BOILED Egg model for C(1–3) (BBB = blood–brain barrier, HIA = gastrointestinal absorption, PGP +  = effluated from the central nervous system by the P-glycoprotein, PGP– = not effluated from the central nervous system by the Pglycoprotein)

In-vitro observation confirmed by molecular docking and dynamics simulations studies.

Docking of selective ligands (C1, C2, and C3 compounds) was performed to estimate the specificity and affinity of drug-receptor interactions (Kahksha et al. 2023). The amino acids present in and surrounding the active site of the binding domain of the receptor play a critical role in these interactions (Conti et al. 2011). The docking results in (COX-2), molecule C1 has the strongest binding affinity (XP GScore = − 10.137), followed by Molecule C3 (COX-2, − 8.632) and Molecule C2 (COX-2, − 8.420), with Molecule C1 exhibiting the best binding stability due to a π⋅⋅⋅π T-shaped interactions (TYR404 and HIE388) (Table 7, Fig. 9). In NF-κB signaling, Molecule 2 shows stronger hydrogen bonding (− 0.972), enhancing its interaction. The 3D and 2D visualizations confirm key binding modes, including π-π stacking, and hydrogen bonding, which explain the observed docking scores (Table 7, Fig. 9). Overall, Molecule C2 emerges as the most promising candidate for NF-κB inhibition, while Molecule C1 demonstrates the highest affinity for COX-2.

Table 7.

Scores of ligand efficiency for the studied compounds upon docking with the listed proteins

Protein Molecules XP GScore Glide emodel H-Bond PhobEn LipophilicEvdw Electro

Human Cyclooxygenase-2 (COX-2)

(PDB code 5F19)

 C1 − 10.137 − 82.724 0.000 − 1.807 − 8.416 − 0.063
C2 − 8.420 − 77.337 0.000 − 1.150 − 7.451 0.031
C3 − 8.632 − 64.027 0.000 − 1.747 − 6.833 − 0.074

A20 ZnF4

NF-κB signaling

(PDB code 3OJ4)

 C1 − 2.181 − 56.875 − 0.137 0.000 − 3.577 − 0.202
C2 − 4.743 − 51.808 − 0.972 0.000 − 5.281 0.008
C3 − 4.160 − 70.269 − 0.257 0.000 − 5.305 − 0.259
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Fig. 9.

Fig. 9.

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3D and 2D views on complexes COX-2–1 (left), COX-2– 2 (middle) and COX-2– 3 (right)

The Root Mean Square Deviation (RMSD) analysis in the simulation assesses the stability of both the protein (COX-2) and the ligand (Molecule C1) over time (Kuzmanic and Zagrovic 2010). Fluctuations in RMSD indicate conformational changes, with higher deviations suggesting structural instability. The ligand's RMSD specifically reflects its binding stability; if significantly higher than the protein's, it may indicate weak binding or ligand diffusion from the active site. In the COX-2–1 complex, the protein backbone remains highly stable between 2 and 12 ns, after which conformational changes occur up to 50 ns. Throughout the simulation, RMSD values remain mostly below 3 Å (Fig. 10), indicating moderate structural fluctuations. The ligand (Molecule C1) demonstrates relative stability compared to the protein, with RMSD values ranging between 2.5 Å and 3 Å, suggesting a well-maintained interaction. Additionally, its internal structure remains consistent, reinforcing a stable protein–ligand interaction with some flexibility in binding poses. The Root Mean Square Fluctuation (RMSF) analysis provides insights into the local flexibility of the protein chain (Narwani et al. 2019). In this simulation, COX-2 remained relatively stable, with flexibility primarily localized in loop regions, while the ligand maintained consistent interactions, confirming its binding stability. The COX-2–1 complex exhibits low fluctuations, with most residues showing RMSF values below 1.5 Å, indicating a predominantly rigid structure. However, increased flexibility is observed around residue 150 near the C-terminal end, particularly in loop regions, as highlighted by the background shading. Ligand interactions, represented by green bars, are concentrated around residues 170 and 360–380, suggesting that Molecule C1 engages with multiple structural components, influencing both flexible and rigid regions of the protein (Fig. 10).

Fig. 10.

Fig. 10

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RMSD and RMSF analysis of COX-2 with molecule 1 from a 50 ns molecular dynamics simulation. RMSD (top) and RMSF (bottom) analysis, secondary structure elements are shaded: red for alpha-helices, blue for beta-strands, and white for loop or coil regions. Green bars indicate residues interacting with the ligand

For the COX-2–1 complex, notable hydrophobic contributions come from residues like HIS207, PHE395, TYR404, and VAL447, while hydrogen bonds are observed with residues such as HIS388. Minimal water bridge interactions involve residue GLN203, VAL444, and LYS446 (Fig. 11). Such detailed interaction analysis is pivotal in drug design, enzyme catalysis, and cellular signaling, highlighting the significance of protein–ligand interactions in biochemistry and pharmaceutical research (Roche et al. 2015).

Fig. 11.

Fig. 11

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Interaction analysis of the COX-2–1 complex over a 50 ns simulation trajectory: (top) 2D interaction diagram illustrating molecule C1 interactions with amino acid residues and water molecules. (bottom) interaction fraction plot depicting the contributions of H-bonds, hydrophobic interactions, and water bridges

The ligand torsion plot provides insights into the conformational behavior of the ligand's rotatable bonds throughout a 50 ns molecular dynamics simulation. The 2D schematic of the ligand highlights rotatable bonds in different colors, corresponding to their respective torsion analysis plots. The radial (dial) plots illustrate the evolution of each torsion over time, where a compact cluster of points indicates a stable conformation, while a wider spread suggests flexibility. The histograms, accompanied by torsional potential curves, depict the probability distribution of each torsion angle and its associated energetic favorability (Yakobi et al. 2024; Sasidharan et al. 2023; Amin et al. 2025). Most torsions, such as the light blue, purple, and green bonds, exhibit stable, low-energy conformations, indicating that the ligand maintains a preferred structure with minimal strain. The red torsion shows moderate flexibility, while the orange torsion displays bimodal behavior, suggesting it alternates between two energetically favorable states (Fig. 12). Overall, the ligand adopts a mostly stable conformation with limited flexibility, ensuring compatibility with its protein-binding environment and minimizing conformational strain.

Fig. 12.

Fig. 12

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Torsional analysis of ligand conformations throughout a 50 ns molecular dynamics simulation

The figure presents a comprehensive molecular dynamics (MD) analysis of Molecule C1, focusing on its structural stability, compactness, and solvent interaction over a simulation period (Fig. 13). The Root Mean Square Deviation (RMSD) plot shows that the ligand maintains a stable conformation with minor fluctuations, indicating minimal structural deviation from the reference state. The Radius of Gyration (rGyr) remains consistent, reflecting the ligand's compact nature without significant unfolding. Notably, no intramolecular hydrogen bonds (intraHB) were detected, suggesting that the ligand does not exhibit internal hydrogen bonding, possibly due to steric hindrance or an unfavorable geometric arrangement. The Molecular Surface Area (MolSA) remains relatively stable, indicating that the overall molecular shape does not change significantly during the simulation. The Solvent Accessible Surface Area (SASA) and Polar Surface Area (PSA) plots reveal moderate solvent exposure, suggesting a balance between hydrophobic and polar interactions. The histogram distributions on the right provide additional insights into the frequency of observed values for each parameter, reinforcing the ligand's stable behavior over time (Fig. 13). Overall, the results indicate that Molecule C1 exhibits a structurally stable conformation in solution, with moderate solvent accessibility and no internal hydrogen bonding.

Fig. 13.

Fig. 13

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Structural stability and solvent accessibility of the molecule 1 during a 50 ns molecular dynamics simulation

Conclusion

In this study, we successfully synthesized a new series of bicyclic benzylidene oxazole pyrimidine derivatives—(Z)-6-benzoyl-2-benzylidene-5,7-diphenyl-5H-oxazolo[3,2-a]pyrimidin-3(2H)-one (C1), (Z)-6-benzoyl-2-(3,4-dimethoxybenzylidene)-5,7-diphenyl-5H-oxazolo[3,2-a]pyrimidin-3(2H)-one (C2), and (Z)-6-benzoyl-2-(4-fluorobenzylidene)-5,7-diphenyl-5H-oxazolo[3,2-a]pyrimidin-3(2H)-one (C3)—via a one-pot reaction involving Hantzsch heterocyclization and Knoevenagel condensation. This efficient single-step synthesis utilized bromoacetic acid and various aryl aldehydes within a single reaction vessel. The structures of the synthesized compounds were confirmed through FTIR, 1H-NMR, and 13C-NMR spectroscopy. To explore their electronic and adsorption properties, quantum chemical calculations were performed using the B3LYP/6-311G + (d,p) method, revealing key molecular characteristics such as HOMO–LUMO energy levels, molecular electrostatic potential (MEP) surfaces, Fukui functions, and topological parameters. Monte Carlo simulations further provided insights into the adsorption behavior of C(1–3) on Fe(110) and Cu(111) surfaces, with C2 demonstrating the highest adsorption energy and strongest binding affinity, followed by C3 and C1.

The pharmacological potential of these compounds was systematically evaluated through drug-likeness predictions, computational toxicity assessments, molecular docking, and molecular dynamics (MD) simulations. Toxicity modeling identified distinct profiles, with C1 exhibiting blood-brain barrier (BBB) toxicity, C2 displaying immunotoxicity, and C3 showing both neurotoxicity and BBB toxicity. Docking and MD simulations highlighted C1 as a strong COX-2 inhibitor, demonstrating stable binding through π-π interactions and minimal structural deviations. Meanwhile, C2 emerged as a promising NF-κB inhibitor due to its enhanced hydrogen bonding interactions. Bioavailability analysis further indicated the suitability of these compounds for drug development, providing a foundation for future optimization. Overall, this study enhances our understanding of ligand-receptor interactions and establishes a framework for the potential therapeutic applications of C(1–3). These findings lay the groundwork for further experimental validation and refinement in drug discovery.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary Material 1 (2.8MB, docx)

Author contributions

Abdalla Ali Amin: Conceptualization, Methodology, Formal analysis, Writing – Original Draft.Ali Rasw Hamad: Data Curation, Software, Visualization, Writing – Review & Editing.Yousif Hussein Azeez: Investigation, Validation, Resources.Karzan Mahmood Ahmed: Data Curation, Software, Methodology.Rebaz Obaid Kareem: Visualization, Formal Analysis, Writing – Review & Editing.Rzgar Faruq Rashid: Supervision, Project Administration, Funding Acquisition.Khdir Ahmed Othman: Investigation, Resources, Validation.Rebaz Anwar Omer: Conceptualization, Supervision, Writing – Review & Editing, Project Administration, Corresponding Author.

Funding

No funding was received.

Data availability

No datasets were generated or analysed during the current study.

Declarations

Conflict of interest

The authors declare no competing interests.

Footnotes

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Supplementary Materials

Supplementary Material 1 (2.8MB, docx)

Data Availability Statement

No datasets were generated or analysed during the current study.

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