Computational insights into anti-Zika quinazoline compounds: Density functional theory analysis, spectral properties, and molecular dynamics simulations European Journal of Chemistry 16 (2) (2025) 207-221 European Journal of Chemistry ISSN 2153-2249 (Print) / ISSN 2153-2257 (Online) – Copyright © 2025 The Authors – Atlanta Publishing House LLC – Printed in the USA. This work is published and licensed by Atlanta Publishing House LLC – CC BY NC – Some Rights Reserved. https://dx.doi.org/10.5155/eurjchem.16.2.207-221.2654 European Journal of Chemistry View Journal Online View Article Online Computational insights into anti-Zika quinazoline compounds: Density functional theory analysis, spectral properties, and molecular dynamics simulations Akhilesh Kumar Rao and Umesh Yadava * Department of Physics, Deen Dayal Upadhyaya Gorakhpur University, Gorakhpur, Uttar Pradesh 273009, India * Corresponding author at: Department of Physics, Deen Dayal Upadhyaya Gorakhpur University, Gorakhpur, Uttar Pradesh 273009, India. e-mail: umesh.phy@ddugu.ac.in (U. Yadava). 10.5155/eurjchem.16.2.207-221.2654 Received: 29 January 2025 Received in revised form: 15 March 2025 Accepted: 9 April 2025 Published online: 30 June 2025 Printed: 30 June 2025 Zika disease, caused by the Zika virus (ZIKV), a mosquito-borne flavivirus, is a leading factor in the emergence and reemergence of serious illnesses. The compounds N-[4-((3-bromo-4- fluorophenyl)amino]-7-methoxyquinazolin-6-yl)-2-butynamide (1), N-[4-((4'-6-difluoro- [1,1'-biphenyl]-3-yl)amino)quinazolin-6-yl]-2-butynamide (2), and N-[4-((3-fluorophenyl) amino)-7-methoxyquinazolin-6-yl]but-2-ynamide (3) have been reported to exhibit anti- ZIKV activity. In this study, we performed geometry optimizations and structural analysis of these compounds using the B3LYP/6-31G** method. On the basis of the optimized geometries, the electronic properties, infrared (IR) assignments, and thermodynamic parameters were evaluated. The results indicate that these molecules maintain robust conformations in their core rings, with notable variations in the conformations of their side chains and functional groups. It was also observed that the rotational temperatures increase as the rotational constants decrease. The evaluated small HOMO-LUMO energy gaps and molecular electrostatic potential maps suggest high chemical reactivity, indicating ease of intramolecular charge transfer within the molecules. Infrared assignments for normal mode vibrations in the range of 400 to 3800 cm-1 were carried out successfully and compared for all three compounds. In addition, to study the structure function, the docking of these molecules along with the control molecule afatinib was performed with the methyltransferase enzyme of the Zika virus. The top-ranked docked complexes were subjected to a molecular dynamics simulation run of 200 ns duration. These theoretical calculations help us to understand how these compounds can interact with enzymes that are involved in the metabolic pathways of the Zika virus. DFT Flavones Anti-ZIKV HOMO-LUMO MD simulation Molecular docking Cite this: Eur. J. Chem. 2025, 16(2), 207-221 Journal website: www.eurjchem.com 1. Introduction Zika virus (ZIKV), a member of the Flavivirus genus, is transmitted through the bites of specific Aedes mosquito species, including Aedes luteocephalus, Aedes africanus, Aedes aegypti, and Aedes hensilli [1]. ZIKV is the main cause of new and re-emerging serious diseases that affect people all over the world [2]. It was first isolated from rhesus monkeys in 1947 [3]. Subsequently, serological evaluations were performed on human serum samples in Uganda, revealing the presence of virus-neutralizing antibodies. It was the first instance of evidence to point to human infection with the Zika virus [4]. Symptoms of a ZIKV infection often include mild fever, conjunctivitis (red eyes), muscle and joint problems, low white blood cell counts, etc. [5], but a sizable proportion of persons infected with the virus do not show any signs of disease [6,7]. Serological evidence of the human Zika virus was found in Thailand, Malaysia, Philippines, Tanzania, Egypt and South Asia including India, Bangladesh, Pakistan, Vietnam and Indonesia [8,9]. The World Health Organization declared ZIKV a global health emergency in 2016 due to its rapid spread and its connection to neurological diseases [10]. Many body fluids, including the brain and placental tissues of congenitally infected fetuses, contain ZIKA virus RNA [11]. Reverse transcriptase PCR is a very thorough and explicit approach to ZIKA virus diagnosis [12]. For Zika virus-specific RT-PCR, several conventional and real-time assays concentrating on the structural genes prM, E, etc., and nonstructural genes NS1, NS3, NS4, and NS5 etc. have been created [13]. To the best of our knowledge, the FDA has only approved one commercial assay, the Roche Cobas Zika test [14]. Additionally, the FDA has authorized the use of many molecular assays for emergency purposes (EUA), based on RT-PCR [15]. Plasma or serum samples are commonly used for the molecular diagnosis of Zika virus infection in humans within one week of the onset of clinical symptoms [16]. As a result of the longer period of viral shedding in this conveniently obtained collection, urine offers many advantages over serum for the detection of Zika virus RNA. However, exciting studies have shown that pee has a shorter persistence of ZIKV RNA than serum [17]. Currently, there are no particular anti-ZIKV drugs available for the treatment of ZIKV disease in humans. However, there are currently numerous treatments under clinical trials [18]. ABSTRACT RESEARCH ARTICLE KEYWORDS https://dx.doi.org/10.5155/eurjchem.16.2.207-221.2654 https://www.eurjchem.com/ https://dx.doi.org/10.5155/eurjchem.16.2.207-221.2654 mailto:umesh.phy@ddugu.ac.in http://www.eurjchem.com/ https://crossmark.crossref.org/dialog/?doi=10.5155/eurjchem.16.2.207-221.2654&domain=pdf&date_stamp=2025-06-30 208 Rao and Yadava / European Journal of Chemistry 16 (2) (2025) 207-221 2025 – European Journal of Chemistry – CC BY NC – DOI: 10.5155/eurjchem.16.2.207-221.2654 O H N N N HN F F O HN N N O HN F Br O HN N N O HN F O N H N N N O O NH F Cl (a) (b) (c) (d) Scheme 1. Chemical structures of compounds (a) afitinib (N-[4-[(3-chloro-4-fluorophenyl)amino]-7-[[(3S)-tetrahydro-3-furanyl]oxy]-6-quinazolinyl]- 4(dimethylamino)-2-butenamide), (b) N-(4-((4',6-difluoro-[1,1'-biphenyl]-3-yl)amino)quinazolin-6-yl)-2-butynamide (1) (c) N-[4-[(3-bromo-4-fluorophenyl) amino]-7-methoxyquinazolin-6-yl]-2-butynamide (2) and (d) N-(4-((3-fluorophenyl)amino)-7-methoxyquinazolin-6-yl)but-2-ynamide (3). In pursuit of innovative strategies to combat the Zika virus (ZIKV), computational quantum mechanical studies have emerged as a powerful tool that offers unprecedented insight into the molecular intricacies of potential antiviral compounds [19,20]. The urgency to develop effective therapies against ZIKV, known for its association with severe neurological disorders, has led researchers to harness the capabilities of quantum mechanics to unravel the behavior of anti-ZIKV compounds at the atomic and molecular levels [21]. By employing advanced quantum mechanical methodologies, researchers investigate the electronic structure, energetics, and spectroscopic proper- ties of these compounds, aiming to elucidate the underlying mechanisms of their antiviral activity [22]. Experimental observations have demonstrated that tyrosine kinase inhibitors (TKI) exhibit antiflaviviral activities [23]. A series of afatinib derivative tyrosine kinase inhibitor compounds, namely: N-[-4((3-bromo-4-flurophenyl)amino]-7- methoxyquinozolin-6-yl]-2-butynamide] (1), N-(4-((4′-6-di fluro-[1, 1′-biphenyl]-3-yl)amino)quninazdine-6-yl)-2-butyn amide (2), and N-(4((3-flurophenyl) amino)-7-methoxy quinazolil-6-yl)but-2-ynamide (3) have been found endowed with antiviral activities against ZIKV infection in vitro and in vivo [24]. Afatinib is a quinazoline compound that has a 3-chloro-4- fluoroanilino group at the 4-position, a 4-dimethylamino-trans- but-2-enamido group at the 6-position and an (S)-tetrahydro furan-3-yloxy group at the 7-position. The 4-dimethylamino- trans-but-2-enamido group at the 6-position has been replaced by 2-butynamide to obtain compounds 1, 2 and 3. Furthermore, the tetrahydrofuran-3-yloxy group at the 7-position is removed and the 3-chloro-4-fluoroanilino group at the 4-position is replaced by the 4′,6-difluoro-[1,1′-biphenyl]-3-yl group in compound 1. The tetrahydrofuran-3-yloxy group in the 7- position is replaced by the methoxy group in compounds 2 and 3 while the 3-chloro-4-fluoroanilino group at the 4-position is replaced by the 3-fluorophenyl group in compound 2 and by the 3-bromo-4-fluoro-phenyl group in compound 3 (Scheme 1). Compound 3 has shown the highest activity against the ZIKV virus [24]. In the present study, the electronic structure properties, thermodynamic analysis, and IR assignments of compounds 1, 2, and 3 have been investigated and compared. The docking of these molecules and afatinib was performed with the methyltransferase enzyme of the Zika virus, and the best-docked poses were further analyzed using molecular dynamics simulation. Theoretical calculations, such as geometry optimizations, HOMO-LUMO analysis, and infrared (IR) spectral assignments, play a crucial role in the development of anti-Zika virus (ZIKV) drugs by providing fundamental insights into the molecular properties, reactivity, and stability of potential drug candidates. Here is how these calculations contribute: Molecular Stability and Reactivity. Optimized geometries help determine the most stable conformations of anti-ZIKV quinazoline compounds. Understanding the lengths, angles, and electronic distribution of bonds helps predict interactions with viral proteins or nucleic acids. The energies of HOMO (highest occupied Molecular Orbital) and LUMO (lowest unoccupied Molecular Orbital) indicate the electronic properties of the molecule. A lower HOMO-LUMO gap suggests high reactivity, which may enhance binding to viral targets. Frontier molecular orbital distributions help predict sites for electrophilic and nucleophilic attacks, guiding modifications for improved bioactivity. IR spectral analysis provides characteristic vibrational frequencies, aiding in structural confirmation and comparison with experimental data. The identification of functional groups helps assess interactions with biological targets, such as hydrogen bonding with ZIKV proteins. Molecular descriptors from DFT calculations assist in screening for drug similarity and ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) properties. Molecular docking provides a fast and effective way to predict initial drug-enzyme interactions, while MD simulations refine these predictions by considering dynamic and environmental effects. The combined approach enhances the accuracy of drug design, leading to the development of more effective and specific therapeutics. By integrating these computational approaches, researchers can design more effective anti-ZIKV drugs with optimized electronic and structural properties, reducing the need for costly and time- consuming experimental trials. 2. Experimental Optimizations of the compounds in their gaseous states were performed using Becke’s three-parameter Lee-Yang-Parr (B3LYP) hybrid exchange-correlation functional [25] with the 6- 31G** basis set [26], as implemented in the Gaussian03 suite [27]. Rao and Yadava / European Journal of Chemistry 16 (2) (2025) 207-221 209 2025 – European Journal of Chemistry – CC BY NC – DOI: 10.5155/eurjchem.16.2.207-221.2654 Table 1. Optimized bond lengths (Å) of the compounds 1, 2, and 3 obtained using the B3LYP/6-31G** method. Compound 1 Compound 2 Compound 3 Br1-C15 1.929 C1-C2 1.427 C1-C2 1.427 C2-C6 1.412 C1-C3 1.452 C1-C3 1.446 C2-C20 1.427 C1-C4 1.412 C1-C4 1.417 C2-N39 1.383 C2-C6 1.415 C2-C6 1.412 C3-C20 1.445 C2-N45 1.383 C2-N39 1.383 C3-N39 1.339 C3-N43 1.376 C3-N36 1.376 C3-N39 1.376 C3-C44 1.336 C3-N37 1.339 C4-C11 1.381 C4-C11 1.394 C4-C11 1.381 C4-C20 1.417 C4-H31 1.087 C4-H35 1.085 C4-H32 1.085 C5-C7 1.216 C5-H29 1.088 C5-H22 1.095 C5-C24 1.458 C5-H30 1.094 C5-H30 1.088 C6-C12 1.379 C5-H31 1.095 C5-H31 1.094 C6-H29 1.083 C5-O40 1.456 C5-O40 1.456 C7-C8 1.446 C6-C12 1.383 C6-C12 1.383 C8-N46 1.388 C6-H21 1.081 C6-H23 1.081 C8-O47 1.250 C7-C8 1.458 C7-C8 1.458 C9-C13 1.403 C7-H32 1.096 C7-H33 1.096 C9-C17 1.409 C7-H33 1.096 C7-H34 1.096 C9-N43 1.415 C7-H34 1.096 C7-H35 1.096 C10-H27 1.083 C8-C18 1.215 C8-C18 1.215 C10-N44 1.368 C9-C13 1.405 C9-C13 1.407 C10-N45 1.322 C9-C14 1.412 C9-C14 1.410 C11-C12 1.424 C9-N36 1.412 C9-N37 1.412 C11-N46 1.411 C10-H22 1.083 C10-H24 1.083 C12-H30 1.079 C10-N37 1.365 C10-N36 1.366 C13-C14 1.41 C10-N39 1.324 C10-N39 1.324 C13-H28 1.078 C11-C12 1.431 C11-C12 1.431 C14-C15 1.486 C11-N38 1.424 C11-N38 1.423 C14-C16 1.401 C12-O40 1.373 C12-O40 1.373 C15-C19 1.410 C13-C15 1.389 C13-C15 1.392 C15-C20 1.410 C13-H23 1.078 C13-H25 1.078 C16-C18 1.389 C14-C17 1.394 C14-C17 1.392 C16-F26 1.399 C14-H24 1.086 C14-H26 1.086 C17-C18 1.391 C15-C16 1.389 C15-C16 1.388 C17-H42 1.086 C15-F20 1.393 C16-C17 1.390 C18-H41 1.082 C16-C17 1.400 C16-F21 1.385 C19-C21 1.396 C16-H25 1.082 C17-H27 1.082 C19-H40 1.084 C17-H26 1.084 C18-C19 1.447 C20-C23 1.396 C18-C19 1.448 C19-N38 1.386 C20-H39 1.081 C19-N38 1.386 C19-041 1.246 C21-C22 1.390 C19-O41 1.246 H28-N37 1.008 C21-H38 1.083 H27-N36 1.008 H29-N38 1.010 C22-C23 1.390 H28-N38 1.010 C22-F25 1.392 C23-H37 1.083 C24-H34 1.095 C25-H35 1.096 C24-H36 1.096 H32-N43 1.007 H33-N46 1.011 Initial molecular geometries of the compounds were obtained using GaussView software [27], and subsequent optimizations were performed to produce accurate and reliable structures. The absence of imaginary frequencies was ensured for each optimized structure [28]. The optimized parameters were then used for detailed calculations of the electronic structure. Various molecular properties were investigated, including Mulliken charges, dipole moments, molecular electrostatic potential (MEP) surfaces, infrared (IR) frequencies, highest- occupied to lowest unoccupied molecular orbital (HOMO- LUMO) gaps, and thermodynamic properties of the compounds in their ground states. All calculations were carried out at the B3LYP/6-31G** level of theory, ensuring a consistent and rigorous approach. The study provides valuable insights into the structural and electronic characteristics of the compounds and offers a deeper understanding of their behavior in the gaseous phase. The Mulliken charges and dipole moments shed light on the distribution of charge within the molecules and their overall polarity. Molecular electrostatic potential (MEP) surfaces offer a visual representation of the electrostatic potential, providing insights into the reactivity patterns and potential reaction sites. Furthermore, the investigation includes analysis of infrared frequencies, providing information about vibrational modes and potential spectroscopic signatures. The HOMO-LUMO gaps the compounds' electronic stability and reactivity of the compounds. Furthermore, the thermodynamic properties offer a glimpse into the energy landscape, providing crucial data to understand their stability and behavior under different conditions [29]. The combination of the hybrid functional and the 6-31G** basis set ensures a balanced and accurate description of molecular structures and properties. The comprehensive approach adopted in this study improves our understanding of behavior of the compounds and sets the foundation for future investigations in the field of computational chemistry [19,20]. To investigate the structure-function relationship, standard precision (SP) and extra precision (XP) docking [30] of these antiviral molecules, along with afatinib, was performed within the binding site of the methyltransferase (MTase) enzyme of the Zika virus using the Schrödinger suite [31]. Initially, the 3D structure of the protein (PDB ID: 5XWB) was retrieved from the RCSB website and processed using the PRIME and Protein Preparation Wizard tools [31]. The collected ligands were prepared for docking using the LigPrep module with default parameters. The cocrystallized ligand was used as the center of the binding site, and an electrostatic grid map was generated for each type of atom in the ligands. 210 Rao and Yadava / European Journal of Chemistry 16 (2) (2025) 207-221 2025 – European Journal of Chemistry – CC BY NC – DOI: 10.5155/eurjchem.16.2.207-221.2654 (a) (b) (c) Figure 1. Optimized molecular structures along with the atomic numbering schemes of compounds 1 (a), 2 (b), and 3 (c). The prepared ligands were then docked within the active site of the MTase using the SP and XP protocols of the GLIDE docking module [31]. The resulting docked poses were further analyzed. The stability and time evolution of the docked poses were examined using molecular dynamics (MD) simulations of the highest scoring ligand and afatinib over a 200-ns production run using DESMOND-v4.6 [32,33]. The simulation system was set in an orthorhombic box (10×10×10 AÅ buffer) and solvated with a Monte Carlo-equilibrated periodic SPCE water bath [34]. To mimic physiological conditions, 0.15 M salt was added and the system was neutralized by introducing an appropriate number of sodium and chloride counterions. The energy minimization of the complete system, including protein, ligand, ions and solvents, was carried out using a combination of the steepest descent and limited memory Broyden-Fletcher- Goldfarb-Shanno (LBFGS) algorithms, with a maximum of 2000 iteration steps until reaching a gradient threshold of 25 kcal/mol/AÅ , according to the default parameters in Desmond [35]. For MD simulation, an anisotropic diagonal position scaling with a 0.002 ps time step was applied to maintain constant pressure. The temperature was set at 300 K, with a 20 ps NPT reassembly under 1 atm pressure, while all other parameters remained at their default values [36]. Finally, each docked complex underwent a 200 ns simulation under similar conditions. 3. Results and discussion 3.1. Molecular geometry optimizations In Figure 1, we present the optimized structures of compounds 1, 2, and 3, including the corresponding atomic numbering schemes. These structures were calculated using the B3LYP/6-31G** method, providing an accurate representation of the molecular arrangements. Energetic insights into the optimized state of the compounds were obtained through total energy calculations. For compound 1, the total energy was found to be -3773.4235 hartree, while compounds 2 and 3 exhibited total energies of -1418.0981 and -1202.3251 hartree, respectively. These values serve as important indicators of the stability and overall energetics of the compounds studied. The total energy values reported for each compound in its optimized state reflect the energetically favored configurations. Lower total energy values generally correspond to more stable structures, suggesting that compound 1 is probably the most stable among the studied compounds. Further details regarding the geometric parameters of the optimized structures are provided in Tables 1 and 2. These tables offer a comprehensive overview of the key parameters, shedding light on the bond lengths and angles within the molecules. Rao and Yadava / European Journal of Chemistry 16 (2) (2025) 207-221 211 2025 – European Journal of Chemistry – CC BY NC – DOI: 10.5155/eurjchem.16.2.207-221.2654 Table 2. Optimized bond angles (°) of compounds 1, 2, and 3 as obtained using the B3LYP/6-31G** method. Compound 1 Compound 2 Compound 3 C6-C2-C20 119.93 C2-C1-C3 115.58 C2-C1-C3 116.00 C6-C2-N39 118.25 C2-C1-C4 118.96 C2-C1-C4 118.32 C20-C2-N39 121.81 C3-C1-C4 125.44 C3-C1-C4 125.66 C20-C3-N36 120.94 C1-C2-C6 118.98 C1-C2-C6 119.93 C20-C3-N37 119.69 C1-C2-N45 122.18 C1-C2-N39 121.84 N36-C3-N37 119.35 C6-C2-N45 118.82 C6-C2-N39 118.22 C11-C4-C20 121.49 C1-C3-N43 119.51 C1-C3-N36 119.70 C11-C4-H32 C20-C4-H32 116.72 121.75 C1-C3-N44 N43-C3-N44 120.85 119.63 C1-C3-N37 N36-C3-N37 120.87 119.42 C22-C5-H30 110.06 C1-C4-C11 121.07 C1-C4-C11 121.50 C22-C5-H31 110.05 C1-C4-H31 120.95 C1-C4-H35 121.73 C22-C5-O40 111.01 C11-C4-H31 117.97 C11-C4-H35 116.74 H30-C5-H31 110.07 C2-C6-C12 121.60 H29-C5-H30 110.07 H30-C5-O40 104.89 C2-C6-H29 117.25 H29-C5-H31 110.05 H31-C5-O40 110.62 C12-C6-H29 121.14 H29-C5-O40 104.91 C2-C6-C12 120.60 C7-C8-N46 113.18 H30-C5-H31 110.03 C2-C6-H23 116.81 C7-C8-O47 122.77 H30-C5-O40 110.63 C12-C6-H23 122.57 N46-C8-O47 124.04 H31-C5-O40 111.02 C8-C7-H33 111.03 C13-C9-C17 119.36 C2-C6-C12 120.60 C8-C7-H34 111.64 C13-C9-N43 124.30 C2-C6-H21 116.79 C8-C7-H35 111.03 C17-C9-N43 116.32 C12-C6-H21 122.58 H33-C7-H34 107.82 H27-C10-N44 115.56 C8-C7-H32 111.03 H33-C7-H35 107.46 H27-C10-N45 117.72 C8-C7-H33 111.63 H34-C7-H35 107.64 N44-C10-N45 126.71 C8-C7-H34 111.04 C13-C9-H14 119.20 C4-C11-C12 119.77 H32-C7-H33 107.82 C13-C9-N37 124.28 C4-C11-N46 117.66 H32-C7-H34 107.47 C14-C9-N37 116.51 C12-C11-N46 122.56 H33-C7-H34 107.64 H24-C10-N36 115.51 C6-C12-C11 119.59 C13-C9-C14 119.40 H24-C10-N39 117.52 C6-C12-H30 121.48 C13-C9-N36 124.16 N36-C10-N39 126.95 C11-C12-H30 118.92 C14-C9-N36 116.43 C4-C11-C12 119.64 C9-C13-C14 121.38 H22-C10-N37 115.51 C4-C11-N38 120.37 C9-C13-H28 118.39 H22-C10-N39 117.48 C12-C11-N38 119.96 C14-C13-H28 120.21 N37-C10-N39 127.00 C6-C12-C11 119.95 C13-C14-C15 119.94 C4-C11-C12 119.65 C6-C12-O40 124.64 C13-C14-C16 116.99 C4-C11-N38 120.39 C11-C12-O40 115.38 C15-C14-C16 123.05 C12-C11-N38 119.93 C9-C13-C15 119.29 C14-C15-C19 119.80 C6-C12-C11 119.95 C9-C13-H25 119.49 C14-C15-C20 121.86 C6-C12-O40 124.63 C15-C13-H25 121.20 C19-C15-C20 118.32 C11-C12-O40 115.40 C9-C14-C17 120.75 C14-C16-C18 122.89 C9-C13-C15 117.92 C9-C14-H26 119.91 C14-C16-F26 120.00 C9-C13-H23 120.65 C17-C14-H26 119.33 C18-C16-F26 117.09 C15-C13-H23 121.42 Br1-C15-C13 119.62 C9-C17-C18 120.14 C9-C14-C17 120.60 Br1-C15-C16 119.41 C9-C17-H42 120.26 C9-C14-H24 119.70 C13-C15-C16 120.96 C18-C17-H42 119.59 C17-C14-H24 119.69 C15-C16-C17 120.43 C16-C18-C17 119.21 C13-C15-C16 124.06 C15-C16-F21 120.75 C16-C18-H41 119.35 C13-C15-F20 117.59 C17-C16-F21 118.81 C17-C18-H41 121.42 C16-C15-F20 118.33 C14-C17-C16 119.35 C15-C19-C21 121.23 C15-C16-C17 117.32 C14-C17-H27 121.24 C15-C19-H40 119.60 C15-C16-H25 120.42 C16-C17-H27 119.39 C21-C19-H40 119.15 C17-C16-H25 122.24 C18-C19-N38 113.81 C15-C20-C23 120.97 C14-C17-H26 120.67 C18-C19-O41 123.43 C15-C20-H39 119.78 C14-C17-H26 119.56 N38-C19-O41 122.73 C23-C20-H39 119.24 C16-C17-H26 119.75 C2-C20-C3 115.98 C19-C21-C22 118.47 C18-C19-N38 113.82 C2-C20-C4 118.34 C19-C21-H38 121.51 C18-C19-O41 123.39 C3-C20-C4 125.66 C22-C21-H38 120.00 N38-C19-O41 122.77 C3-N36-C10 117.97 C21-C22-C23 122.26 C3-N36-C9 131.05 C3-N37-C9 130.92 C21-C22-F25 118.85 C3-N36-H27 115.57 C3-N37-H28 115.55 C23-C22-F25 118.87 C9-N36-H27 113.36 C9-N37-H28 113.51 C20-C23-C22 118.72 C3-N37-C10 118.00 C11-N38-C19 123.14 C20-C23-H37 121.36 C11-N38-C19 123.15 C11-N38-H29 118.89 C22-C23-H37 119.91 C11-N38-H28 118.88 C19-N38-H29 117.84 C5-C24-H34 111.04 C19-N38-H28 117.83 C2-N39-C10 116.32 C5-C24-H35 111.26 C2-N39-C10 116.26 C5-O40-C12 118.95 C5-C24-H36 111.25 C5-O40-C12 118.91 H34-C24-H35 107.76 H34-C24-H36 107.76 H35-C24-H36 107.57 C3-N43-C9 131.14 C3-N43-H32 115.50 C9-N43-H32 113.34 C3-N44-C10 118.29 C2-N45-C10 116.35 C8-N46-C11 128.85 C8-N46-H33 115.15 C11-N46-H33 115.99 212 Rao and Yadava / European Journal of Chemistry 16 (2) (2025) 207-221 2025 – European Journal of Chemistry – CC BY NC – DOI: 10.5155/eurjchem.16.2.207-221.2654 Table 3. Mulliken atomic charges on each atom of compounds 1, 2, and 3. Compound 1 Compound 2 Compound 3 Atom no Symbol Charge Atom no Symbol Charge Atom no Symbol Charge 1 Br -0.094934 1 C 0.101116 1 C 0.091121 2 C 0.219777 2 C 0.221504 2 C 0.219455 3 C 0.535356 3 C 0.529524 3 C 0.533884 4 C -0.158845 4 C -0.203510 4 C -0.159362 5 C -0.084071 5 C -0.070126 5 C -0.083618 6 C -0.162237 6 C -0.107119 6 C -0.16252 7 C -0.420523 7 C 0.104744 7 C -0.420485 8 C -0.090901 8 C 0.489226 8 C -0.091023 9 C 0.327216 9 C 0.326749 9 C 0.325886 10 C 0.240621 10 C 0.234267 10 C 0.239967 11 C 0.254394 11 C 0.338745 11 C 0.254087 12 C 0.387250 12 C -0.093607 12 C 0.386920 13 C -0.080659 13 C -0.122693 13 C -0.142248 14 C -0.143309 14 C -0.009624 14 C -0.147195 15 C -0.032436 15 C 0.071339 15 C 0.348904 16 C 0.348149 16 C 0.305781 16 C -0.143937 17 C -0.137509 17 C -0.146070 17 C -0.088218 18 C 0.122024 18 C -0.135024 18 C 0.121566 19 C 0.484567 19 C -0.112864 19 C 0.485061 20 C 0.091223 20 C -0.104626 20 F -0.297993 21 F -0.277554 21 C -0.146480 21 H 0.108581 22 H 0.117391 22 C 0.355555 22 H 0.104103 23 H 0.109404 23 C -0.146864 23 H 0.144197 24 H 0.105769 24 C -0.421940 24 H 0.074965 25 H 0.156692 25 F -0.296544 25 H 0.098838 26 H 0.086660 26 F -0.295673 26 H 0.093937 27 H 0.111503 27 H 0.102794 27 H 0.268955 28 H 0.269073 28 H 0.140339 28 H 0.271241 29 H 0.271429 29 H 0.113324 29 H 0.132900 30 H 0.133568 30 H 0.149051 30 H 0.129247 31 H 0.129565 31 H 0.065717 31 H 0.116957 32 H 0.079047 32 H 0.266425 32 H 0.155609 33 H 0.155969 33 H 0.268550 33 H 0.146699 34 H 0.146896 34 H 0.159594 34 H 0.151613 35 H 0.151927 35 H 0.152253 35 H 0.080085 36 N -0.534847 36 H 0.152048 36 N -0.690781 37 N -0.693148 37 H 0.103417 37 N -0.531723 38 N -0.625175 38 H 0.104297 38 N -0.624968 39 N -0.509768 39 H 0.102498 39 N -0.510392 40 O -0.513892 40 H 0.106251 40 O -0.514296 41 O -0.475662 41 H 0.104118 41 O -0.476019 42 H 0.080010 43 N -0.692813 44 N -0.530192 45 N -0.499706 46 N -0.634271 47 O -0.479489 The analysis of these parameters is crucial to understand the structural characteristics and potential reactivity of the compounds. Deviations from standard values or trends in these parameters may indicate structural features relevant to behavior and interactions. The combination of optimized structures, total energy values, and detailed geometric parameters provides a complete picture of the compounds studied. This information is vital to understanding their stability, reactivity, and potential applications in various fields ranging from chemistry to materials science. The data presented establish a foundation for further investigations and applications of these compounds. 3.2. Mulliken charge analyses Table 3 presents the Mulliken atomic charges for the compounds studied, which were estimated using the density functional theory (DFT) with the B3LYP functional and a 6- 31G** basis set. The calculations were conducted in the gaseous phase, offering insights into the distribution of charge among the atoms in each compound. Mulliken atomic charges play a crucial role in understanding the electronic structure and reactivity of molecules [37]. In this study, the DFT/B3LYP method, renowned for its accuracy in describing electronic properties, was used to estimate these charges. The inclusion of the 6-31G** basis set ensures a comprehensive and balanced representation of the electron density around each atom. Positive or negative charges on specific atoms indicate the degree of electron density and, therefore, the electronegativity or electro-positive positivity of those atoms [37]. These insights are essential to predict chemical reactivity, bond polarity, and potential reaction sites within molecules [38]. From Table 3, it has been observed that carbon atoms have partial positive and partial negative charges depending on their positions in the molecules. The highest values of negative charge on carbon atoms are -0.420523, -0.421940, and -0.420485 in compounds 1, 2, and 3, respectively. Hydrogen atoms are partially positively charged while nitrogen and oxygen atoms are partially negatively charged, irrespective of their positions in the molecules. Bromine and fluorine both atoms are partially negatively charged. Fluorine has the highest negative value in compound 3, indicating more electronegativity. This infor- mation is particularly relevant for interaction studies. 3.3. HOMO-LUMO analysis The interaction between the reacting species’ lowest unoccupied molecular orbital (LUMO) and highest occupied molecular orbital (HOMO) is what causes an electron to transition, according to the frontier molecular orbital theory (FMO) of chemical reactivity [39]. EHOMO is a quantum chemical characteristic that is frequently linked to a molecule’s capacity to donate electrons [40]. Rao and Yadava / European Journal of Chemistry 16 (2) (2025) 207-221 213 2025 – European Journal of Chemistry – CC BY NC – DOI: 10.5155/eurjchem.16.2.207-221.2654 Compound 1 Compound 2 Compound 3 LUMO ELUMO = 0. 05799 a.u. Egap = 0. 1549 a.u. EHOMO = -0. 21289 a.u. HOMO LUMO ELUMO = 0. 06231 a.u. Egap = 0. 1449 a.u. EHOMO = -0. 20730 a.u. HOMO LUMO ELUMO = -0. 05566 a.u. Egap = 0. 1555 a.u. EHOMO = -0. 2119 a.u. HOMO Figure 2. HOMO and LUMO molecular orbitals and their energy values as estimated at the B3LYP/6-31G** level. Compound 1 Compound 2 Compound 3 Figure 3. Molecular electrostatic maps of the compounds 1,2 and 3 obtained using the DFT/B3LYP/6-31G** method. High EHOMO values are probably indicative of a propensity of the molecule to give electrons to suitable acceptor molecules with low empty molecular orbital energies [39,40]. The outer- most orbital presumed to contain electrons, HOMO, is thought to operate as an electron donor. On the other hand, LUMO might be considered to be the innermost orbital with open spaces for electrons to enter. Molecular orbitals and their properties are utilized to explain many sorts of reactions and to forecast the most reactive position in conjugated systems. A little frontier orbital gap makes a molecule more polarizable and is typically linked to a high level of chemical reactivity and a poor level of kinetic stability. HOMO and LUMO orbitals and their energy values are shown in Figure 2. 3.4. Molecular electrostatic potential The molecular electrostatic potential (MEP) is frequently used to understand molecular interactions and as a reactivity, map splaying most probable regions for the electrophilic attack of charged point-like reagents on organic molecules in studies 214 Rao and Yadava / European Journal of Chemistry 16 (2) (2025) 207-221 2025 – European Journal of Chemistry – CC BY NC – DOI: 10.5155/eurjchem.16.2.207-221.2654 Table 4. Frequency of the vibration modes, relative intensity and vibrational assignments in the spectra of compound 1. Frequency (cm-1) IR intensity (km/mol) Vibrational assignments 17 0.0222 CH3- Rocking vibration in the plane 134 0.0626 CH3- Rocking vibration in the plane 143 2.2150 CH3- Rocking vibration in the plane 177 1.5207 CH3- Rocking vibration in the plane 203 1.3063 CH3- Rocking vibration in the plane 210 0.5117 CH3- Rocking vibration in the plane 279 0.3161 CH3- Rocking vibration in the plane 455 19.2052 Two benzene rings stretching in a plane 480 7.9702 Single benzene ring vibrates 531 32.6503 Single benzene ring stretching 638 3.3530 Two benzene ring stretching 697 16.8579 Two connected benzene ring stretching 718 18.3474 C=O Out of plane deformation 759 35.6510 C-F stretching of the benzene ring 782 8.3891 N-H stretching of two connected benzene rings 878 32.0762 Stretching in single benzene ring 906 28.3564 C=N stretching in benzene ring 1006 32.0315 O-CH3 Stretching attached with benzene ring 1017 2.6038 CH3- Rocking vibration in plane 1022 5.8639 Stretching in a benzene ring attached with fixed O-atom 1047 55.5160 C-CH3 stretching 1138 4.0690 CH2- Rocking vibration 1266 36.4754 Stretching in single benzene ring 1304 17.3420 Stretching in single benzene ring 1332 41.3553 C-N stretching attached with two benzene rings 1377 2.2911 C-H3 Scissoring vibration in the same plane 1407 370.8627 C=N Stretching attached with two benzene ring 1422 171.3653 CH3- Scissoring vibration 1437 5.7732 CH3- Rocking vibration 1439 7.3614 CH2- Scissoring vibration 1455 6.4320 CH2- Rocking vibration 1458 36.2467 CH2- Scissoring vibration 1460 906.9779 N-H- Stretching vibration 1466 27.7286 CH2- Scissoring vibration 1499 294.8916 Scissoring vibration 1524 439.4134 C=N- Stretching two benzene rings attached with each other 1557 205.6282 Stretching in two connected benzene rings 1572 127.5731 Stretching in benzene ring 1597 175.6831 Stretching in single benzene ring 1608 26.0594 Stretching in single benzene ring 1618 164.1261 Stretching in a benzene ring connected with other benzene ring 1718 238.7300 C=O out of plane deformation 2277 135.5385 C≡C Stretching 2932 52.9608 CH3- Symmetrical vibration 2943 21.2772 CH3- Symmetrical vibration 3008 6.7612 CH2- Antisymmetrically vibration 3011 6.1131 CH3- Antisymmetrically vibration 3062 19.4688 CH2- Symmetrically vibration of biological recognition and hydrogen-bonding interactions [41]. It is a highly useful tool for molecular modeling investi- gations. Predicting potential interactions between various geometries is made simple by MEP. Different colors are used to illustrate the various electrostatic potential levels. Potential growth in the following order: red, orange, yellow, green, and blue. The significance of MEP rests in its ability to dynamically display the molecular size, shape, and regions of positive, negative, and neutral electrostatic potential. MEP is also very helpful in the study of molecular structure and the relationship between it and its physiochemical properties. The MEP map of the compounds is shown in Figure 3. In Figure 3 it has been observed that the negative region is related to electrophilic reactivity (red color), while the positive regions are related to nucleophilic reactivity (blue color). It is evident that the electron densities are very low at the outer surface and near the hydrogen atoms (blue and light blue region), indicating positive electrostatic potentials. 3.5. Infrared spectra The infrared spectra of the compounds in the range of 400 to 3800 cm-1 have been calculated and are presented in Tables 4-6. The calculated IR frequencies have been scaled with a scaling factor of 0.9679 [19,42]. Normal vibrational modes have been assigned on their corresponding vibrational characteristics. Infrared (IR) spectra effectively identify specific functional groups, particularly in larger molecules. The molecules exhibit a syn conformation and structural symmetry, with no imaginary wavenumbers detected, confirming their stability. Vibrational spectroscopy has contributed significantly to understanding the structural and physicochemical properties of crystals and molecular systems. Fundamental vibrations have been systematically assigned on their nature, position, form, and relative intensity. The IR spectra of compounds 1, 2, and 3 within the 400-3800 cm-1 range show characteristic vibrational features, including CH and CN stretching modes, among other notable vibrations. From Table 4, it has been observed that compound 1 exhibits strong N-H stretching (1460 cm-1, 907 km/mol), emphasizing the importance of amine functionalities. C=O out- of-plane deformations are observed at 718 and 1718 cm-1 with moderate to high intensities. The diversity of benzene ring vibrations points to a complex aromatic framework. In the spectrum of compound 2, prominent C-N stretching modes (e.g. 1493 cm-1, 585 km/mol) highlight the nitrogen-containing structures. Benzene-ring interactions dominate, with intense vibrations at 1562 cm-1 (451 km/mol). Additionally, functional group contributions include C≡C stretching and CH₃ attachments, further diversifying the vibrational spectrum. Rao and Yadava / European Journal of Chemistry 16 (2) (2025) 207-221 215 2025 – European Journal of Chemistry – CC BY NC – DOI: 10.5155/eurjchem.16.2.207-221.2654 Table 5. Frequency of the vibration modes, relative intensity, and vibrational assignments in the spectra of compound 2. Frequency (cm-1) IR intensity (km/mol) Vibrational assignments 19 0.0401 CH3 Rocking vibration in the plane 505 8.9892 Stretching of benzene rings connected with each other 550 9.8547 Stretching of benzene rings connected with each other 567 22.0004 Stretching of a benzene ring connected with C-C 630 3.0919 Stretching of a benzene ring connected with F 655 0.3715 Stretching of two benzene rings connected with each other 679 0.7310 Stretching of two benzene rings connected with C-C 688 4.0338 Stretching of a benzene ring connected with C-C 700 9.7984 C=O Out of plane deformation 747 10.0723 Stretching of two benzene rings connected with each other 769 26.2927 Stretching of a benzene ring connected with F 812 17.0811 Stretching of a benzene ring connected with F 857 37.0474 C-N Out of plane deformation 892 32.0418 Stretching of a benzene ring attached with two nitrogen atoms 998 4.2262 Stretching in benzene ring attached with F 1018 2.8709 Scissoring vibration in the plane 1020 2.1998 Scissoring vibration in the plane 1059 22.6460 C≡C-CH3 Stretching 1196 79.2316 C-CH3 Stretching attached with C=O 1267 3.6779 Stretching in a benzene ring attached with -N 1297 2.9408 Stretching in a benzene ring attached with -F 1349 43.9101 Stretching in two benzene rings attached 1377 17.7764 CH3- Scissoring vibration in the plane 1402 202.5159 Stretching in a benzene ring attached with -F 1435 7.7481 CH2- Rocking vibration in the plane 1438 7.8824 CH2- Scissoring vibration in the plane 1485 523.1373 Stretching in a benzene ring attached with another benzene ring 1493 585.6062 C-N Stretching in a benzene ring attached with benzene ring 1508 8.7209 C-N Stretching in a benzene ring attached with C=O 1513 118.7992 Stretching in all four-benzene ring 1535 451.3081 C-N Stretching connected with the benzene ring 1562 170.7172 Stretching in two benzene rings attached to each other 1572 208.7248 Stretching in a benzene ring attached with -F 1583 125.8284 Stretching in a benzene ring attached with -F 1597 163.4928 Stretching in a benzene ring attached with -F 1610 34.8223 Stretching in two benzene rings connected with C-C 1615 26.9603 Stretching in two benzene rings connected with C-C 1624 25.9094 Stretching in a benzene ring attached to another benzene ring 1706 287.5465 C=O Stretching attached with -N 2274 149.0858 C≡C Stretching attached with -CH3 2944 18.2785 CH3- Wagging vibration in the plane 3008 5.7120 CH2- Twisting vibration in the plane 3014 4.9187 CH2- Twisting vibration in the plane Table 6. Frequency of the vibrational modes, relative intensity and vibrational assignments in the spectra of compound 3. Frequency (cm-1) IR intensity (km/mol) Vibrational assignments 20 0.4986 CH2- Rocking vibration attached with alkene C 216 0.1326 CH2- Rocking vibration attached with -O 281 0.0751 CH2- Rocking vibration attached with -O 345 46.5911 C triple bond C out of plane deformation 353 9.0719 C triple bond C out of plane deformation 510 5.2249 Stretching in benzene ring attached with F 578 17.4487 Stretching in benzene ring attached with F 645 15.2814 Stretching in a benzene ring containing two N 697 14.7333 Stretching in two benzene rings attached to each other 718 20.0948 C=O Out of plane deformation 744 7.2228 Stretching in benzene ring attached with F 882 21.5528 N-H Out of plane deformation 982 3.2651 Stretching in benzene ring attached with F 1007 34.3227 CH3-O Stretching attached with benzene 1017 2.6013 CH3- Rocking vibration attached with -C≡C 1022 5.4891 CH3- Rocking vibration attached with -C≡C 1138 1.6187 CH2- Rocking vibration attached with -O 1182 1.7246 CH2- Rocking vibration attached with -O 1189 238.0394 CH3-C Stretching vibration 1272 87.9545 Stretching in benzene ring attached with F 1318 25.5817 Stretching in benzene ring attached with F 1335 9.9024 Stretching in two benzene rings attached 1339 15.9766 Stretching in benzene ring attached with F 1376 208.6871 CH3- scissoring vibration attached with C≡C 1377 5.7116 C≡C Scissoring vibration attached with -O40 1437 5.7536 CH2- Scissoring vibration attached with C≡C 1439 6.8450 CH2- Scissoring vibration attached with C≡C 1447 246.4877 Stretching in benzene ring attached with F 1455 4.9092 Rocking vibration in the plane 1460 661.1954 CH2- Scissoring vibration attached with -O40 1466 30.6800 CH2- Scissoring vibration attached with -O40 1476 7.6803 Stretching in a benzene ring attached with -F 1500 188.7587 Stretching in a benzene ring attached with another benzene ring 1532 441.4520 N36-C3 Stretching attached with the benzene ring 216 Rao and Yadava / European Journal of Chemistry 16 (2) (2025) 207-221 2025 – European Journal of Chemistry – CC BY NC – DOI: 10.5155/eurjchem.16.2.207-221.2654 Table 6. (Continued). Frequency (cm-1) IR intensity (km/mol) Vibrational assignments 1557 270.9331 Stretching two benzene rings attached 1606 116.6676 Stretching in a benzene ring attached with -F and -N 1613 159.0424 Stretching in a benzene ring attached with -F and -N 1618 128.1936 Stretching in a benzene ring connected with other benzene ring 1717 238.0266 O=C Out of plane deformation 2275 131.8029 C≡C attached with CH3 wagging vibration attached O40 2943 21.5235 Wagging vibration attached with C≡C 2999 27.7150 Rocking vibration attached with O40 3007 6.8738 CH2- Twisting out of a plane attached with C≡C 3011 6.2070 CH2- Twisting out of a plane attached with C≡C Table 7. Thermodynamic properties of compounds 1, 2 and 3. Parameters Compound 1 Compound 2 Compound 3 Rotational temperature (K) 0.01425, 0.00263, 0.00225 0.01444, 0.00233, 0.00202 0.01551, 0.00428, 0.00341 Rotational constant (GHz) 0.29697, 0.05463, 0.04678 0.30091, 0.04848, 0.04209 0.32318, 0.08920, 0.07104 Thermal energy (kcal/mol) Translational 44.052 43.954 43.453 Rotational 37.288 37.502 36.305 Vibrational 100.829 105.930 92.559 Total 182.169 187.385 172.317 Molecular capacity at volume (cal/mol-K) Translational 0.889 0.889 0.889 Rotational 0.889 0.889 0.889 Vibrational 202.131 234.723 207.470 Total 203.909 236.500 209.248 Entropy (Cal/mol- K) Traslational 2.981 2.981 2.981 Rotational 2.981 2.981 2.981 Vibrational 85.744 94.392 81.663 Total 91.000 100.353 87.625 Dipole moment (Debye) 7.3582 7.6266 6.7476 Zero-point vibrational energy (Kcal/mol) 188.16051 219.96177 194.46004 Compound 3 exhibits unique out-of-plane vibrations, such as C≡C stretching (345 and 3537 cm-1, 47 km/mol) and CH₃ wagging (2943 cm-1, 22 km/mol). Intense benzene ring stretches paired with functional groups, such as the vibration at 1557 cm-1 (271 km/mol), underscore its distinct structural features. Certain vibrational modes, particularly those involving benzene rings and C-N/C=O bonds, dominate IR absorption. These peaks reflect the significant contribution of these bonds to the compounds' IR profiles. Lower-energy vibrations, such as rocking modes below 500 cm-1, exhibit minimal IR intensities, indicating reduced dipole activity during these motions. Benzene ring vibrations: All compounds show characteristic stretching vibrations associated with benzene rings, with frequencies ranging from 471 to 1659 cm-1. In particular, the “two-benzene rings stretching" mode exhibits greater intensity in compound 1 (19.2052 km/mol) compared to the others, indicating a more pronounced aromatic interaction. CH3 and CH2 vibrations: Dynamic motions such as rocking, scissoring, and wagging are observed for the methyl (-CH₃) and methylene (-CH2) groups. For example, CH₂ scissoring in Compound 1 (906.9779 km/mol) and CH₃ scissoring in Compound 3 (246.4877 km/mol) show a high intensity, highlighting their significant contributions to molecular vibrations. This analysis reveals the nuanced vibrational behaviors of each compound, providing insights into their structural and functional properties. 3.6. Thermodynamic properties of compounds 1, 2 and 3 Thermodynamic properties like Zero-point vibration energy, entropy, molecular capacity, etc. have been calculated for the molecules by density function theory using B3LYP/6- 31G** and are present in Table 7. It is observed that compound 3 exhibits the highest values of rotational temperature and rotational constants among the three, indicating a smaller moment of inertia and a more rigid structure compared to the other compounds. Differences in these parameters suggest variations in molecular geometry and mass distribution. The translational and rotational energies are nearly identical across all compounds, suggesting similar mass and moment of inertia. The vibrational energy varies significantly, with compound 2 having the highest value (105.930 kcal/mol) and compound 3 the lowest (92.559 kcal/mol). It is observed that the translational and rotational contributions remain constant across all compounds. Compound 2 (7.6266 D) has the highest dipole moment, suggesting a stronger polarity, which may influence its solubility and intermolecular interactions. Compound 3 has the lowest dipole moment (6.7476 D), indicating relatively weaker dipole-dipole interactions. Compound 3 has the lowest vibrational energy and entropy, indicating a more rigid structure with lower disorder. 3.7. Global reactivity DFT has dominated as a sufficient tool for attaining theoretical perceptions of the chemical reactivity and site selectivity. The energy space between HOMO and LUMO is an analytical parameter that governs molecular electrical transport properties. Using HOMO and LUMO energy values for a molecule can describe global chemical parameter descriptors of molecules, such as electron affinity (A), ionization potential (I), global hardness (η), Softness (S), Electronegativity (χ), Chemical potential (μ) and Electrophilicity Index (ω) have been analyzed of the compounds. On account of HOMO energy and LUMO energy, the above are calculated using the below equations. By Koopmans’s theorem for closed-shell molecules, there are following global parameters, which can be calculated as [42,43]: Global hardness (η) 2 I A− = (1) ( )Softness S 1 2η = (2) ( )Electronegativity χ 2 I A+ = (3) ( )Chemical potent ( ) 2 ial μ I A− + = (4) 2μElectrophilicity index (ω) = 2η (5) where A and the I are the electron affinity and ionization potential of the given molecules. Rao and Yadava / European Journal of Chemistry 16 (2) (2025) 207-221 217 2025 – European Journal of Chemistry – CC BY NC – DOI: 10.5155/eurjchem.16.2.207-221.2654 Table 8. The calculated global reactivity parameters of the molecules. Parameters Compound 1 Compound 2 Compound 3 Energy (HOMO) Hartree -0.21289 -0.20730 -0.21119 Energy (LUMO) Hartree -0.05799 -0.06231 -0.05566 ∆E Hartree 0.15490 0.14499 0.15553 Global hardness (η) Hartree 0.0774 0.0725 0.0778 Softness (S) Hartree-1 6.4558 6.8961 6.4296 Electronegativity (χ) Hartree 0.1354 0.1348 0.1334 Chemical potential (µ) Hartree -0.1354 -0.1348 -0.1334 Electrophilicity index (ω) Hartree 0.1184 0.1253 0.1145 Electron affinity (A) Hartree 0.0580 0.0623 0.0557 Ionization potential (I) Hartree 0.2129 0.2073 0.2112 Table 9. Various energy terms (kcal/mol) as obtained through the SP and XP docking of molecules within the binding site of methyltransferase. Rank (SP) Compound GScore HBond vdW Coul Emodel CvdW 1 Compound 3 -5.07 -0.4 -37.6 -6.0 -55.0 -43.6 2 Afatinib -4.64 -0.4 -38.6 -12.7 -69.1 -51.3 3 Compound 1 -4.29 -0.4 -36.4 -5.6 -54.4 -41.9 4 Compound 2 -3.64 -0.1 -42.3 -5.1 -56.9 -47.4 Rank (XP) Compound GScore HBond vdW Coul Emodel CvdW 1 Afatinib -6.36 -1.2 -41.4 -9.1 -72.7 -50.6 2 Compound 3 -4.68 -0.7 -42.0 0.6 -61.9 -41.3 3 Compound 1 -4.61 -0.7 -41.4 -4.5 -61.6 -45.9 4 Compound 2 -2.61 -0.7 -40.5 -1.0 -57.9 -41.5 All determined values of HOMO energy, LUMO energy, energy gap, hardness, softness, electronegativity, chemical potential, electrophilicity index, electron affinity, and ionization potential are shown in Table 8. Compound 3 shows the least amount of HOMO-LUMO energy gap ΔEgap = 0.02532 Hartree, indicating it is the most delicate molecule. The molecule that has the highest HOMO energy is compound 3 (EHOMO = 0.21119Hartree). It represents that it can be the best electron acceptor. These two properties, potential ionization (I) and affinity (A), are so important that they decide to calculate the global hardness (η) and electronegativity (χ). HOMO and LUMO are concerned with an electro-orbital potential. Compound 2 (I = 0.2073 Hartree) has the least potential ionization, which will make it a better electron donor. Compound 3 has the best affinity (A = 0.0557 Hartree), as a result, it is the best electron acceptor. The chemical reactivity changes with the activity of the molecule. Compound 3 has a global hardness value (η = 0.0778 Hartree) that is less in all molecules. Thus, compound 3 is found with more activity in comparison to other compounds. Compound 3 electronegativity value (χ = 0.1334 Hartree) is higher than other compounds that is the compound is the best electron acceptor. Value for ω for compound 3 (ω = 0.1145 Hartree) shows that they are more powerful in electrophiles compared to others. Compound 3 has fewer frontiers orbital gaps, hence, it is more polarized and it is associated with less kinetic stability and higher chemical reactivity and hence can be said a soft molecule [34]. 3.8. Docking and binding pose analysis The SP and XP docking of compounds 1, 2, 3, and afatinib was carried out within the binding site of the MTase enzyme (PDB ID: 5WXB) of the Zika virus, and the results are presented in Figures 4a and b, and Table 9. From Table 9, it is observed that compound 3 exhibits the highest docking score (-5.07 kcal/mol), followed by afatinib (-4.64 kcal/mol). Compounds 1 and 2 rank third and fourth, respectively, in agreement with their experimentally observed inhibitory activities [24]. The Emodel energies follow the same trend, except for afatinib and compound 3, which are reversed in ranking. The XP docking results provide a clearer differentiation of molecular affinities. The XP docking score of afatinib (-6.36 kcal/mol) is better than that of compound 3 (-4.68 kcal/mol), followed by compounds 1 and 2 (Table 9). The Emodel energies also follow the same order. Furthermore, it is concluded that the van der Waals energy component plays a major role in the interaction of these molecules within the binding site of the MTase enzyme of the Zika virus. Figures 4a and 4b illustrate the hydrogen bonding and other noncovalent interactions obtained through SP and XP docking, respectively. Compound 3 forms hydrogen bonds with residues GLY148, LYS105, and THR104, while afatinib interacts by hydrogen bonding with GLU149 and GLU111. Hydrophobic interactions are observed with CYS82, TYR103, VAL130, VAL132, PHE133, and ILE147, among others. SER150, THR104, and HIS110 contribute to polar interactions, while LYS182, ARG84, ARG163, and ARG160 exhibit positively charged interactions, and GLU149, ASP146, GLU111, and ASP131 display negatively charged interactions. In Figure 4b, it can be observed that afatinib forms hydrogen bonds with GLU111, LYS105, ARG163, and GLY148, while compound L3 interacts with GLY81 and GLY148. Hydrophobic interactions are contributed by TRP87, CYS82, VAL130, VAL132, PHE133, TYR103, and ILE147. Polar interactions arise due to SER88, SER56, THR104, and HIS110, while positively charged interactions are exhibited by LYS182, ARG84, ARG183, and LYS105, and negatively charged interactions are observed with GLU149, ASP146, GLU111, ASP131, and ASP79. Based on docking scores, hydrogen bonding, and other noncovalent interactions, afatinib and compound 3 demonstrate stronger interactions compared to compounds 1 and 2. 3.9. Explicit solvent molecular dynamics simulation analysis Molecular dynamics (MD) simulations were performed on the best-docked poses of the afatinib-MTase and Compound 3@MTase complexes using the SPC/E water model, salts; and sodium ions within the improved OPLS4 force field environment [44]. Following MD simulations, various thermodynamic parameters were evaluated, including the root mean square deviations (RMSD) of heavy atoms and the root mean square fluctuations (RMSFs) of the residues. Additionally, noncovalent interactions during the simulations were analyzed. The RMSD plots of protein C-α atoms and ligand atoms for afatinib and molecule 3 over a simulation period of 200 ns are shown in Figures 5a and 5b, respectively. As seen in Figure 5a, the protein RMSD stabilizes at an average value of 2.1 AÅ within the first 20 ns, remaining constant with minor fluctuations for the rest of the simulation. The RMSD of afatinib fluctuates up to 118 ns, after which it stabilizes at 14 AÅ within the MTase binding site of the Zika virus, suggesting that a new binding site is achieved during the simulation. 218 Rao and Yadava / European Journal of Chemistry 16 (2) (2025) 207-221 2025 – European Journal of Chemistry – CC BY NC – DOI: 10.5155/eurjchem.16.2.207-221.2654 Afatinib Compound 1 Compound 2 Compound 3 (a) Afatinib Compound 1 Compound 2 Compound 3 (b) Figure 4. Hydrogen bonding and other noncovalent interactions as obtained through (a) standard-precision (SP) docking and (b) extra-precision (XP) docking. For the Compound 3@MTase complex (Figure 5b), the protein C-α RMSD increases with simulation time, reaching an average deviation of 2.8 AÅ at 100 ns, after which it remains stable with slight fluctuations. Unlike afatinib, compound 3 attains its equilibrium conformation within the binding site at an early stage (20 ns). The average RMSD of compound 3 within the binding site remains approximately 5.6 AÅ , indicating that the ligand remains within the same binding site throughout the simulation. The root mean square fluctuation (RMSF) plots for the Afatinib@MTase and Compound 3@MTase complexes are presented in Figures 5c and 5d, respectively. These plots provide information on local conformational changes along the protein chain. Rao and Yadava / European Journal of Chemistry 16 (2) (2025) 207-221 219 2025 – European Journal of Chemistry – CC BY NC – DOI: 10.5155/eurjchem.16.2.207-221.2654 (a) (b) (c) (d) (e) (f) Figure 5. Results of the MD simulation (a) Variation of the RMSD of protein C-α and the afatinib molecule during the molecular dynamics simulation run of 200 ns. (b) Variation of the RMSD of the protein C-α and compound 3 molecules during the simulation of molecular dynamics of 200 ns. (c) RMSF of the interacting protein residues in the Afatinib@MTase complex. (d) RMSF of the interacting protein residues in Compound 3@MTase complex, (e) Interactions fraction of hydrogen bonds, hydrophobic, ionic, and water bridges during MD simulation of the interacting residues in Afatinib@MTase complex, (f) Interactions fraction of hydrogen bonds, hydrophobic, ionic and water bridges during MD simulation of the interacting residues in Compound 3@MTase complex. The peaks indicate the regions of the protein that exhibit the highest fluctuations. In Figure 5a, significant fluctuations are observed in residues 1-50 and 100-110, while other regions show relatively lower fluctuations. In contrast, Figure 5b shows that the RMSF values for residues 1-50 in the Compound 3@MTase complex are higher than those observed in the afatinib-bound system, indicating greater flexibility in this region. Both simulations reveal relatively stable regions with RMSF values below 1.5 AÅ for most of the protein, suggesting structural rigidity in these segments. However, the RMSF plot for compound 3 exhibits more pronounced fluctuations across multiple regions, implying that the protein undergoes greater conformational changes compared to the afatinib-bound system. The green bars in both plots mark key interaction sites. Variations in the number and intensity of these interaction sites suggest potential differences in the stability of the ligand and binding interactions during the simulations. Additionally, differences in interaction site distribution indicate that the ligands may induce distinct effects on protein flexibility. The histograms shown in Figures 5e and 5f illustrate the protein-ligand interaction frequencies during molecular dynamics simulations for the Afatinib@MTase and Compound 3@MTase complexes, respectively. The first histogram (Afatinib@MTase), Figure 5e, shows dominant interactions at residues TYR74, GLY75, and LEU141, with a mix of hydrogen- bonding, hydrophobic, and water-bridge interactions. The second histogram (Compound 3@MTase) presents more dispersed interactions, with strong contributions from SER56, GLY81, GLU111, ASP146, and GLU149. It can be seen that Afatinib forms stable interactions with residues located primarily in a concentrated region, particularly around LEU141 and TYR74. Compound 3, however, engages with a broader range of residues, suggesting a more dynamic binding mode. In both cases, specific residues exhibit almost 100% interaction fractions, indicating consistent ligand binding during simulation. Compound 3 forms more extensive polar and charged interactions (e.g., GLU111, ASP146, GLU149), which could influence binding stability. Although both ligands exhibit strong interactions with MTase, Afatinib appears to maintain a more rigid and specific binding profile, while Compound 3 shows broader residue engagement, potentially allowing more flexibility at the binding site. These differences could impact their respective binding affinities and functional effects. 4. Conclusions In summary, the estimation of Mulliken atomic charges using the DFT/B3LYP method with a 6-31G** basis set in the gaseous phase contributes valuable information to the understanding of the electronic characteristics of the studied compounds. These data serve as a foundation for elucidating the reactivity patterns of compounds, guiding future research endeavors, and informing applications in various scientific disciplines. The geometrical parameters of the anti-ZIKV biological Compounds 1, 2, and 3 are calculated using the Density function B3LYP/6-31G** basis set. Optimized parameters (bond length, bond angle, etc.) have been used for the computations of electronic structure properties and IR frequencies. MEP, Mulliken charge, and HOMO-LUMO analyses show that the compounds are chemically active. The most sensitive region of the molecules is predicted by MEP. The charge transfer interaction inside the molecule is supported by the difference in HOMO and LUMO energy. Global reactivity descriptors have been used to determine the chemical reactivity and site selectivity of compounds. Several experimental vaccines are undergoing early human clinical testing and could be created as a treatment candidate for the treatment of ZIKV. The docking analysis of the molecules within the MTase enzyme binding site reveals that Afatinib and Compound 3 exhibit higher binding affinities compared to Compound 1 and Compound 2. Molecular dynamics simulations of the top- ranked complexes (Afatinib@MTase and Compound 3@MTase) further confirm their stability within the Zika virus MTase binding site, highlighting their potential as promising candidates for the development of anti-Zika virus therapeutics. Acknowledgements The authors thank the Center for Development of Advanced Computing (CDAC), Pune, for providing a high-performance supercomputing facility. Disclosure statement Conflict of interest: The authors declare that they have no conflict of interest. Ethical approval: All ethical guidelines have been followed. 220 Rao and Yadava / European Journal of Chemistry 16 (2) (2025) 207-221 2025 – European Journal of Chemistry – CC BY NC – DOI: 10.5155/eurjchem.16.2.207-221.2654 CRediT authorship contribution statement Conceptualization: Umesh Yadava; Methodology: Umesh Yadava; Software: Umesh Yadava; Validation: Umesh Yadava, Akhilesh Kumar Rao; Formal Analysis: Umesh Yadava, Akhilesh Kumar Rao; Investigation: Umesh Yadava, Akhilesh Kumar Rao; Resources: Umesh Yadava; Data Curation: Umesh Yadava, Akhilesh Kumar Rao; Writing - Original Draft: Umesh Yadava, Akhilesh Kumar Rao; Writing - Review and Editing: Umesh Yadava; Visualization: Akhilesh Kumar Rao; Funding acquisition: Umesh Yadava, Akhilesh Kumar Rao; Supervision: Umesh Yadava; Project Administration: Umesh Yadava. Funding Umesh Yadava thanks Council of Science and Technology, Uttar Pradesh, Lucknow, India for funding through its major research project. ORCID and Email Akhilesh Kumar Rao akhileshkrao@rediffmail.com https://orcid.org/0009-0003-8523-8535 Umesh Yadava u_yadava@yahoo.com umesh.phy@ddugu.ac.in https://orcid.org/0000-0002-9127-532X References [1]. Ledermann, J. P.; Guillaumot, L.; Yug, L.; Saweyog, S. C.; Tided, M.; Machieng, P.; Pretrick, M.; Marfel, M.; Griggs, A.; Bel, M.; Duffy, M. R.; Hancock, W. T.; Ho-Chen, T.; Powers, A. M. Aedes hensilli as a Potential Vector of Chikungunya and Zika Viruses. PLoS Negl Trop Dis 2014, 8 (10), e3188. [2]. Altaf Khan, M.; Farhan, M.; Islam, S.; Bonyah, E. Modeling the transmission dynamics of avian influenza with saturation and psychological effect. Discrete amp; Contin. Dyn. Syst. - S 2019, 12 (3), 455–474. [3]. Newman, C.; Friedrich, T. C.; O’Connor, D. H. Macaque monkeys in Zika virus research: 1947–present. Curr. Opin. Virol. 2017, 25, 34–40. 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This is an open access article distributed under the terms and conditions of the CC BY NC License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited without any further permission from Atlanta Publishing House LLC (European Journal of Chemistry). No use, distribution, or reproduction is permitted which does not comply with these terms. Permissions for commercial use of this work beyond the scope of the License (https://www.eurjchem.com/index.php/eurjchem/terms) are administered by Atlanta Publishing House LLC (European Journal of Chemistry). https://www.eurjchem.com/index.php/eurjchem/terms http://creativecommons.org/licenses/by-nc/4.0 https://www.eurjchem.com/index.php/eurjchem/terms 1. Introduction 2. Experimental 3. Results and discussion 3.1. Molecular geometry optimizations 3.2. Mulliken charge analyses 3.3. HOMO-LUMO analysis 3.4. Molecular electrostatic potential 3.5. Infrared spectra 3.6. Thermodynamic properties of compounds 1, 2 and 3 3.7. Global reactivity 3.8. Docking and binding pose analysis 3.9. Explicit solvent molecular dynamics simulation analysis 4. Conclusions Acknowledgements Disclosure statement CRediT authorship contribution statement Funding ORCID and Email References PrintField10: PrintField11: PrintField12: PrintField13: PrintField14: PrintField15: PrintField16: PrintField17: PrintField18: PrintField19: PrintField110: PrintField111: PrintField112: PrintField113: PrintField114: PrintField20: PrintField21: PrintField22: PrintField23: PrintField24: PrintField25: PrintField26: PrintField27: PrintField28: PrintField29: PrintField210: PrintField211: PrintField212: PrintField213: PrintField214: