Molecular Docking and Virtual Screening of Boswellia dalzielii Phytochemicals as Potential Inhibitors of Rabies lyssavirus.

 Corresponding author: Ezeagha Chigozie Celestina Copyright © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution License 4.0. Molecular Docking and Virtual Screening of Boswellia dalzielii Phytochemicals as Potential Inhibitors of Rabies lyssavirus. Emmanuel Chuks Oranu 1, Chigozie Celestina Ezeagha 1, *, Afomachukwu Jessica Madueke 1, Blessing Ejiro Otarigho 2, joseph Orjiakor 1 and Ifechukwu Kingsley Etuka 1 1 Department of Pharmaceutical and Medicinal Chemistry, Faculty of Pharmaceutical Sciences, Chukwuemeka Odumegwu Ojukwu University Igbariam, Anambra State, Nigeria. 2 Department of Pharmacology and Therapeutics, Faculty of Basic Medical science, Delta State University, Delta State, Nigeria. GSC Biological and Pharmaceutical Sciences, 2025, 33(02), 267–279 Publication history: Received on 03 October 2025; revised on 13 November 2025; accepted on 15 November 2025 Article DOI: https://doi.org/10.30574/gscbps.2025.33.2.0447 Abstract Rabies is a fatal viral encephalitic disease caused by the Rabies lyssavirus that has the highest case fatality rate of any infectious disease. Infection with rabies virus takes either the furious form or paralytic form defined by neurological complications or widespread paralysis respectively. This study was aimed to employ computational methods and tools to predict, analyse, and understand the potential antiviral effects of phytochemical compounds from Boswellia dalzielii (hutch) on this virus. To achieve this, the target protein of Rabies lyssavirus was selected from protein data bank. The receptor (8B8V) was prepared using Chimera-1.10.1, PyMOL-2.3.0, and Autodock tools-1.5.6, and the same was done for the reference ligand (PEG), while the phytochemicals were selected from Drugbank and PubChem database. The phytochemicals which were screened out were then extracted and prepared using Autodock tools-1.5.6. Validation of docking protocol was done after which molecular docking was carried out using Linux operating system (Ubuntu)- 20.04. The docking results were analysed and visualised using PyMOL-2.3.0 and the front runners were screened on Datawarrior based on the Lipinski’s Rule of Five and toxicity. Following the completion of the aforementioned procedures, the reference ligand was observed to have a mean binding energy of -3.3 Kcal/mol. While the 149 phytoconstituents including the 10 front-runners had lower binding energies ranging from -8.6 to -3.8 Kcal/mol indicating better binding affinity than the reference ligand. Comparing the phytochemicals with the reference ligand of the selected protein, it can be concluded that these phytochemicals exhibit better binding affinity, with Gallocatechin (- 8.6 Kcal/mol) having the highest binding affinity, thus, a better anti-rabies activity, however, it failed the Lipinski rule but Luteolin (-7.7 Kcal/mol), Epicatechin (-7.6 Kcal/mol) and Cianidanol (-7.3 Kcal/mol) passed the Lipinski rule and toxicity studies and are also part of the front runners and can be predicted to have better anti-rabies activity. Keywords: Rabies lyssavirus; Phytochemicals; Molecular docking; Boswellia dalzielii; Binding affinity; Reference ligand; Gallocatechin; Anti-viral activity. 1. Introduction Lyssa viruses cause rabies, which is widely regarded as the deadliest known encephalitic disease known. The prototype, known as Rabies lyssavirus (RABV), is thought to infect all terrestrial mammals. Transmission is by virus-laden saliva, typically through the bite of an infected animal, but sometimes through other ways such as scratches and, in rare cases, organ transplants [1, 2]. GSC Biological and Pharmaceutical Sciences, 2025, 33(02), 267–279 268 This single-stranded, negative-sense RNA virus is typically transmitted via the bite of an infected animal, with domestic dogs serving as the primary reservoir and vector for human transmission in many regions of the world [3]. Rabies, or 'rabere' in Latin, means 'to be mad.' The sickness has been known since the beginning of civilization. Rabies was first officially documented in the pre-mosaic Eshmuna code of Babylon in the twenty-third century BC. However, in the 1880s, Louis Pasteur identified a virus as the source of the sickness. Though rabies is a preventable viral zoonosis by vaccines [4], it remains an important public health issue in developing countries, as evidenced by the fact that globally, this devastating disease is responsible for more than 60,000 human deaths, while approximately 15 million people receive rabies post-exposure prophylaxis (PEP) annually [5]. Plants have been employed as medicinal agents for many years, initially in the form of traditional concoctions and later as isolated active drug moieties, with the transfer of knowledge and expertise from one generation to the next [6]. The utilisation of indigenous plants for the management of human ailments dates back to the ancient civilisations of China and India. Currently, there is a growing emphasis and interest in the production of medicinal substances, with a particular focus on the field of Phytochemistry [7]. Phytochemicals, commonly referred to as phytonutrients, are substances that exist naturally in plants and contribute to their flavour, colour, and ability to resist diseases. Phytochemicals have sparked widespread interest in scientific research due to their potential health-promoting and disease-preventive characteristics [8]. Epidemiological studies have established links between high intake of phytochemical-rich foods and decreased risk of chronic diseases such as cardiovascular disease, cancer, diabetes, and neurological disorders [9]. Boswellia dalzielii, commonly known as “African frankincense”, is a tree in the Burseraceae family, belonging to the Boswellia genus and the B. dalzielii species. The wooden savanna stands about 13 metres tall and has a pale, papery bark that peels and is ragged [10]. The bark produces whitish gum resin that dries quickly and is friable. The plant products (such as gum resin) and various plant parts are commonly used in traditional medicine [11]. It is abundantly found in West Africa in different countries such as Ghana, Niger, Ivory Coast, Upper Volta and Northern Nigeria, where the Hausa-speaking inhabitants of Nigeria call it ‘Hano’ or ‘Ararrabi’ [11]. Moreover, in Burkina Faso, it is called ‘Kumdagneogo’, ‘Tree Man’ or ‘Volta’, and in Ghana, it is called ‘Piangwogu’, while in Ethiopia, it is known as ‘Etan’ [7]. B. dalzielii is the frankincense-producing plant found in West Africa.It is used to treat, among others, rheumatism, septic sores, venereal diseases and gastrointestinal disorders. Despite its widespread use in traditional medicine in the sub region, the West African species is understudied compared to its more well-known counterparts. Phytochemical examination of the plant confirmed the absence of alkaloids while saponins, tannins, flavonoids, cardiac glycosides, steroids, and terpenes were found to be present [11]. The term 'in silico' is a modern word that refers to computer-based experimentation and is connected to the more widely known biological terms in vivo and in vitro. In silico pharmacology (also known as computational therapeutics and computational pharmacology) is a rapidly expanding field that encompasses the development of strategies for employing software to acquire, evaluate, and integrate biological and medical data from a variety of sources. It explicitly outlines the use of this data in the development of computational models or simulations that can be used to generate predictions, propose hypotheses, and, eventually, give discoveries or breakthroughs in medicine and therapies [12, 13]. 2. Materials and methods Several software programmes are required to investigate the activities of the constituents of Boswellia dalzielii against Rabies lyssavirus through molecular docking and post-docking analysis. These software programmes have demonstrated high reliability and effectiveness in in silico research, making them valuable resources in drug discovery and design. They include PyMOL (v 2.3.0), Chimera (v 1.10.1), Autodock tools (v 1.5.6), Datawarrior 550, MGL Tools (v 1.5.6), and OpenBabel (v 2.4.1). Biological [Protein Data Bank (PDB)] and Chemical (PUBCHEM and Drug bank) databases are used for bioinformatics and cheminformatics mining respectively [14]. Molecular docking and dynamics simulation documents include; • Conf.Text: This Ubuntu text document inputs binding site scores based on grid box size and position for accurate binding site representation in molecular docking simulations. GSC Biological and Pharmaceutical Sciences, 2025, 33(02), 267–279 269 • Bash Binbash.sh: This ODT document contains codes for molecular docking procedures. Finally, a window 10 pro laptop. 2.1. Bioinformatics MiningIdentification of Target Sites A search on protein data bank (PDB) for possible target proteins of Rabies lyssavirus with the following factors; a resolution of below (because the lower the Armstrong the better the resolution), an organic compound as a ligand and its relation to Boswellia dalzielii pathogenesis was determined. 2.2. Cheminformatics mining Constituents from Boswellia dalzielii with potential antiviral activities against Rabies lyssavirus were identified and about 150 phytochemicals downloaded from Drugbank and Pubchem which were screened on Datawarrior using the Lipinski’s Rule of Five, thus phytochemicals with molecular weight higher than 500 Da, hydrogen bond donors higher than 5, hydrogen bond acceptors higher than 10 and partition coefficient higher than 5 were screened out. Based on toxicity they were also screened for tumorigenicity, mutagenicity, effect on reproduction, irritant and undesirable functions. 2.3. Selection and Preparation of Target Protein After a thorough search on Protein databank, Rabies virus RNA free nucleoproteinphosphoprotein complex with the code 8B8V was identified and selected for the study. Its resolution is 2.30 Å. The ligand present in the protein is Di(Hydroxyethyl)ether with the chemical formula; C4 H10 O3. The protein of choice (8B8V) was downloaded from protein databank in pdb format. The protein preparation was conducted in both Chimera and Autodock tools. In Chimera, the similar chains were deleted leaving only two chains (A and B). This was saved as “Deleted 8B8V” as an SDF file. All ligands except the ligands of choice [Di(Hydroxyethyl)ether] were deleted. Again, this was saved as “Deleted 8B8V+Ligand” The ligand of choice was then deleted, leaving only the protein behind and the file was saved as “Filtered 8B8V” The target protein saved as the file “Filtered 8B8V” was then prepared on Autodock Tools. This was done by opening the protein on Autodock tools to edit it by adding polar only hydrogen and Kollman charges. It was then saved as a pdbqt file. 2.4. Selection and Preparation of Target Ligands The reference ligand was effectively determined with the following factors; first it was going to be an organic molecule, the second requirement is that it must bind to a binding site, this was observed using Pymol and Chimera, after observation Di(Hydroxyethyl)ether was selected. The reference ligand was found and downloaded from Protein Data Bank in ideal sdf format. The Preparation of ligands and phytochemicals were done in both Open Babel in Ubuntu and Autodock tools in Windows 10pro using the following process; The ligands were converted from sdf to mol2 format in Open Babel in Ubuntu using the command line: Is + enter + obabel (ligand) -O ligand.mo12. After which the mol2 files were copied and transferred to Windows where they were prepared in Autodock tools in windows by computing Gesteiger charges and making all bonds non rotatable. The file was then saved as pdpqt format and ready for docking. 2.5. Validation of Docking Protocol Here, the proteins are ready to be docked and now the binding site was determined. The program used is the Autodock tools in Windows 10pro and the reference ligand was isolated from the protein in Chimera and introduced alongside the prepared protein in Autodock tools. A grid box was introduced and made to cover the ligand in the binding site and the centre and dimension recorded in table 1. GSC Biological and Pharmaceutical Sciences, 2025, 33(02), 267–279 270 Table 1 Centre and Dimension of Grid Box for prepared 8B8V+ligand Grid box Center Dimension X 36.068 16 Y 38.908 16 Z 16.676 16 2.6. Molecular Docking Docking simulations are conducted in the Autodock-vina in Ubuntu. The pdpqt files which included the protein 8B8V, the ligands (phytochemicals) and reference ligand [Di(Hydroxyethyl)ether] with the code e introduced into a folder in Ubuntu, then three copies of this folder was created and opened in terminal using the command line; ‘bash binbash.sh’ which was used to dock the four folders. 2.7. Post Docking Analysis After the docking was successfully conducted (in four places), all results were compiled on excel and the mean alongside the standard deviation for each of the phytochemicals was calculated. The mean binding affinity of each of the ligands was then compared to the reference ligand and the frontliners were ascertained. These ligands within the binding pocket were visualised on pymol, to differentiate the ligands within the binding pocket, they were each coloured separately. The forces of interaction between the amino acids and the ligands were also visualised. Snapshots were made for easy visualisation of the affinity within the binding pocket and saved as PNG. 3. Results There were about 150 phytochemicals downloaded from Drugbank and PubChem, then molecular docking was conducted with these ligands against the target protein and their binding energies were determined on Ubuntu. Only the first 10 compounds with better binding affinities (the frontrunners) were screened on Datawarrior using the Lipinski Rule of Five and their toxicity profiles considered. The tables below contain the 150 phytochemicals with their binding energies and the first 10 compounds with better binding affinity as compared with the reference ligand (PEG) which was determined after docking with the selected protein 8B8V. Also shows the results obtained after the first screening of the ligands based on the Lipinski rule/toxicity screening done and results which were collated after comparison of the phytochemicals with the reference ligand during the post docking analysis. Table 2 Binding energies, mean binding energies and standard deviation of all the docked phytochemicals against the reference ligand PEG. S/N LIGANDS E 1 E 2 E 3 E 4 MEAN STANDARD DEVIATION 1 Gallocatechin -8.6 -8.6 -8.6 -8.6 -8.6 0.0 2 Robinetin -8.3 -8.2 -8.2 -8.2 -8.2 0.1 3 Isorhamnetin -8.1 -8.1 -8.1 -8.1 -8.1 0.0 4 Epicatechin-3-gallate -8.3 -8.2 -8.3 -7.3 -8.0 0.5 5 Apigenin -7.8 -7.8 -7.8 -7.8 -7.8 0.0 6 Luteolin -7.7 -7.7 -7.7 -7.7 -7.7 0.0 7 Epicatechin -7.6 -7.6 -7.5 -7.5 -7.6 0.1 8 Epigallocatechin-3-gallate -7.5 -7.5 -7.5 -7.5 -7.5 0.0 9 Kaempherol -7.4 -7.4 -7.4 -7.4 -7.4 0.0 GSC Biological and Pharmaceutical Sciences, 2025, 33(02), 267–279 271 10 Cianidanol -7.3 -7.3 -7.3 -7.3 -7.3 0.0 11 Quercetin -7.3 -7.3 -7.3 -7.3 -7.3 0.0 12 Butein -7.2 -7.2 -7.2 -7.2 -7.2 0.0 13 Myricetin -7.1 -7.1 -7.1 -7.1 -7.1 0.0 14 Epigallocatechin -7.3 -7.3 -6.6 -6.5 -6.9 0.4 15 Daidzein -6.9 -6.9 -6.9 -6.9 -6.9 0.0 16 Baicalin -6.4 -7 -7 -7 -6.9 0.3 17 Beta-pinacene -6.8 -6.8 -6.8 -6.8 -6.8 0.0 18 Caryophyllene alcohol acetate -7.3 -6.3 -7.1 -6.3 -6.8 0.5 19 Genistein -6.7 -6.7 -6.8 -6.7 -6.7 0.0 20 Biochanin A -6.7 -6.7 -6.7 -6.7 -6.7 0.0 21 Incensole -6.7 -6.7 -6.7 -6.7 -6.7 0.0 22 Eupalestin -6.5 -6.5 -6.5 -6.5 -6.5 0.0 23 Cembrenol -6.3 -6.4 -6.5 -6.5 -6.4 0.1 24 Resveratrol -6.3 -6.3 -6.3 -6.3 -6.3 0.0 25 Serratol -5.9 -6.1 -6.1 -6.1 -6.1 0.1 26 Alpha-Longipinene -6 -6 -6 -6 -6.0 0.0 27 Incensole acetate -6 -6 -6 -6 -6.0 0.0 28 m-Camphorene -5.9 -5.7 -5.9 -6 -5.9 0.1 29 Sinensetin -5.9 -5.8 -5.9 -5.9 -5.9 0.1 30 Alpha-Patchoulene -5.8 -5.8 -5.8 -5.8 -5.8 0.0 31 Alpha-Selinene -5.8 -5.8 -5.8 -5.8 -5.8 0.0 32 Caryophyllene oxide -5.8 -5.8 -5.8 -5.8 -5.8 0.0 33 Alpha-amyrin -6.2 -5.6 -6.3 -4.8 -5.7 0.7 34 Gamma-Eudesmol -5.5 -5.8 -5.8 -5.8 -5.7 0.2 35 Trans-Geranylgeraniol -5.9 -5.6 -5.7 -5.7 -5.7 0.1 36 Widdrol -5.7 -5.7 -5.7 -5.7 -5.7 0.0 37 Alpha-copaene -5.6 -5.6 -5.6 -5.6 -5.6 0.0 38 Alpha-cubebene -5.6 -5.6 -5.6 -5.6 -5.6 0.0 39 Bergamotene -5.6 -5.6 -5.6 -5.6 -5.6 0.0 40 Beta-caryophyllene -5.6 -5.6 -5.6 -5.6 -5.6 0.0 41 9-epicaryophyllene -5.6 -5.6 -5.6 -5.6 -5.6 0.0 42 (-)-beta-Chamigrene -5.6 -5.5 -5.6 -5.6 -5.6 0.0 43 Lilial -5.6 -5.6 -5.5 -5.6 -5.6 0.0 44 Zerumbone -5.6 -5.5 -5.5 -5.5 -5.5 0.0 45 Alpha-cadinol -5.5 -5.5 -5.5 -5.5 -5.5 0.0 46 Beta-selinene -5.5 -5.5 -5.5 -5.5 -5.5 0.0 47 Cyperene -5.5 -5.5 -5.5 -5.5 -5.5 0.0 GSC Biological and Pharmaceutical Sciences, 2025, 33(02), 267–279 272 48 Italicene -5.5 -5.5 -5.5 -5.5 -5.5 0.0 49 Tau-Muurolol -5.5 -5.5 -5.5 -5.5 -5.5 0.0 50 Viridiflorol -5.5 -5.5 -5.5 -5.5 -5.5 0.0 51 (-)-gamma-Cadinene -5.5 -5.3 -5.5 -5.5 -5.5 0.1 52 Alpha-humulene -5.5 -5.4 -5.4 -5.5 -5.5 0.1 53 Gallic acid -5.4 -5.5 -5.4 -5.5 -5.5 0.1 54 Aromadendrene -5.4 -5.4 -5.4 -5.4 -5.4 0.0 55 Alpha-bourbonene -5.3 -5.3 -5.3 -5.3 -5.3 0.0 56 Beta-longipinene -5.3 -5.3 -5.3 -5.3 -5.3 0.0 57 Beta-patchoulene -5.3 -5.3 -5.3 -5.3 -5.3 0.0 58 Beta-santalene -5.3 -5.3 -5.3 -5.3 -5.3 0.0 59 D-allose -5.3 -5.3 -5.3 -5.3 -5.3 0.0 60 Germacrene A -5.3 -5.3 -5.3 -5.3 -5.3 0.0 61 Isolongifolene -5.3 -5.3 -5.3 -5.3 -5.3 0.0 62 Protocatechuic acid -5.3 -5.3 -5.3 -5.3 -5.3 0.0 63 Viridiflorene -5.3 -5.3 -5.3 -5.3 -5.3 0.0 64 p-Camphorene -5.3 -5.2 -5.1 -5.3 -5.2 0.1 65 Beta-guaiene -5.2 -5.2 -5.2 -5.2 -5.2 0.0 66 Alpha-Pinene oxide -5.1 -5.1 -5.1 -5.1 -5.1 0.0 67 Beta-himachalene -5.1 -5.1 -5.1 -5.1 -5.1 0.0 68 Bornyl acetate -5.1 -5.1 -5.1 -5.1 -5.1 0.0 69 Thymol -5.1 -5.1 -5.1 -5.1 -5.1 0.0 70 Tribulin -5.1 -5.1 -5.1 -5.1 -5.1 0.0 71 6-epi-Shyobunol -5.1 -5.1 -5.1 -5.1 -5.1 0.0 72 Alpha-Terpinyl acetate -5 -5 -5 -5 -5.0 0.0 73 Beta-D-Xylopyranose -5 -5 -5 -5 -5.0 0.0 74 Trans-Pinocarveol -5 -5 -5 -5 -5.0 0.0 75 Trans-Verbenol -5 -5 -5 -5 -5.0 0.0 76 Linalyl acetate -5 -4.9 -4.9 -5 -5.0 0.1 77 Verbenone -4.9 -5 -4.9 -5 -5.0 0.1 78 Beta-farnesene -4.8 -4.8 -5.2 -4.8 -4.9 0.2 79 Chrysanthenone -4.9 -4.9 -4.9 -4.9 -4.9 0.0 80 Cis-Verbenol -4.9 -4.9 -4.9 -4.9 -4.9 0.0 81 6-Camphenone -4.9 -4.9 -4.9 -4.9 -4.9 0.0 82 Methyl salicylate -4.8 -4.9 -4.8 -4.9 -4.9 0.1 83 Alpha-terpineol -4.8 -4.8 -4.8 -4.8 -4.8 0.0 84 Beta-fenchol -4.8 -4.8 -4.8 -4.8 -4.8 0.0 85 Carvacrol -4.8 -4.8 -4.8 -4.8 -4.8 0.0 GSC Biological and Pharmaceutical Sciences, 2025, 33(02), 267–279 273 86 Carvone -4.8 -4.8 -4.8 -4.8 -4.8 0.0 87 Cis-Pinocamphone -4.8 -4.8 -4.8 -4.8 -4.8 0.0 88 Exo-Fenchol -4.8 -4.8 -4.8 -4.8 -4.8 0.0 89 Myrtenal -4.8 -4.8 -4.8 -4.8 -4.8 0.0 90 Trans-Sabinol -4.8 -4.8 -4.8 -4.8 -4.8 0.0 91 1-8-Cineole -4.8 -4.8 -4.8 -4.8 -4.8 0.0 92 Beta-bisabolene -4.5 -4.5 -4.5 -5.6 -4.8 0.6 93 o-Creosol -4.8 -4.7 -4.8 -4.7 -4.8 0.1 94 Perillene -4.9 -4.6 -4.6 -4.7 -4.7 0.1 95 Umbellulone -4.7 -4.7 -4.7 -4.7 -4.7 0.0 96 p-Cymen-8-ol -4.7 -4.7 -4.7 -4.6 -4.7 0.1 97 Pinocarvone -4.7 -4.7 -4.7 -4.6 -4.7 0.1 98 Terpinen-4-ol -4.7 -4.6 -4.7 -4.7 -4.7 0.1 99 Carvenone -4.7 -4.6 -4.6 -4.7 -4.7 0.1 100 Trans-Pinocamphone -4.6 -4.6 -4.7 -4.6 -4.6 0.1 101 (+)-trans-Limonene oxide -4.6 -4.6 -4.6 -4.6 -4.6 0.0 102 Alpha-campholenal -4.6 -4.6 -4.6 -4.6 -4.6 0.0 103 Borneol -4.6 -4.6 -4.6 -4.6 -4.6 0.0 104 Camphor -4.6 -4.6 -4.6 -4.6 -4.6 0.0 105 Isopinocamphone -4.6 -4.6 -4.6 -4.6 -4.6 0.0 106 p-Cymene -4.6 -4.6 -4.6 -4.6 -4.6 0.0 107 Pyrogallic acid -4.6 -4.6 -4.6 -4.6 -4.6 0.0 108 Tricyclene -4.6 -4.6 -4.6 -4.6 -4.6 0.0 109 Rosefuran -4.7 -4.5 -4.5 -4.5 -4.6 0.1 110 Alpha-terpinene -4.6 -4.5 -4.5 -4.5 -4.5 0.0 111 Linalool -4.5 -4.6 -4.3 -4.7 -4.5 0.2 112 (-)-cis-Limonene oxide -4.5 -4.5 -4.5 -4.5 -4.5 0.0 113 (+)-cis-Limonene oxide -4.5 -4.5 -4.5 -4.5 -4.5 0.0 114 (Z)-Chrysanthemol -4.5 -4.5 -4.5 -4.5 -4.5 0.0 115 Alpha-phellandren-8-ol -4.6 -4.6 -4.4 -4.4 -4.5 0.1 116 Beta-cyclocitral -4.5 -4.5 -4.5 -4.5 -4.5 0.0 117 Delta-3-carene -4.5 -4.5 -4.5 -4.5 -4.5 0.0 118 3-p-menthene -4.5 -4.5 -4.5 -4.5 -4.5 0.0 119 Undecan-2-one -4.3 -4.4 -4.6 -4.6 -4.5 0.2 120 Myrcene -4.6 -4.5 -4.6 -4.1 -4.5 0.2 121 Cis-sabinene hydrate -4.5 -4.4 -4.4 -4.4 -4.4 0.0 122 (-)-trans-Limonene oxide -4.4 -4.4 -4.4 -4.4 -4.4 0.0 123 Alpha-thujene -4.4 -4.4 -4.4 -4.4 -4.4 0.0 GSC Biological and Pharmaceutical Sciences, 2025, 33(02), 267–279 274 124 Beta-terpinene -4.4 -4.4 -4.4 -4.4 -4.4 0.0 125 Cis-p-menth-8-ene -4.4 -4.4 -4.4 -4.4 -4.4 0.0 126 Cuminal -4.4 -4.4 -4.4 -4.4 -4.4 0.0 127 Gamma-terpinene -4.4 -4.4 -4.4 -4.4 -4.4 0.0 128 Trans-thujone -4.4 -4.4 -4.4 -4.4 -4.4 0.0 129 D-limonene -4.4 -4.4 -4.3 -4.4 -4.4 0.1 130 Terpinolene -4.3 -4.4 -4.3 -4.4 -4.4 0.1 131 Alpha-phellandrene -4.3 -4.3 -4.3 -4.3 -4.3 0.0 132 Alpha-pinene -4.3 -4.3 -4.3 -4.3 -4.3 0.0 133 Beta-fenchene -4.3 -4.3 -4.3 -4.3 -4.3 0.0 135 Beta-pinene -4.3 -4.3 -4.3 -4.3 -4.3 0.0 136 Camphene -4.3 -4.3 -4.3 -4.3 -4.3 0.0 137 Carvotanacetone -4.3 -4.3 -4.3 -4.3 -4.3 0.0 138 Isoterpinolene -4.3 -4.3 -4.3 -4.3 -4.3 0.0 139 m-Cymene -4.3 -4.3 -4.3 -4.3 -4.3 0.0 140 Myrcenol -4.1 -4.4 -4.4 -4.3 -4.3 0.1 141 o-Cymene -4.3 -4.3 -4.3 -4.3 -4.3 0.0 142 Thuja-2-4(10)-diene -4.3 -4.3 -4.3 -4.3 -4.3 0.0 143 Toluene -4.3 -4.3 -4.3 -4.3 -4.3 0.0 144 Alpha-fenchene -4.2 -4.2 -4.2 -4.2 -4.2 0.0 145 Beta-ocimene -4.3 -4.3 -3.8 -4.3 -4.2 0.3 146 (Z)-Salvene -4.2 -4 -4.2 -4.2 -4.2 0.1 147 Lavandulol -4.1 -4.1 -4.1 -4.1 -4.1 0.0 148 Beta-Citronellene -4.5 -3.7 -3.7 -4.1 -4.0 0.4 149 Santolina triene -3.8 -3.8 -3.8 -3.8 -3.8 0.0 150 PEG reference ligand -3.4 -3.2 -3.2 -3.3 -3.3 0.1 Table 3 Binding energies, mean binding energies and standard deviation of the docked front-runners. S/N LIGANDS E 1 E 2 E 3 E 4 MEAN STANDARD DEVIATION 1 Gallocatechin -8.6 -8.6 -8.6 -8.6 -8.6 0.0 2 Robinetin -8.3 -8.2 -8.2 -8.2 -8.2 0.1 3 Isorhamnetin -8.1 -8.1 -8.1 -8.1 -8.1 0.0 4 Epicatechin-3-gallate -8.3 -8.2 -8.3 -7.3 -8.0 0.5 5 Apigenin -7.8 -7.8 -7.8 -7.8 -7.8 0.0 6 Luteolin -7.7 -7.7 -7.7 -7.7 -7.7 0.0 7 Epicatechin -7.6 -7.6 -7.5 -7.5 -7.6 0.1 GSC Biological and Pharmaceutical Sciences, 2025, 33(02), 267–279 275 8 Epigallocatechin-3-gallate -7.5 -7.5 -7.5 -7.5 -7.5 0.0 9 Kaempherol -7.4 -7.4 -7.4 -7.4 -7.4 0.0 10 Cianidanol -7.3 -7.3 -7.3 -7.3 -7.3 0.0 150 PEG reference ligand -3.4 -3.2 -3.2 -3.3 -3.3 0.1 Figure 1 The first nine front runner ligands on the table and the reference ligand PEG within the binding pocket of the selected protein 4IVV A B D C E F G H I