Eclet. Quim. 49 | e-1492, 2024 https://doi.org/10.26850/1678-4618.eq.v49.2024.e1492 ISSN 1678-4618 page 1/11 1Bowen University, Industrial Chemistry Programme, Iwo, Osun State, Nigeria. 2Beijing Institute of Technology, School of Chemistry and Chemical Engineering, Beijing, China. 3Precious Cornerstone University, Faculty of Pure and Applied Sciences, Ibadan, Nigeria. 4Covenant University, Department of Biochemistry, Ota, Ogun State, Nigeria. 5Ladoke Akintola University of Technology, Department of Pure and Applied Chemistry, Ogbomoso, Oyo State, Nigeria. 6Ekiti State University, Department of Chemistry, Ado-Ekiti, Nigeria. 7Federal University Oye-Ekiti, Department of Chemistry, Oye-Ekiti, Ekiti State, Nigeria. 8University of Ibadan, Department of Chemistry, Ibadan, Oyo State, Nigeria. 9Adeleke University, Department of Basic Sciences, Ede, Osun State, Nigeria. 10University of Jos, Department of Medical Laboratory Science, Jos, Nigeria. +Corresponding author: Oyebamiji Abel Kolawole, Phone: +234 08032493676, Email address: abeloyebamiji@gmail.com Original Article Predicting the biological activity of selected phytochemicals in Alsophila spinulosa leaves against 4-aminobutyrate-aminotransferase: A potential antiepilepsy agents Oyebamiji Abel Kolawole1+ , Olujinmi Faith Eniola1 , Akintelu Sunday Adewale2 , Adetuyi Babatunde3 , Ogunlana Olubanke4 , Semire Banjo5 , Akintayo Emmanuel Temitope1,6 , Akintayo Cecilia Olufunke1,7 , Babalola Jonathan Oyebamiji8 , Olawoye Bolanle Mary9 , Aworinde Juliana Oluwasayo10 Abstract The use of medicinal plants as an alternative mean of treating various diseases has drawn the attention of several researchers. The desire to find lasting solutions to epilepsy among humans increases every day. Thus, this work was aimed at investigating the potential capacity of the studied phytochemicals in Alsophila spinulosa against human 4-aminobutyrate-aminotransferase as well as to predict the nonbonding interactions involved in the studied complexes. In this work, ten compounds with biological activities were selected and studied using molecular docking method. The molecules selected obtained from A. spinulosa leaves were optimized and various descriptors that described the anti-4-aminobutyrate- aminotransferase features were obtained. More so, 2-(3,4-dihydroxyphenyl)-5,7- dihydroxy-3-(((2S,3R,4R,5R,6S)-3,4,5-trihydroxy-6-methyltetrahydro-2H-pyran-2- yl)oxy)-4H-chromen-4-one (compound 9) with highest binding affinity proved to have greater strength to inhibit 4-aminobutyrate-aminotransferase thereby downregulating epilepsy than other studied compounds and the reference drug (clobazam). The ADMET features of both compound 9 and clobazam were explored and reported. Article History Received May 06, 2023 Accepted October 23, 2023 Published January 03, 2024 Keywords 1. heterocycles; 2. binding sites; 3. ligands; 4. ADMET; 5. herbs. Section Editor Irlon Maciel Ferreira Highlights The descriptors that enhance the inhibiting activity of the studied ligands were observed. The amino acid residues involved in the interaction were investigated. Pharmacokinetic analysis on the ligand with highest binding affinity was examined. https://doi.org/10.26850/1678-4618.eq.v49.2024.e1492 https://ror.org/02avtbn34 https://ror.org/01skt4w74 https://ror.org/04fzaxn66 https://ror.org/00frr1n84 https://ror.org/043hyzt56 https://ror.org/043hyzt56 https://ror.org/02c4zkr79 https://ror.org/02q5h6807 https://ror.org/03wx2rr30 https://ror.org/03gnb6c23 https://ror.org/009kx9832 mailto:abeloyebamiji@gmail.com https://orcid.org/0000-0002-8932-6327 https://orcid.org/0000-0002-0655-4018 https://orcid.org/0000-0001-8919-3029 https://orcid.org/0000-0003-0294-3435 https://orcid.org/0000-0001-5781-592X https://orcid.org/0000-0002-4173-9165 https://orcid.org/0000-0001-8543-9554 https://orcid.org/0000-0002-6023-5405 https://orcid.org/0000-0002-1407-6677 https://orcid.org/0009-0008-2981-133X https://orcid.org/0009-0008-5623-0514 Original Article https://doi.org/10.26850/1678-4618.eq.v49.2024.e1492 Eclet. Quim. 49 | e-1492, 2024 ISSN 1678-4618 page 2/11 1. Introduction Traditional medicine has played a crucial role in boosting human health for years (Kebede et al., 2021). Many ground- breaking successes in recent therapeutic science depend greatly on natural/local resources (Shriram et al., 2018; Poulakou et al., 2018). Over the years, many medicinal agents of synthetic and natural products have been used to combat diseases and infections (Pitout 2008). The World Health Organization reports that more than 60% of developing countries still use herbal drugs originating from medicinal plants as alternative medicine (Duraipandiyan et al., 2006; Mishra et al., 2013; Vaou et al., 2021). One of the most common neurological syndromes in the world is epilepsy, which remains in third position among the diseases that affect people with old age (Hirtz et al., 2007; Werhahn 2009; Queeny et al., 2018; Dunkel et al., 2023). Its rate of increase has been observed to be high in infants and aged people (Hesdorffer et al., 2011; Jeżowska-Jurczyk et al., 2023). As stated by Gagliano et al. (2018), more than 45 million people have been reported to have epilepsy. Antiepileptic agents are one way of combating epilepsy; nevertheless, the activities of epilepsy in 80% of patients remain unrestrained. The tactics behind the treatment failure of epilepsy still seem to be unclear; however, the fight against epilepsy by scientists all over the world has been observed to be increasing (Kwan and Brodie, 2000; Bartolini et al., 2023). According to Mukhopadhyay et al. (2012), epilepsy is a combination of many syndromes, each of which has various warning signs such as intermittent irregular electrical activity in the brain. Gamma-aminobutyrate-aminotransferase played a significant role in the degradation of the inhibitory neurotransmitter. It has been the target of several antiepileptic drug-like compounds (Choi and Churchich, 1986). 4- Aminobutyrate-aminotransferase was observed to have the ability to transfer nitrogenous groups and catalyze the combination of 4-aminobutanoate and 2-oxoglutarate, resulting in succinate semialdehyde and L-glutamate (Shen et al., 2023; Kim and Yoon, 2023; Zhang et al., 2022; Gao et al., 2022; Yasuhide et al., 1999). Alsophila spinulosa is a plant with much biological importance. According to Morton (1971), it is a fern that looks like a tree. It grows in humus soil and can be found in countries such as China, Japan, and India. In China, it is used to treat various ailments, including rheumatism, helminthic infections, cough, and gout (Abbas et al., 2016). More so, in American continents, it is used in teas and as poultices for treating some ailments (Irene et al., 2023). It belongs to the Cyatheaceae family and is commonly called the flying spider-monkey tree fern (Chiang et al., 1994; Lanza et al., 2022). The trunk of A. spinulosa can grow taller than 5 m (Chinese DmgDictionay, 1985; Yan et al., 2022). It is a fern and it possesses the potential ability to inhibit tumors (Kan, 1986). Therefore, this work aims to evaluate the potential inhibitory properties of selected phytochemicals present in A. spinulosa against human 4-aminobutyrate-aminotransferase and investigate the potential nonbonding interaction involved in the studied complexes and their efficiency. 2. Methodology 2.1 Software and hardware The optimization of the studied compounds was accomplished using density functional theory via Spartan ’14 software (Semire et al., 2017). The binding affinity and nonbonding interactions between selected phytochemicals in A. spinulosa leaves and 4-aminobutyrate-aminotransferase were investigated via docking study using Pymol for treating enzyme, Discovery Studio software for viewing the interaction between the docked complexes, AutoDock tool for locating a binding site in the studied protein and AutoDock Vina software for docking calculation. The names and the two-dimensional structures of the selected phytochemicals are shown in Table 1. Table 1. Studied phytochemicals obtained from A. spinulosa. Structures IUPAC Names 1 5,7-dihydroxy-2-(4-hydroxyphenyl)-4H-chromen-4-one 2 7-(((2S,3R,4S,5S,6R)-3-(((2S,3R,4R)-3,4-dihydroxy-4- (hydroxymethyl)tetrahydrofuran-2-yl)oxy)-4,5-dihydroxy-6- (hydroxymethyl)tetrahydro-2H-pyran-2-yl)oxy)-5-hydroxy-2-(4- hydroxyphenyl)-4H-chromen-4-one https://doi.org/10.26850/1678-4618.eq.v49.2024.e1492 https://doi.org/10.26850/1678-4618.eq.v49.2024.e1492 Original Article https://doi.org/10.26850/1678-4618.eq.v49.2024.e1492 Eclet. Quim. 49 | e-1492, 2024 ISSN 1678-4618 page 3/11 3 (3S,8S,9S,10R,13R,14S,17R)-17-((2R,5R)-5-ethyl-6-methylheptan-2-yl)- 10,13-dimethyl-2,3,4,7,8,9,10,11,12,13,14,15,16,17-tetradecahydro-1H- cyclopenta[a]phenanthren-3-ol 4 (1S,3R,4R,5R)-3-(((E)-3-(3,4-dihydroxyphenyl)acryloyl)oxy)-1,4,5- trihydroxycyclohexanecarboxylic acid 5 (2R,3R,4S,5S,6R)-2-(((3S,8S,9S,10R,13R,14S,17R)-17-((2R,5R)-5-ethyl-6- methylheptan-2-yl)-10,13-dimethyl-2,3,4,7,8,9,10,11,12,13,14,15,16,17- tetradecahydro-1H-cyclopenta[a]phenanthren-3-yl)oxy)-6- (hydroxymethyl)tetrahydro-2H-pyran-3,4,5-triol 6 2-((3S,3aS,5aR,5bR,7aS,11aS,11bR,13aR,13bS)-5a,5b,8,8,11a,13b- hexamethylicosahydro-1H-cyclopenta[a]chrysen-3-yl)propan-2-ol 7 2-(3,4-dihydroxyphenyl)-5,7-dihydroxy-6-((2S,3R,4R,5S,6R)-3,4,5- trihydroxy-6-(hydroxymethyl)tetrahydro-2H-pyran-2-yl)-4H-chromen-4- one 8 2-(3,4-dihydroxyphenyl)-5,7-dihydroxy-4H-chromen-4-one https://doi.org/10.26850/1678-4618.eq.v49.2024.e1492 https://doi.org/10.26850/1678-4618.eq.v49.2024.e1492 Original Article https://doi.org/10.26850/1678-4618.eq.v49.2024.e1492 Eclet. Quim. 49 | e-1492, 2024 ISSN 1678-4618 page 4/11 9 2-(3,4-dihydroxyphenyl)-5,7-dihydroxy-3-(((2S,3R,4R,5R,6S)-3,4,5- trihydroxy-6-methyltetrahydro-2H-pyran-2-yl)oxy)-4H-chromen-4-one 10 5,7-dihydroxy-2-(4-hydroxyphenyl)-8-((2S,3R,4R,5S,6R)-3,4,5-trihydroxy- 6-(hydroxymethyl)tetrahydro-2H-pyran-2-yl)-4H-chromen-4-one Source: Retrieved from Storici et al., (2004). 2.2. Receptor (target) The studied receptor (4-aminobutyrate-aminotransferase with protein data bank code: 1OHV) used in this work was repossessed from the recognized database (protein data bank) (Storici et al., 2004). 2.3. Studied pharmacophore Ten pharmacophores from A. spinulosa leaves were selected and prepared for a molecular docking study (Chen et al., 2008). The selected compounds were chosen based on descriptions from literature (Vijayakumar et al., 2018) and the compounds were obtained from a recognized database (https://pubchem.ncbi.nlm.nih.gov/). 2.4. Studied protein preparation The studied receptor was retrieved from a protein data bank and a series of small molecules such as acetate ion (ACT), pyridoxal-5'-phosphate (PLP) and FE2/S2 (inorganic) cluster (FES) as well as water molecules were downloaded with it. The necessary factors for the downloaded receptor (resolution, R- value free, and R-value work) were observed to be 2.30, 0.221 and 0.118 Å, respectively. The studied receptor was treated using Pymol v 1.7.4 software and both small molecules such as ACT, PLP and FES as well as water molecules were removed and saved the clean 4-Aminobutyrate-Aminotransferase in .pdb format (El Fadili et al., 2022a; Erazua et al., 2023). The binding site in clean/treated 4-aminobutyrate-aminotransferase (PDB ID:1ohv) was predicted using AutoDockTools-1.5.6 (Waziri et al., 2023; El Fadili et al., 2022b). The calculation and analysis of site map of the studied receptor revealed the likely binding site and the figure for center (center_x = 5.638; center_y = 3.578 and center_z = 21.309) as well as the size of the site area (size_x = 62; size_y = 62 and size_z = 84) were reported accordingly. The docking calculation was executed using AutoDock Vina software to calculate binding affinity between the studied complexes. 2.5. ADMET investigation This study was executed using ADMETsar 2.0 online software (Oyebamiji et al., 2022). The ligands with higher binding affinity were investigated and absorption, distribution, metabolism, excretion, and toxicity (ADMET) factors such as physicochemical property, medicinal chemistry, absorption, distribution, metabolism, excretion, toxicity, environmental toxicity, tox21 pathway, and toxicophoric rule were considered. 3. Results and Discussion 3.1. Calculated descriptors The descriptors obtained from optimization of the phytochemicals of A. spinulosa leaves revealed the activities of the studied medicinal plants. The descriptors obtained are reported in Table 2. According to Adeoye et al. (2022), the higher the highest occupied molecular orbital energy (EHOMO), the better the tendency of the compound to release electrons to the nearby molecules. The unit for highest occupied molecular orbital energy was electron volt (eV) and as shown in Table 2, (1S,3R,4R,5R)-3-(((E)-3-(3,4- dihydroxyphenyl)acryloyl)oxy)-1,4,5- trihydroxycyclohexanecarboxylic acid (compound 4) possess the potential strength to react better than other studied compounds. Also, the lower the lowest unoccupied molecular orbital energy (ELUMO), the greater the strength of molecules to receive electrons from the compound that can give it out; thus, 2-(3,4- dihydroxyphenyl)-5,7-dihydroxy-3-(((2S,3R,4R,5R,6S)-3,4,5- trihydroxy-6-methyltetrahydro-2H-pyran-2-yl)oxy)-4H-chromen- 4-one (compound 9) showed potential strength to receive electron from nearby compounds thereby brings about better interactions. https://doi.org/10.26850/1678-4618.eq.v49.2024.e1492 https://doi.org/10.26850/1678-4618.eq.v49.2024.e1492 Original Article https://doi.org/10.26850/1678-4618.eq.v49.2024.e1492 Eclet. Quim. 49 | e-1492, 2024 ISSN 1678-4618 page 5/11 Other calculated descriptors (band gap, dipole moment, molecular weight (≤ 500 amu) ovality, log P (≤5), polarizability, hydrogen bond donor (HBD) (≤5) and hydrogen bond acceptor (HBA) (≤10)) are reported in Table 2. Table 2. The selected descriptors obtained from A. spinulosa leaves. EHOMO (eV) ELUMO (eV) EG (eV) DM (Debye) MW (amu) AREA (Å2) OVA LOG P POL (Å3) HBD HBA 1 –6.06 –1.60 4.46 4.39 270.24 266.07 1.38 –2.38 60.79 3 5 2 –6.06 –1.64 4.42 12.60 564.49 517.78 1.69 –5.68 81.15 8 14 3 –6.16 0.71 6.87 2.11 414.71 493.59 1.63 8.14 79.85 1 1 4 –5.74 –1.60 4.14 2.03 354.31 350.48 1.54 –2.42 66.53 6 7 5 –6.21 0.69 6.90 5.94 576.85 628.71 1.77 6.40 90.98 4 6 6 –6.79 1.77 8.56 1.76 428.74 460.39 1.51 8.49 79.90 1 1 7 –5.87 –1.68 4.19 4.35 448.38 400.84 1.55 –6.39 72.21 8 11 8 –5.85 –1.64 4.21 7.55 286.23 273.50 1.39 –3.46 61.40 3 6 9 –5.86 –1.74 4.12 11.36 448.38 404.80 1.55 –5.68 72.50 7 11 10 –6.10 –1.67 4.43 5.06 432.38 384.94 1.50 –5.31 71.61 7 10 EG: Energy gap; DM: Dipole moment; MW: Molecular Weight; OVA: Ovality; LOG P: Lipophilicity; POL: Polarozability; HBD: Hydrogen bond donor; HBA: Hydrogen Bond Acceptor. 3.2. Molecular docking investigation The docking of selected phytochemicals in A. spinulosa leaves was executed in 4-aminobutyrate-aminotransferase. Ten phytochemicals were docked into the active site of the 4- aminobutyrate-aminotransferase with PDB ID 1ohv and binding affinity, residue involved in the interactions as well as types of nonbonding interaction involved in the docked complexes were observed. The report obtained for studied docked complexes were: compound 1 (–33.472 kJ mol–1; Lys442, Asp441, Asp415, Arg404, Met186, Arg222; conventional hydrogen bond, carbon hydrogen bond, pi-cation, pi-anion, pi-alkyl); compound 2 (–35.564 kJ mol– 1; Cys169, Phe161, Arg156, Pro178, Arg152, Arg349, Tyr180; conventional hydrogen bond, pi-cation, pi-sulfur, pi-pi stacked, pi- alkyl); compound 3 (–34.7272 kJ mol–1; Lys145, Pro178, Trp215, Met149, Phe144, Phe148, Phe213, Cys177, Gly176; carbon hydrogen bond, alkyl, pi-alkyl); compound 4 (–32.6352 kJ mol–1; Phe148, Arg349, Tyr180, Pro178, Arg156, Arg152, Gly176; conventional hydrogen bond, unfavorable donor-donor, pi-pi stacked, pi-alkyl); compound 5 (–33.472 kJ mol–1; Val231, Leu223, Leu227, Gly409, Ala381; conventional hydrogen bond, unfavorable acceptor-acceptor, alkyl) (Figs. 1–9). Moreover, compound 6 (–35.1456 kJ mol–1; Val88, Leu363, Tyr79, Gln71, Ile75, Val85, Leu84, Tyr49; conventional hydrogen bond, pi-alkyl, alkyl); compound 7 (–33.0536 kJ mol–1; Glu270, Ile426, Gly440, Asn423, Arg430; conventional hydrogen bond, unfavorable donor-donor, alkyl); compound 8 (–33.0536 kJ mol–1; Lys442, Ser443, Cys439, Asp415, Asp441, Arg404, Pro221, Phe220, Met186, Arg222; conventional hydrogen bond, carbon hydrogen bond, pi-cation, pi-anion, pi-alkyl); compound 9 (-35.9824 kJ mol–1; Arg152, Pro178, Phe148, Tyr180, Gly176, Arg349; conventional hydrogen bond, carbon hydrogen bond, pi- cation, pi-pi stacked, pi-stacked); compound 10 (–33.0536 kJ mol– 1; Leu355, Ile131, Pro344, Gln129, Leu130, Arg343; conventional hydrogen bond, carbon hydrogen bond, unfavorable donor-donor, unfavorable acceptor-acceptor, pi-sigma, alkyl). According to the report shown in Table 3, 2-(3,4- dihydroxyphenyl)-5,7-dihydroxy-3-(((2S,3R,4R,5R,6S)-3,4,5- trihydroxy-6-methyltetrahydro-2H-pyran-2-yl)oxy)-4H-chromen- 4-one (compound 9) proved to be superior based on the docking score of –35.9824 kJ mol–1 when compared to other studied compounds as well as the reference drug (clobazam). Oyeneyin et al. (2022) reported that lower binding affinity value of any molecule is an indication that such compound has a higher potential ability to inhibit than other studied compounds; thus, the selection of compound 9 as superior to other studied compound was considered appropriate. As shown in Fig. 9, series of nonbonding interactions were observed in the interaction between 2-(3,4- dihydroxyphenyl)-5,7-dihydroxy-3-(((2S,3R,4R,5R,6S)-3,4,5- trihydroxy-6-methyltetrahydro-2H-pyran-2-yl)oxy)-4H-chromen- 4-one (compound 9) and 4-aminobutyrate-aminotransferase; the nonbonding interaction involved wee conventional hydrogen bond, carbon hydrogen, pi-pi stacked and pi-alkyl. The conventional hydrogen bond was observed between Tyr180 and hydrogen (H14), Gly176 and hydrogen (H11) as well as Arg349 and oxygen (O7), which showed the specificity of compound 9 in the active site of 4-aminobutyrate-aminotransferase. Also, the hydrogen bond formed by compound 9 with the studied receptor was observed to enhance the exactness of calculated binding affinity (Fig. 10). Also, carbon hydrogen bond was observed between Pro178 and oxygen (O1); pi-cation interaction was observed between Arg349 and the aromatic ring attached to the parent compound; its presence between Arg349 and Pi-electron cloud in the aromatic compound was observed to enhance the lowest calculated binding affinity value when compared to the binding for other studied compounds as well as the binding score for the reference drug. The result also revealed the level of bioavailability, selectivity, steadiness, and lipophilicity of 2-(3,4- dihydroxyphenyl)-5,7-dihydroxy-3-(((2S,3R,4R,5R,6S)-3,4,5- trihydroxy-6-methyltetrahydro-2H-pyran-2-yl)oxy)-4H-chromen- 4-one (compound 9) to be more desirable when compares to that of the other studied compounds and clobazam (referenced drug). The presence of pi-pi stacked (Phe148 and the electron cloud of the aromatic ring of the parent compound) and pi-alkyl (Pro178 and Arg152 attracted to the electron cloud of the aromatic ring of the studied compound) interactions also augmented the accomplishment of lowest binding score by compound 9 when compared to other studied compounds (Fig. 11). Yan et al. (2022) investigated the activity of A. spinulosa leaves as potential anti-Alzheimer disease agents. It was observed that the polyphenols isolated from A. spinulosa leaves were excellent antioxidant agents and a potential ingredient for the alleviation of Alzheimer disease. Therefore, their report agreed well with the work carried out in this study as antiepilepsy agents. Also, the activity of Alsophila spp. against Gram positive and negative bacteria using the Kirby–Bauer disc diffusion method was investigated by Longtine and Tejedor (2017). It was observed that ethanolic extract of Alsophila spp. proved to be more active again Gram positive than Gram negative bacteria. The activity of these plants as anti-Gram positive bacteria goes in line with the A. spinulosa as antiepilepsy. https://doi.org/10.26850/1678-4618.eq.v49.2024.e1492 https://doi.org/10.26850/1678-4618.eq.v49.2024.e1492 Original Article https://doi.org/10.26850/1678-4618.eq.v49.2024.e1492 Eclet. Quim. 49 | e-1492, 2024 ISSN 1678-4618 page 6/11 Table 3. Calculated binding score. Binding Affinity (kJ mol–1) Residues involved in the interactions Types of Nonbonding interaction involved 1 –33.472 Lys442, Asp441, Asp415, Arg404, Met186, Arg222 Conventional hydrogen bond, carbon hydrogen bond, pi- cation, pi-anion, pi-alkyl 2 –35.564 Cys169, Phe161, Arg156, Pro178, Arg152, Arg349, Tyr180, Conventional hydrogen bond, pi-cation, pi-sulfur, pi-pi stacked, pi-alkyl 3 –34.7272 Lys145, Pro178, Trp215, Met149, Phe144, Phe148, Phe213, Cys177, Gly176 Carbon hydrogen bond, alkyl, pi-alkyl 4 –32.6352 Phe148, Arg349, Tyr180, Pro178, Arg156, Arg152, Gly176 Conventional hydrogen bond, unfavorable donor-donor, pi-pi stacked, pi-alkyl 5 –33.472 Val231, Leu223, Leu227, Gly409, Ala381 Conventional hydrogen bond, unfavorable acceptor- acceptor, alkyl 6 –35.1456 Val88, Leu363, Tyr79, Gln71, Ile75, Val85, Leu84, Tyr49 Conventional hydrogen bond, pi-alkyl, alkyl 7 –33.0536 Glu270, Ile426, Gly440, Asn423, Arg430 Conventional hydrogen bond, unfavorable donor-donor, alkyl 8 –33.0536 Lys442, Ser443, Cys439, Asp415, Asp441, Arg404, Pro221, Phe220, Met186, Arg222 Conventional hydrogen bond, carbon hydrogen bond, pi- cation, pi-anion, pi-alkyl 9 –35.9824 Arg152, Pro178, Phe148, Tyr180, Gly176, Arg349 Conventional hydrogen bond, carbon hydrogen bond, pi- cation, pi-pi stacked, pi-stacked 10 –33.0536 Leu355, Ile131, Pro344, Gln129, Leu130, Arg343 Conventional hydrogen bond, carbon hydrogen bond, unfavorable donor-donor, unfavorable acceptor-acceptor, pi- sigma, alkyl Clobazam –31.7984 - - Figure 1. 2D structures of interaction between compound 1 and 4- aminobutyrate-aminotransferase (PDB ID: 1ohv). Figure 3. 2D structures of interaction between compound 3 and 4- aminobutyrate-aminotransferase (PDB ID: 1ohv). Figure 2. 2D structures of interaction between compound 2 and 4- aminobutyrate-aminotransferase (PDB ID: 1ohv). Figure 4. 2D structures of interaction between compound 4 and 4- aminobutyrate-aminotransferase (PDB ID: 1ohv). https://doi.org/10.26850/1678-4618.eq.v49.2024.e1492 https://doi.org/10.26850/1678-4618.eq.v49.2024.e1492 Original Article https://doi.org/10.26850/1678-4618.eq.v49.2024.e1492 Eclet. Quim. 49 | e-1492, 2024 ISSN 1678-4618 page 7/11 Figure 5. 2D structures of interaction between compound 5 and 4- aminobutyrate-aminotransferase (PDB ID: 1ohv). Figure 6. 2D structures of interaction between compound 6 and 4- aminobutyrate-aminotransferase (PDB ID: 1ohv). Figure 7. 2D structures of interaction between compound 7 and 4- aminobutyrate-aminotransferase (PDB ID: 1ohv). Figure 8. 2D structures of interaction between compound 8 and 4- aminobutyrate-aminotransferase (PDB ID: 1ohv). Figure 9. 2D structures of interaction between compound 9 and 4- aminobutyrate-aminotransferase (PDB ID: 1ohv) https://doi.org/10.26850/1678-4618.eq.v49.2024.e1492 https://doi.org/10.26850/1678-4618.eq.v49.2024.e1492 Original Article https://doi.org/10.26850/1678-4618.eq.v49.2024.e1492 Eclet. Quim. 49 | e-1492, 2024 ISSN 1678-4618 page 8/11 Figure 10. 2D structures of interaction between compound 10 and 4-aminobutyrate-aminotransferase (PDB ID: 1ohv). Figure 11. 3D structure of 2-(3,4-dihydroxyphenyl)-5,7-dihydroxy- 3-(((2S,3R,4R,5R,6S)-3,4,5-trihydroxy-6-methyltetrahydro-2H- pyran-2-yl)oxy)-4H-chromen-4-one (compound 9). 3.3. Pharmacokinetic analysis The calculated ADMET features were obtained using ADMETsar (Cheng et al., 2012). The ADMET properties compound with the lowest binding score (compound 9) and the reference drug (clobazam) were investigated and the result for each compound are shown in Tables 4 and 5. The ADMET properties obtained for compound 9 were in a close range to the properties obtained for the reference drug. This indicates that 2-(3,4- dihydroxyphenyl)-5,7-dihydroxy-3-(((2S,3R,4R,5R,6S)-3,4,5- trihydroxy-6-methyltetrahydro-2H-pyran-2-yl)oxy)-4H-chromen- 4-one (compound 9) possess a greater attribute of a drug to inhibit 4-aminobutyrate-aminotransferase thereby downregulate epilepsy. Table 4. Pharmacokinetic prediction for compound 9. ADMET Predicted Profile --- Classification Model Result Probability Absorption Blood-brain barrier BBB- 0.7568 Human intestinal absorption HIA+ 0.9051 Caco-2 permeability Caco2- 0.7493 P-glycoprotein substrate Substrate 0.6415 P-glycoprotein inhibitor Noninhibitor 0.8740 Noninhibitor 0.7784 Renal organic cation transporter Noninhibitor 0.9396 Distribution Subcellular localization Mitochondria 0.7163 Metabolism CYP450 2C9 substrate Nonsubstrate 0.7557 CYP450 2D6 substrate Nonsubstrate 0.9171 CYP450 3A4 substrate Nonsubstrate 0.6312 CYP450 1A2 inhibitor Noninhibitor 0.5306 CYP450 2C9 inhibitor Noninhibitor 0.8538 CYP450 2D6 inhibitor Noninhibitor 0.9547 CYP450 2C19 inhibitor Noninhibitor 0.8339 CYP450 3A4 inhibitor Noninhibitor 0.7109 CYP inhibitory promiscuity Low CYP inhibitory promiscuity 0.5648 Human ether-a-go-go-related gene inhibition Weak inhibitor 0.9846 Noninhibitor 0.8181 AMES toxicity Non-AMES toxic 0.9319 Carcinogens Noncarcinogens 0.9461 Fish toxicity High FHMT 0.9657 Tetrahymena pyriformis toxicity High TPT 0.9945 https://doi.org/10.26850/1678-4618.eq.v49.2024.e1492 https://doi.org/10.26850/1678-4618.eq.v49.2024.e1492 Original Article https://doi.org/10.26850/1678-4618.eq.v49.2024.e1492 Eclet. Quim. 49 | e-1492, 2024 ISSN 1678-4618 page 9/11 Honey bee toxicity High HBT 0.6560 Biodegradation Not biodegradable 0.9073 Acute oral toxicity III 0.5184 Carcinogenicity (three-class) Nonrequired 0.6170 ADMET Predicted Profile --- Regression Model Value Unit Absorption Aqueous solubility –3.4974 LogS Caco-2 permeability –0.3114 LogPapp, cm s–1 Rat acute toxicity 2.5458 LD50, mol kg–1 Fish toxicity 0.6766 pLC50, mg L–1 Tetrahymena pyriformis toxicity 0.8401 pIGC50, ug L–1 Table 5. Pharmacokinetic prediction for Clobazam. ADMET Predicted Profile --- Classification Model Result Probability Absorption Blood-brain barrier BBB+ 0.9904 Human intestinal absorption HIA+ 0.9900 Caco-2 permeability Caco2+ 0.7487 P-glycoprotein substrate Nonsubstrate 0.5733 P-glycoprotein inhibitor Noninhibitor 0.5462 Noninhibitor 0.9204 Renal organic cation transporter Noninhibitor 0.7373 Distribution Subcellular localization Mitochondria 0.4586 Metabolism CYP450 2C9 substrate Nonsubstrate 0.7058 CYP450 2D6 substrate Nonsubstrate 0.8607 CYP450 3A4 substrate Substrate 0.6871 CYP450 1A2 inhibitor Noninhibitor 0.6829 CYP450 2C9 inhibitor Noninhibitor 0.5296 CYP450 2D6 inhibitor Noninhibitor 0.8908 CYP450 2C19 inhibitor Noninhibitor 0.5791 CYP450 3A4 inhibitor Inhibitor 0.7008 CYP inhibitory promiscuity Low CYP inhibitory promiscuity 0.5308 Excretion Toxicity Human ether-a-go-go-related gene inhibition Weak inhibitor 0.9896 Noninhibitor 0.8651 AMES toxicity Non-AMES toxic 0.9132 Carcinogens Noncarcinogens 0.7846 Fish toxicity High FHMT 0.9713 Tetrahymena pyriformis toxicity High TPT 0.9399 Honey bee toxicity Low HBT 0.9163 Biodegradation Not biodegradable 1.0000 Acute oral toxicity IV 0.6201 Carcinogenicity (three-class) Nonrequired 0.5725 ADMET Predicted Profile --- Regression Absorption Aqueous solubility –4.5627 LogS Caco-2 permeability 1.8526 LogPapp, cm s–1 Rat acute toxicity 1.7313 LD50, mol kg–1 Fish toxicity 1.0749 pLC50, mg L–1 Tetrahymena pyriformis toxicity 0.8911 pIGC50, ug L–1 4. Conclusions Ten molecular compounds obtained from A. spinulosa leaves were investigated using in silico approach. The assessment of the potential inhibitory properties of selected phytochemicals present in A. spinulosa against human 4-aminobutyrate- aminotransferase and exploration of the potential nonbonding interaction involved in the studied complexes and their efficiency were accomplished in this work. The descriptors obtained from the optimized phytochemicals revealed that the studied medicinal plant have potential antiepileptic capacity. Moreover, the selected phytochemicals and the studied 4-aminobutyrate- aminotransferase (PDB ID: 1ohv), which were subjected to docking study, resulted into series of binding scores to expose the inhibiting capability of each compound. Compound 9 (2-(3,4- dihydroxyphenyl)-5,7-dihydroxy-3-(((2S,3R,4R,5R,6S)-3,4,5- https://doi.org/10.26850/1678-4618.eq.v49.2024.e1492 https://doi.org/10.26850/1678-4618.eq.v49.2024.e1492 Original Article https://doi.org/10.26850/1678-4618.eq.v49.2024.e1492 Eclet. Quim. 49 | e-1492, 2024 ISSN 1678-4618 page 10/11 trihydroxy-6-methyltetrahydro-2H-pyran-2-yl)oxy)-4H- chromen-4-one) proved to possess highest binding strength to inhibit 4-aminobutyrate-aminotransferase than other selected phytochemicals in A. spinulosa leaves and the reference drug thereby down-regulating epilepsy. The pharmacokinetic features calculated for compound 9 and clobazam (reference drug) revealed that compound 9 (2-(3,4-dihydroxyphenyl)-5,7- dihydroxy-3-(((2S,3R,4R,5R,6S)-3,4,5-trihydroxy-6- methyltetrahydro-2H-pyran-2-yl)oxy)-4H-chromen-4-one) have superior characteristic to inhibit 4-aminobutyrate- aminotransferase than other selected studied phytochemicals obtained from A. spinulosa leaves, thereby hindering the operation of epilepsy in human. These findings may open door for the design and development of library of efficient 2-(3,4- dihydroxyphenyl)-5,7-dihydroxy-3-(((2S,3R,4R,5R,6S)-3,4,5- trihydroxy-6-methyltetrahydro-2H-pyran-2-yl)oxy)-4H- chromen-4-one-based drug-like compounds as potential antiepileptic agent. Authors’ contributions Conceptualization: Oyebamiji, A. K.; Data curation: Olujinmi, F. E.; Formal Analysis: Akintelu, S. A.; Funding acquisition: Not applicable; Investigation: Adetuyi, B. O.; Ogunlana, O. 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