Virtual Screening of Anti-HIV Leads from Mayana (Coleus scutellarioides Benth.) Phytoconstituents

Abstract

While some Coleus species have demonstrated anti-HIV activity, the potential of Mayana (Coleus scutellarioides Benth.) remains largely unexplored. This study therefore aimed to investigate the anti-HIV potential of phytoconstituents from Mayana using in silico methods. Phytochemicals from Mayana were identified using gas chromatography–mass spectrometry and their binding affinity against HIV-1 integrase (IN), protease (PR), and reverse transcriptase (RT) were evaluated through molecular docking simulations. In this work, a total of 32 individual compounds were identified. Stigmasterol was found to have the highest binding affinity to HIV IN (−8.571 kcal/mol) and HIV PR (−10.250 kcal/mol), whereas caryophyllene showed the highest affinity to HIV RT (−9.625 kcal/mol). These compounds also demonstrated multitarget interactions, suggesting potential inhibitory effects. However, compared with synthetic drugs such as amprenavir (−9.421 kcal/mol for PR), raltegravir (−9.825 kcal/mol for IN), and nevirapine (−9.748 kcal/mol for RT), the phytoconstituents had lower binding affinities. Pharmacokinetic predictions revealed that the top-ranked phytochemicals conform to Lipinski's Rule of Five, indicating favorable drug-like properties. Overall, Mayana contains bioactive phytoconstituents with promising affinity for key HIV-1 enzymes, supporting the potential of Mayana as a source of novel anti-HIV leads. However, further in vitro and in vivo studies are needed to confirm the efficacy, safety, and pharmacokinetic profile.

Keywords

Mayana - HIV - molecular docking - phytochemicals - antiviral potential

Introduction

The human immunodeficiency virus (HIV) remains a major global health challenge, with millions affected worldwide. Despite significant advancements in antiretroviral therapy (ART), HIV remains incurable and requires lifelong treatment to suppress viral replication. Although ART effectively suppresses viral replication, its utility is compromised by drug resistance, adverse effects, and accessibility challenges, particularly in resource-limited settings. These issues highlight the need for alternative or complementary therapeutic strategies, particularly those derived from natural sources. As a result, some people turn to natural products and herbal medicines, which are often perceived as safer and having fewer undesirable effects than synthetic drugs.[1]

ART is associated with a range of adverse effects that can significantly impair patient adherence. Commonly reported side effects, including nausea, dizziness, fatigue, difficulty in concentration, and diarrhea, are significant factors influencing treatment compliance.[2] Other frequent complications encompass anemia, hepatotoxicity, hypertriglyceridemia, and peripheral neuropathy, as well as allergic reactions like skin rashes and itching.[3] Furthermore, the development of drug resistance to antiretroviral medications remains a critical concern, especially in patients on long-term regimens.[4] Although the prevalence of resistance has decreased with modern ART, its prevention is essential to ensure sustained treatment success and preserve future therapeutic options.

Herbal medicine and remedies are proven to be beneficial as a treatment for HIV infections. The use of an herbal remedy was proven effective in treating HIV infection by improving clinical features and laboratory results.[5] Also, herbal medicines were used to treat infections secondary to HIV, but can also be used to reduce the side effects of antiretroviral drugs and to provide an overall positive effect on well-being.[6] Although antiretroviral drugs produce a potent and immediate improvement in CD4 cell counts, Chinese herbal medicine produces a steady rise and can provide a higher CD4 cell count increase than drugs alone.[7] These studies highlight the contribution and benefits that herbal medicine may provide when considering herbal medicine as an option in the treatment of HIV.

Moreover, species from the Coleus genus have shown inhibitory effects against HIV, which is primarily attributed to diterpenes and polyphenolic compounds.[8] [9] [10] While certain members like Coleus forskohlii and Coleus parvifolius have been studied for their anti-HIV activity, research on Mayana (Coleus scutellarioides Benth.) remains limited. Mayana is widely available in the Philippines. Mayana is an ornamental plant that is abundant in the Philippines and has been reported to be ethnobotanically used as an herbal medicine for various conditions and diseases.[11] [12] [13] [14] [15] Given the documented anti-HIV activity in some Coleus species, Mayana may also possess similar bioactivity. However, published studies directly investigating its efficacy against HIV are scarce. Traditional experimental methods, which are often resource-intensive and time-consuming, further limit research in this area. To bridge this gap, computational approaches such as molecular docking offer a viable and efficient alternative.

Molecular docking is an in silico approach to virtually simulate interactions between two molecules.[16] This tool can be used to investigate the mechanisms underlying molecular recognition, interaction, and also to identify the conformation of a receptor–ligand complex.[17] It has been an integral tool for drug discovery, especially in lead identification. In natural product research, molecular docking has gained prominence as a computational tool that predicts interactions between phytochemicals and disease targets, providing valuable insights for further studies and natural product development.[18] This approach offers a more efficient alternative to traditional drug discovery processes, reducing attrition rates by prioritizing promising candidates before costly and time-consuming experimental validation.[18]

As such, this study aims to identify the phytoconstituents present in the crude extracts of Mayana leaves and explore the potential of these phytoconstituents against target HIV enzymes using molecular docking software and a virtual screening approach. By investigating Mayana's bioactive compounds, this study seeks to contribute to the growing field of plant-based drug discovery for HIV treatment and encourage further experimental validation.

Materials and Methods

Research Design

This study employs an exploratory laboratory experimental design to identify the bioactive phytochemicals present in Mayana. Furthermore, the potential of these phytochemicals to interact with major HIV-1 enzymes such as integrase (IN), protease (PR), and reverse transcriptase (RT) was also determined through an in silico approach. The input–process–output framework was used to systematically structure the workflow of this study, from the extraction and identification of phytochemicals to the molecular docking analysis.

Preparation and Extraction of Crude Extract

The dried and powdered Mayana leaves that were procured from Herbanext Laboratories, Inc., were portioned for maceration in two different solvents. A total of 100 g of the plant material was submerged in enough 95% ethanol, and another 100 g sample was submerged in 500 mL of n-hexane. These were set aside and allowed to macerate for 3 days with frequent shaking. Using both ethanol and hexane as solvents for polar and nonpolar compounds will maximize the phytochemicals that can be extracted from the plant material. After maceration, the marc was filtered out using vacuum filtration, then gravity filtration. The resulting polar and nonpolar extracts were concentrated using a rotary evaporator (temperature of the water bath at 60°C and pressure at 600 mm Hg) and were dried using a lyophilizer. The lyophilized powder was then subjected to gas chromatography–mass spectrometry (GC–MS) analysis.

Identification Using Gas Chromatography–Mass Spectrometry Analysis

Analysis using GC–MS was carried out at Ateneo De Davao University, Davao City, Philippines. The specific instrument model used was GC–MS-QP2010 ULTRA (Shimadzu, Japan). Column oven temperature was maintained at 60°C. Splitless injection mode was used with an injection temperature of 220°C. Helium was used as a courier gas with a pressure of 100 kPa, and the sampling time was 1 minute. The column used was a Rtx5MS capillary column with specifications of 30 m length with 0.25 mm internal diameter, and 0.25-µm film thickness. Ion source temperature was maintained at 300°C, whereas interface temperature was maintained at 290°C. The peaks obtained from the mass spectra were compared and validated with standard spectra available from NIST08 (National Institute of Standards and Technology, United States) and Wiley7 (Wiley Science Solutions, United States) databases. A peak quality below 80% was excluded from the study.

Virtual Screening Using Molecular Docking

Molecular docking was carried out using AutoDock Vina (Scripps Research Institute, United States). AutoDock Vina is one of the fastest and most widely used virtual screening tools that offers a more accurate prediction of binding mode.[19] [20] For a streamlined and flexible molecular docking workflow, Dockey was used. Dockey is an open-access software (downloadable at https://github.com/lmdu/dockey) that is cross-platform compatible, easy to use, flexible, and implements the whole molecular docking pipeline in one intuitive graphical interface and making it simple for all types of researchers.[21] The docking study and its preparations were performed on a 2022 MacBook Pro 13” (Apple, United States) with 512 gigabytes of internal storage and eight gigabytes of memory.

HIV-1 IN (PDB Code: 3OYA), PR (PDB Code: 3NU3), and RT (PDB Code: 3LP1) were obtained from RCSB Protein Data Bank (https://www.rcsb.org). The enzymes were prepared by removing water, solvent, organics, and heteroatom nonreceptor atoms of the respective protein enzymes through the Docking software. Receptor preparation was done using AutoDock Tools, which is already integrated with Docking. Furthermore, grid box assignments for the various HIV enzymes followed the specification set by the study of Zubair et al.[22]

The structured data files of the phytochemicals identified from the GC–MS analysis of Mayana crude extract were collected from PubChem (https://pubchem.ncbi.nlm.nih.gov). The native ligands of the target enzymes, as based on a previous study, were also included as a form of validation of the results.[22] These native ligands include amprenavir, raltegravir, and nevirapine for HIV PR, IN, and RT, respectively. Native ligand docking and redocking were done to ascertain the most accurate receptor preparation algorithm and docking parameters. These ligands were also prepared for docking using AutoDock Tools, similarly to receptor preparation.

In the assessment or virtual screening through Docking, default parameters for docking were used. These parameters have been well-tested and highly optimized.[23] These default parameters include Vina as the scoring function and exhaustiveness of eight. Minimum root mean square deviation was 1.00 Å, and the maximum number of binding modes to generate was nine. The result of docking was expressed in binding free energy, and the ligand with the lowest value or score for the respective enzymes was associated with better affinity to the target enzymes, and the ligand with the most promising potential for bioactivity. LigPlot+ version 2.2 was used to illustrate the ligand–receptor complex interaction.[24] Furthermore, the ligand with the lowest binding free energy value was also associated with the most promising ligand conformation for the potential enzyme inhibitory activity.

Pharmacokinetic Prediction

Following molecular docking, the absorption, distribution, metabolism, excretion (ADME) prediction was carried out using SwissADME. SwissADME is a free web tool that provides researchers with a pool of robust predictive tools that assess the physicochemical properties, pharmacokinetics, drug-likeness, and medicinal chemistry friendliness of compounds.[25] Furthermore, the BOILED-Egg method was also used to easily visualize gastrointestinal absorption and brain access, which are two crucial pharmacokinetic behaviors.[26]

In doing the pharmacokinetic prediction, only the top ten Mayana phytochemicals that exhibited the lowest binding free energy were used. The selection of these phytochemicals was based on their strong binding affinities toward the target HIV enzymes, which suggested a greater likelihood of biological activity. By narrowing the pool to the most promising candidates, the study ensured that the pharmacokinetic evaluation would focus on compounds with both favorable docking profiles and potential drug-like characteristics. This approach not only streamlines the analysis but also increases the relevance of the ADME predictions.

Results

Through chromatographic analysis of the crude extracts of Mayana, 40 phytochemicals were identified. Some of these phytochemicals were found in both the ethanol and hexane extracts. These phytochemicals are reported in [Table 1]. From this table, the three most abundant phytochemicals based on % peak area were (3.beta.,23E)-9,19-cyclolanost-23-ene-3,25-diol (35.22%), methyl commate C (17.14%), and phytol (16.84%) in the ethanolic portion. All the while, the three most abundant in the hexane portion were squalene or 2,6,10,14,18, 22-tetracosahexaene, 2,6,10,15,19,23-hexamethyl-, (all-E)- (27.54%), tetrapentacontane (11.67%), and stigmasterol (3.24%).

Table 1 Phytochemicals identified from the ethanolic and hexane crude extract of Mayana leaves

Number	PubChem Compound ID	Identified Compound	RT (min)	Peak area (%)	Peak height (%)	Peak quality (%)	Extracted from
1	6420801	Sulfurous acid, butyl nonyl ester	5.08	0.03	0.26	81	EtOH
2	140213	3-Ethyl-3-methylheptane	5.12	0.13	1.16	92	EtOHa
3	12389	Tetradecane	5.15	0.09	0.73	84	EtOH
4	519387	Undecane, 3,7-dimethyl-	5.41	0.02	0.26	89	EtOH
5	519404	Undecane, 3,5-dimethyl-	5.46	0.03	0.31	85	EtOHa
6	569301	Silane, cyclohexyldimethoxymethyl-	5.49	0.04	0.39	87	EtOHa
7	2537	Bicyclo[2.2.1]heptan-2-one, 1,7,7-trimethyl-, (1R)-	5.52	0.06	0.49	91	EtOH
8	6552009	endo-Borneol	5.68	0.47	2.03	91	EtOH
9	136810	Benzene, 1,3-bis(1,1-dimethylethyl)-	6.09	0.06	0.36	81	EtOHa
10	545627	Dodecane, 4,6-dimethyl-	6.21	0.43	3.47	94	EtOHa
11	300476	Nonane, 5-butyl-	6.31	0.06	0.44	87	EtOH
12	551397	Nonane, 5-methyl-5-propyl-	6.36	0.07	0.61	88	EtOHa
13	595370	1H-Cyclopropa[a]naphthalene, decahydro-1,1,3a-trimethyl-7-methylene-, [1aS-(1a.alpha.,3a.alpha.,7a.beta.,7b.alpha.)]-	6.85	0.15	0.75	83	EtOHa
14	5281515	Caryophyllene	7.48	0.19	1.06	95	EtOHa
15	1742210	Caryophyllene oxide	9.33	0.95	1.28	92	EtOH
16	11007	Hexadecane, 1-iodo-	10.43	0.20	0.34	81	EtOH
17	8181	Hexadecanoic acid, methyl ester	13.87	0.40	0.84	92	EtOH
18	5280435	Phytol	16.50	16.84	9.66	95	EtOH
19	573073	5.beta.-iodomethyl-1.beta.-isopropenyl-4.alpha.,5.alpha.-dimethyl, 6.beta.Bicyclo[4.3.0]nonane	24.51	1.74	1.57	84	EtOH
20	*	Methyl Commate C	24.96	17.14	13.75	90	EtOH
21	609236	1,4-Dimethyl-8-isopropylidenetricyclo[5.3.0.0(4,10)]decane	25.71	4.53	3.88	84	EtOH
22	612782	4,4,6a,6b,8a,11,11,14b-Octamethyl-1,4,4a,5,6,6a,6b,7,8,8a,9,10,11,12,12a,14,14a,14b-octadecahydro-2H-picen-3-one	25.96	4.77	4.11	82	EtOH
23	5363281	(3.beta.,23E)-9,19-Cyclolanost-23-ene-3,25-diol	26.60	35.22	20.78	86	EtOH
24	545936	Nonane, 5-(2-methylpropyl)-	5.11	0.13	0.84	93	Hex
25	140213	3-Ethyl-3-methylheptane	5.15	0.06	0.39	90	Hex
26	519404	Undecane, 3,5-dimethyl-	5.46	0.06	0.34	87	Hex
27	569301	Silane, cyclohexyldimethoxymethyl-	5.49	0.09	0.41	86	Hex
28	136810	Benzene, 1,3-bis(1,1-dimethylethyl)-	6.08	0.01	0.09	85	Hex
29	11006	Hexadecane	6.21	0.46	2.69	93	Hex
30	12398	Heptadecane	6.27	0.08	0.51	91	Hex
31	545627	Dodecane, 4,6-dimethyl-	6.51	0.17	0.89	92	Hex
32	551397	Nonane, 5-methyl-5-propyl-	6.58	0.04	0.19	87	Hex
33	5374422	Acetic acid, 3-(2,2-dimethyl-6-methylene-cyclohexylidene)-1-methyl-butyl ester	6.70	0.04	0.23	80	Hex
34	595370	1H-Cyclopropa[a]naphthalene, decahydro-1,1,3a-trimethyl-7-methylene-, [1aS-(1a.alpha.,3a.alpha.,7a.beta.,7b.alpha)]-	6.85	0.09	0.39	84	Hex
35	5281515	Caryophyllene	7.47	0.04	0.19	90	Hex
36	11008	Dotriacontane	20.29	0.48	0.56	86	Hex
37	5280794	Stigmasterol	22.56	3.24	3.31	83	Hex
38	12412	Hexatriacontane	23.48	1.52	1.76	91	Hex
39	521846	Tetrapentacontane	24.88	11.67	8.42	93	Hex
40	638072	2,6,10,14,18, 22-Tetracosahexaene, 2,6,10,15,19,23-hexamethyl-, (all-E)-	25.96	27.54	23.63	95	Hex

Notes: * indicated a sourced from SpectraBase with the compound ID LPM8fPGaWYa. Phytochemicals detected in both the ethanol (EtOH) and hexane (Hex) extracts are indicated with a superscript (^a), shown in the EtOH row where they are first listed. A total of 32 individual phytochemicals were identified.

Molecular docking analysis was performed to predict the interactions between the phytochemicals and the three major HIV enzymes. Results are reported in [Table 2]. For HIV IN and HIV PR, the phytochemical with the lowest binding free energy is stigmasterol (−8.571 kcal/mol for HIV IN and −10.250 kcal/mol for HIV RT). Caryophyllene was predicted to have the highest binding affinity to HIV RT among all phytochemicals (−9.625 kcal/mol).

Table 2 Binding free energy of identified Mayana phytochemicals against HIV-1 enzymes

No	Compound identified	HIV IN	HIV PR	HIV RT
1	Sulfurous acid, butyl nonyl ester	−4.889	−5.002	−6.306
2	3-Ethyl-3-methylheptane	−4.285	−4.603	−6.078
3	Tetradecane	−4.099	−4.877	−6.500
4	Undecane, 3,7-dimethyl-	−4.850	−5.073	−6.425
5	Undecane, 3,5-dimethyl-	−4.483	−4.874	−4.602
6	Silane, cyclohexyldimethoxymethyl-	−5.191	−5.397	−6.658
7	Bicyclo[2.2.1]heptan-2-one, 1,7,7-trimethyl-, (1R)-	−5.061	−5.899	−5.975
8	endo-Borneol	−5.035	−5.565	−5.769
9	Benzene, 1,3-bis(1,1-dimethylethyl)-	−5.95710	−6.8858	−8.8384
10	Dodecane, 4,6-dimethyl-	−4.477	−5.318	−7.44710
11	Nonane, 5-butyl-	−4.387	−4.777	−4.655
12	Nonane, 5-methyl-5-propyl-	−4.686	−4.809	−6.742
13	1H-Cyclopropa[a]naphthalene, decahydro-1,1,3a-trimethyl-7-methylene-, [1aS-(1a.alpha.,3a.alpha.,7a.beta.,7b.alpha.)]-	−6.4704	−6.8759	−9.5292
14	Caryophyllene	−6.3275	−7.0087	−9.6251
15	Caryophyllene oxide	−6.0778	−7.4235	−8.5607
16	Hexadecane, 1-iodo-	−4.288	−5.072	−4.414
17	Hexadecanoic acid, methyl ester	−4.710	−5.135	−4.181
18	Phytol	−5.832	−6.272	−5.280
19	5.beta.-Iodomethyl-1.beta.-isopropenyl-4.alpha.,5.alpha.-dimethyl, 6.beta.bicyclo[4.3.0]nonane	−5.636	−6.217	−5.399
20	1,4-Dimethyl-8-isopropylidenetricyclo[5.3.0.0(4,10)]decane	−6.0299	−7.1316	−7.9989
21	4,4,6a,6b,8a,11,11,14b-Octamethyl-1,4,4a,5,6,6a,6b,7,8,8a,9,10,11,12,12a,14,14a,14b-octadecahydro-2H-picen-3-one	−7.6753	−7.5264	−8.8345
22	(3.beta.,23E)-9,19-Cyclolanost-23-ene-3,25-diol	−7.8922	−8.8052	−8.6536
23	Nonane, 5-(2-methylpropyl)-	−4.491	−4.889	−7.169
24	Silane, cyclohexyldimethoxymethyl-	−5.191	−5.397	−6.658
25	Hexadecane	−4.340	−5.029	−6.969
26	Heptadecane	−4.537	−5.279	−6.860
27	Acetic acid, 3-(2,2-dimethyl-6-methylene-cyclohexylidene)-1-methyl-butyl ester	−6.3166	−6.70410	−5.909
28	Dotriacontane	−5.077	−5.903	−6.784
29	Stigmasterol	−8.5711	−10.2501	−8.4508
30	Hexatriacontane	−5.099	−5.911	−6.916
31	Tetrapentacontane	−5.344	−6.188	−5.882
32	2,6,10,14,18,22-Tetracosahexaene, 2,6,10,15,19,23-hexamethyl-, (all-E)-	−6.1407	−7.7463	−9.3123

Note: Superscript numbers indicate the top 10 ligands with the highest binding affinities for each target enzyme. Native ligands have the following binding affinity: −9.825 kcal/mol for raltegravir against HIV integrase (IN), −9.421 kcal/mol for amprenavir against HIV protease (PR), and −9.748 kcal/mol for nevirapine against HIV reverse transcriptase (RT). The ten phytochemicals with the lowest binding free energy values for each enzyme are distinguished with subscripts 1 to 10.

In comparison to native ligands, raltegravir scored −9.825 kcal/mol for HIV IN, amprenavir scored −9.421 kcal/mol for HIV PR, and nevirapine scored −9.748 kcal/mol for HIV RT.

Comparison between the interactions of the phytochemicals with the lowest binding free energy and the native ligands is reported in [Table 3] and visualized in [Table 4]. Raltegravir and stigmasterol share similar interactions with HIV IN in that they both interact with the residues Arg-350, Leu-113, Pro-115, and Lys-219. Amprenavir and stigmasterol both interact with HIV PR, mainly with the residues Ala-28, Asp-30, Ile-84, Ile-47 (chain B), and Ile-50 (chain B). Lastly, nevirapine and caryophyllene interact with HIV RT through the residues Leu-100, Tyr-181, and Leu-234.

Table 3 Drug likelihood and ADME prediction of Mayana phytochemicals with high binding affinity to HIV enzymes

PubChem CID	Identified Compound	MW	Lipinski violations	GI absorption	BBB permeant	Pgp substrate	CYP1A2 inhibitor	CYP2C19 inhibitor	CYP2C9 inhibitor	CYP2D6 inhibitor	CYP3A4 inhibitor
5280794	Stigmasterol	412.69	1	Low	No	No	No	No	Yes	No	No
5363281	(3.beta.,23E)-9,19-Cyclolanost-23-ene-3,25-diol	484.75	1	Low	No	No	No	No	No	No	No
612782	4,4,6a,6b,8a,11,11,14b-Octamethyl-1,4,4a,5,6,6a,6b,7,8,8a,9,10,11,12,12a,14,14a,14b-octadecahydro-2H-picen-3-one	424.70	1	Low	No	No	No	No	No	No	No
595370	1H-Cyclopropa[a]naphthalene, decahydro-1,1,3a-trimethyl-7-methylene-, [1aS-(1a.alpha.,3a.alpha.,7a.beta.,7b.alpha.)]-	204.35	1	Low	No	No	No	Yes	Yes	No	No
5281515	Caryophyllene	204.35	1	Low	No	No	No	Yes	Yes	No	No
5374422	Acetic acid, 3-(2,2-dimethyl-6-methylene-cyclohexylidene)-1-methyl-butyl ester	250.38	0	High	Yes	No	No	Yes	Yes	No	No
638072	2,6,10,14,18, 22-Tetracosahexaene, 2,6,10,15,19,23-hexamethyl-, (all-E)-	410.72	0	High	Yes	No	No	Yes	Yes	No	No
1742210	Caryophyllene oxide	220.35	0	High	Yes	No	No	Yes	Yes	No	No
609236	1,4-Dimethyl-8-isopropylidenetricyclo[5.3.0.0(4,10)]decane	204.35	1	Low	No	No	No	Yes	Yes	No	No
545627	Dodecane, 4,6-dimethyl-	198.39	1	Low	No	No	No	No	Yes	No	No
136810	Benzene, 1,3-bis(1,1-dimethylethyl)-	198.39	1	Low	No	No	No	No	Yes	No	No

Abbreviation: GI, gastrointestinal.

Note: Lipinski violations stand for the number of violations to the Lipinski druggability rule or rule of 5.

Table 4 Visualization of interactions between the native ligands and the top phytochemical for each HIV enzyme

Enzyme	Native ligand	Mayana phytochemical
HIV reverse transcriptase
HIV integrase
HIV protease

Pharmacokinetic prediction results are tabulated in [Table 3] and visualized through the BOILED-Egg method in [Fig. 1]. A total of 11 compounds were used and analyzed with the SwissADME and BOILED-Egg method. The 11 compounds ranged in molecular weight from 198.39 to 484.75 daltons. In terms of the violations of drug-likeness rules, 8 of the 11 compounds were found to have only 1 violation—they had poor solubility, resulting in low gastrointestinal absorption. Compounds acetic acid, 3-(2,2-dimethyl-6-methylene-cyclohexylidene)-1-methyl-butyl ester (CID: 5374422), 2,6,10,14,18, 22-Tetracosahexaene, 2,6,10,15,19,23-hexamethyl-, (all-E)- (CID: 638072), and caryophyllene oxide (CID: 1742210) were predicted to have blood–brain barrier permeability. The rest of the compounds did not have any violations of the Lipinski rules. None of the compounds was predicted to be p-glycoprotein substrates.

Fig. 1 Boiled-egg diagram for the top Mayana phytochemicals against HIV enzyme. Ligands with a red outline indicate they are not p-glycoprotein substrates. Ligands are labeled using their PubChem CID. Three molecules were outside of range: 612782, 638072, 136810.

Discussion

This study used a molecular docking program to investigate the potential of Mayana and its constituents as agents against selected HIV-1 enzymes. These phytochemical constituents were identified from the ethanolic and hexane extracts of dried Mayana powders using GC–MS. Through molecular docking, the binding affinity of these phytochemicals was predicted and elaborated.

Through the chromatographic analysis, around 32 individual organic compounds from a variety of classes were identified. Upon closer examination, these compounds mostly consisted of the terpenoid family, steroids, and hydrocarbon compounds. These terpenoid compounds include monoterpenes, sesquiterpenes, diterpenes, and triterpenes. The findings align with phytochemical analyses of other studies, confirming the presence of terpenoid compounds, steroids, and steroid-based phytochemicals in Mayana.[27] [28] However, unlike other studies where flavonoids and phenols were qualitatively indicated, the current study did not show compounds of flavonoid or phenolic nature. This may be a result of drying since flavonoids and phenolic compounds have been known to degrade in heat.[29] [30] [31]

Results of docking analysis have also been reported in the literature. The binding free energy measures the stability of the complex formed between the ligand and the target protein.[32] The smaller the binding free energy, the more stable the complex is, and the higher the binding affinity is. The phytochemicals having the lowest binding free energy were caryophyllene for HIV RT (−9.625 kcal/mol) and stigmasterol for both HIV IN (−8.571 kcal/mol) and HIV PR (−10.25 kcal/mol). These compounds are terpenoid compounds, which align with previously conducted studies on the anti-HIV activity of terpenoids.[33] [34] [35]

Stigmasterol is one of the most common plant sterols found in nature and has been reported to have a variety of pharmacological properties, including anti-HIV activity.[36] [37] Another study has also reported that stigmasterol extracted from stem bark and leaf extracts of Kra Don (Careya arborea Roxb.) exhibited bioactivity against HIV RT with inhibition levels comparable to nevirapine.[38] Furthermore, the binding affinity of stigmasterol for HIV PR aligns with the findings of Zubair et al.[22] Stigmasterol was also reported to have inhibitory activity against HIV IN.[39]

Caryophyllene is a natural bicyclic sesquiterpene that possesses extensive biological activities.[40] Caryophyllene has also demonstrated preventive effects of mechanical allodynia induced by nucleoside RT in mouse models.[41] Many plants containing caryophyllene have also reported inhibitory effects on HIV-1 reverse transcriptase, with varying levels of activity.[42] Plant species containing caryophyllene and caryophyllene oxide were also reported to exhibit anti-HIV activity against HIV-infected lymphocyte cells.[43] Although the HIV-1 RT inhibitory activity of β-caryophyllene itself has not been validated in vitro, plant extracts containing this compound have demonstrated relevant bioactivity. The findings of this study provide an in silico basis that warrants further investigation on caryophyllene.

A comparison of binding affinities revealed that the native synthetic drugs generally outperformed the phytochemicals, except in the case of HIV PR, where certain plant-derived compounds showed superior or comparable binding. The binding free energies of raltegravir, amprenavir, and nevirapine were −9.825, −9.421, and −9.748 kcal/mol, respectively, indicating that the drugs remain superior. For amprenavir, the results are similar to the study of Zubair et al, where the plant metabolites had a lower free binding energy than the same native ligands.[22] These phytochemicals may have a higher affinity to HIV PR than amprenavir, implying better inhibitory activity. However, in-depth investigations are needed to confirm this claim.

An analysis of the underlying interactions reveals similar and overlapping binding modes between the compounds and the target enzymes. For HIV IN, both raltegravir and stigmasterol formed hydrogen bonds and hydrophobic interactions. These interactions span the essential domains of HIV IN, which are critical for enzymatic function.[44] Similarly, amprenavir and stigmasterol shared identical interaction types and residues in HIV PR. Notably, stigmasterol interacts with both Asp-25 residues in the dimeric HIV PR enzyme, a key component of the catalytic active site.[45] Furthermore, stigmasterol also interacts with the amino acid residues of the flap regions, which are important for securing substrate binding. Lastly, nevirapine and caryophyllene interact with amino acid residues of HIV RT through hydrophobic interactions. The amino acid residues with which caryophyllene interacts are the identical residues that RNase H inhibitors interact with,[46] suggesting it works by inhibiting RNase H, which is an important catalytic active site of HIV RT.[47]

The top phytochemicals in Mayana, especially stigmasterol, also showed similar affinity to the other two HIV enzymes. Some other Mayana compounds display affinities comparable to stigmasterol and caryophyllene. These phytochemicals may be beneficial due to their ability to target multiple enzymes, a key area of research interest.[48] [49] The findings support further research on Mayana as a plant-based therapy for HIV, although more studies, including the isolation of specific compounds and additional testing, are needed to confirm its anti-HIV effects.

For ADME prediction, the analysis revealed that the 11 phytochemicals predicted with the highest binding affinity to HIV target enzymes generally adhered to Lipinski's rule of 5, with at most one violation each. This suggests that they possess favorable drug-like properties. The Lipinski's rule of 5, also called the druggability rule, is a widely used “rule of thumb” for evaluating whether a substance has characteristics consistent with orally active drugs.[50] Caryophyllene oxide was predicted to have no violations with the Lipinski rules, but caryophyllene had one—it has poor solubility. This suggests that the structure of caryophyllene should be slightly modified, such as by introducing polar functional groups, to improve its pharmacokinetic properties without significantly compromising its bioactivity.

Sterol-like compounds such as stigmasterol and (3.beta.,23E)-9,19-cyclolanost-23-ene-3,25-diol showed strong binding affinities across HIV target enzymes. These two sterol compounds had binding free energy values that approached the active ligands closely. However, these compounds were found to have limitations with their drug-likeness as they were predicted to have low gastrointestinal absorption. This can be circumvented by chemical modifications or formulating these compounds in a suitable drug delivery system.

Taken together, docking and ADME predictions suggest that while sterol derivatives may serve as strong bioactive leads, compounds such as acetic acid ester, tetracosahexaene, and caryophyllene oxide emerge as the most balanced candidates, offering both significant enzyme inhibition potential and favorable drug-like properties for further development.

Limitations

Firstly, compounds must be sufficiently volatile to transfer from the liquid to the gas phase to be eluted from the analytical column.[51] Without adequate volatility, they cannot be eluted or detected. As no chemical derivatization was performed to facilitate the identification of flavonoids, this likely resulted in the absence of identified flavonoid and phenolic compounds in the analysis. Future studies should consider using high-performance liquid chromatography or other chromatographic techniques that better account for phytochemical stability. Second, the molecular docking findings of this research require validation through in vitro and in vivo studies. While molecular docking predicts binding potential, it does not confirm actual enzymatic inhibition. Furthermore, although this study focused on three key enzymes, phytochemicals may also interact indirectly with these enzymes or through other signaling pathways. Despite these limitations, the findings remain relevant and provide a valuable contribution to the field of natural product-based HIV drug discovery.

Conclusion

This virtual screening study provides in silico evidence that Mayana phytochemicals, particularly terpenoids, can target HIV IN, PR, and RT, supporting their great potential as anti-HIV agents. While their binding affinities are generally lower than those of synthetic drugs, these natural compounds represent promising lead structures for further optimization. Future work should focus on the targeted isolation of these specific compounds, followed by experimental validation of their bioactivity, safety, and efficacy through in vitro and in vivo studies.

Conflict of Interest

None declared.

Supporting Information

The original docking result for HIV integrase (IN), protease (PR), and reverse transcriptase (RT) ([Supplementary Tables S1]–[S3], available in online version) can be found in the “Supporting Information” section of this article's webpage.

• References

• 1 Karimi A, Majlesi M, Rafieian-Kopaei M. Herbal versus synthetic drugs; beliefs and facts. J Nephropharmacol 2015; 4 (01) 27-30
• 2 Arisudhana GAB, Sofro MAU, Sujianto U. Antiretroviral side effects on adherence in people living with HIV/AIDS. Nurse Media J Nurs 2018; 8 (02) 79-85
• 3 Rather ZA, Chowta MN, Prakash Raju GJ, Mubeen F. Evaluation of the adverse reactions of antiretroviral drug regimens in a tertiary care hospital. Indian J Pharmacol 2013; 45 (02) 145-148
• 4 Carr A, Mackie NE, Paredes R, Ruxrungtham K. HIV drug resistance in the era of contemporary antiretroviral therapy: a clinical perspective. Antivir Ther 2023; 28 (05) 13 596535231201162
• 5 Onifade AA, Jewell AP, Ajadi TA, Rahamon SK, Ogunrin OO. Effectiveness of a herbal remedy in six HIV patients in Nigeria. J Herb Med 2013; 3 (03) 99-103
• 6 Shiferaw A, Baye AM, Amogne W, Feyissa M. Herbal medicine use and determinant factors among HIV/AIDS patients on antiretroviral therapy in Tikur Anbessa Specialized Hospital, Addis Ababa, Ethiopia. HIVAIDS - Res. HIV AIDS (Auckl) 2020; 12: 941-949
• 7 Sun Y, Lu H, Ye J, Li D, Li G. Awareness and use of HIV pre-exposure prophylaxis and factors associated with awareness among MSM in Beijing, China. Sci Rep 2023; 13 (01) 554
• 8 Sabde S, Bodiwala HS, Karmase A. et al. Anti-HIV activity of Indian medicinal plants. J Nat Med 2011; 65 (3-4): 662-669
• 9 Bodiwala HS, Sabde S, Mitra D, Bhutani KK, Singh IP. Anti-HIV diterpenes from Coleus forskohlii . Nat Prod Commun 2009; 4 (09) 1173-1175
• 10 Tewtrakul S, Miyashiro H, Nakamura N. et al. HIV-1 integrase inhibitory substances from Coleus parvifolius . Phytother Res 2003; 17 (03) 232-239
• 11 Agapin JS. Medicinal plants used by traditional healers in Pagadian City, Zamboanga del Sur, Philippines. Philipp J Sci 2019; 149 (01) 83-89
• 12 Belgica TH, Suba M, Alejandro GJ. Quantitative ethnobotanical study of medicinal flora used by local inhabitants in selected Barangay of Malinao, Albay, Philippines. Biodiversitas (Surak) 2021; 22 (07) 2711-2721
• 13 Cordero CS, Meve U, Alejandro GJD. Ethnobotany and diversity of medicinal plants used among rural communities in Mina, Iloilo, Philippines: a quantitative study. J Asia-Pac Biodivers 2023; 16 (01) 96-117
• 14 Dapar MLG, Alejandro GJD, Meve U, Liede-Schumann S. Quantitative ethnopharmacological documentation and molecular confirmation of medicinal plants used by the Manobo tribe of Agusan del Sur, Philippines. J Ethnobiol Ethnomed 2020; 16 (01) 14
• 15 Susaya-Garcia J, Borja N, Sevilla-Nastor J, Villanueva J, Peyraube N. An ethnobotanical study of medicinal plants and perceptions on plant biodiversity conservation in Leyte, Philippines. J Hum Ecol 2018; 7 (01) 26-42
• 16 Batool M, Ahmad B, Choi S. A structure-based drug discovery paradigm. Int J Mol Sci 2019; 20 (11) 2783
• 17 Singh DB. Computer-Aided Drug Design. Springer Nature; 2020
• 18 Asiamah I, Obiri SA, Tamekloe W, Armah FA, Borquaye LS. Applications of molecular docking in natural products-based drug discovery. Sci Afr 2023; 20: e01593
• 19 Eberhardt J, Santos-Martins D, Tillack AF, Forli S. AutoDock Vina 1.2.0: new docking methods, expanded force field, and python bindings. J Chem Inf Model 2021; 61 (08) 3891-3898
• 20 Trott O, Olson AJ. AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem 2010; 31 (02) 455-461
• 21 Du L, Geng C, Zeng Q. et al. Dockey: a modern integrated tool for large-scale molecular docking and virtual screening. Brief Bioinform 2023; 24 (02) bbad047
• 22 Zubair MS, Maulana S, Widodo A, Mukaddas A, Pitopang R. Docking study on anti-HIV-1 activity of secondary metabolites from Zingiberaceae Plants. J Pharm Bioallied Sci 2020; 12 (Suppl. 02) S763-S767
• 23 Forli S, Huey R, Pique ME, Sanner MF, Goodsell DS, Olson AJ. Computational protein-ligand docking and virtual drug screening with the AutoDock suite. Nat Protoc 2016; 11 (05) 905-919
• 24 Laskowski RA, Swindells MB. LigPlot+: multiple ligand-protein interaction diagrams for drug discovery. J Chem Inf Model 2011; 51 (10) 2778-2786
• 25 Daina A, Michielin O, Zoete V. SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Sci Rep 2017; 7 (01) 42717
• 26 Daina A, Zoete V. A Boiled-egg to predict gastrointestinal absorption and brain penetration of small molecules. ChemMedChem 2016; 11 (11) 1117-1121
• 27 Clemen-Pascual LM, Macahig RAS, Rojas NRL. Comparative toxicity, phytochemistry, and use of 53 Philippine medicinal plants. Toxicol Rep 2021; 9: 22-35
• 28 Casuga KMS, Natividad LR. Comparative analysis of pigment contents, phytochemical constituents, and antioxidant properties of selected plants in the Philippines. Int Res J Sci Technol Educ Manag 2023; 3 (04) 37-49
• 29 Wang Z, Liang Y, Wu W. et al. The effect of different drying temperatures on flavonoid glycosides in white tea: a targeted metabolomics, molecular docking, and simulated reaction study. Food Res Int 2024; 190: 114634
• 30 Gao Y, Xia W, Shao P. et al. Impact of thermal processing on dietary flavonoids. Curr Opin Food Sci 2022; 48: 100915
• 31 Esparza I, Cimminelli MJ, Moler JA, Jiménez-Moreno N, Ancín-Azpilicueta C. Stability of phenolic compounds in grape stem extracts. Antioxidants 2020; 9 (08) 720
• 32 Mir WR, Bhat BA, Rather MA. et al. Molecular docking analysis and evaluation of the antimicrobial properties of the constituents of Geranium wallichianum D. Don ex Sweet from Kashmir Himalaya. Sci Rep 2022; 12 (01) 12547
• 33 Wu HF, Morris-Natschke SL, Xu XD. et al. Recent advances in natural anti-HIV triterpenoids and analogs. Med Res Rev 2020; 40 (06) 2339-2385
• 34 Sharapov AD, Fatykhov RF, Khalymbadzha IA, Zyryanov GV, Chupakhin ON, Tsurkan MV. Plant coumarins with anti-HIV activity: isolation and mechanisms of action. Int J Mol Sci 2023; 24 (03) 2839
• 35 Sillapachaiyaporn C, Rangsinth P, Nilkhet S, Moungkote N, Chuchawankul S. HIV-1 protease and reverse transcriptase inhibitory activities of Curcuma aeruginosa Roxb. Rhizome extracts and the phytochemical profile analysis: in vitro and in silico screening. Pharmaceuticals (Basel) 2021; 14 (11) 1115
• 36 Bakrim S, Benkhaira N, Bourais I. et al. Health benefits and pharmacological properties of stigmasterol. Antioxidants 2022; 11 (10) 1912
• 37 Hisham Shady N, Youssif KA, Sayed AM. et al. Sterols and triterpenes: antiviral potential supported by in-silico analysis. Plants 2020; 10 (01) 41
• 38 Bapia S, Srisombata N, Ratanabunyong S. et al. Isolation of stigmasterol from Kra Don (Careya arborea Roxb.) and bioactivities of its crude extracts against free radicals and human immunodeficiency virus. Agric Nat Resour (Bangk) 2021; 55 (01) 33-42
• 39 Bunluepuech K, Wattanapiromsakul C, Madaka F, Tewtrakul S. Anti-HIV-1 integrase and anti-allergic activities of Bauhinia strychnifolia . Songklanakarin J Sci Technol 2013; 35 (06) 659-664
• 40 Francomano F, Caruso A, Barbarossa A. et al. β-Caryophyllene: a sesquiterpene with countless biological properties. Appl Sci (Basel) 2019; 9 (24) 5420
• 41 Aly E, Khajah MA, Masocha W. β-Caryophyllene, a CB2-receptor-selective phytocannabinoid, suppresses mechanical allodynia in a mouse model of antiretroviral-induced neuropathic pain. Molecules 2019; 25 (01) 106
• 42 Chinsembu KC. Chemical diversity and activity profiles of HIV-1 reverse transcriptase inhibitors from plants. Rev Bras Farmacogn 2019; 29 (04) 504-528
• 43 Zubair MS, Khairunisa SQ, Widodo A, Nasronudin, Pitopang R. Antiviral screening on Alpinia eremochlamys, Etlingera flexuosa, and Etlingera acanthoides extracts against HIV-infected MT-4 cells. Heliyon 2021; 7 (04) e06710
• 44 Sala M, Spensiero A, Esposito F. et al. Development and identification of a novel anti-HIV-1 peptide derived by modification of the N-terminal domain of HIV-1 integrase. Front Microbiol 2016; 7: 845
• 45 Ghosh AK, Osswald HL, Prato G. Recent progress in the development of HIV-1 protease inhibitors for the treatment of HIV/AIDS. J Med Chem 2016; 59 (11) 5172-5208
• 46 Esposito F, Corona A, Tramontano E. HIV-1 reverse transcriptase still remains a new drug target: structure, function, classical inhibitors, and new inhibitors with innovative mechanisms of actions. Mol Biol Int 2012; 2012 (01) 586401
• 47 Singh AK, Das K. Insights into HIV-1 reverse transcriptase (rt) inhibition and drug resistance from thirty years of structural studies. Viruses 2022; 14 (05) 1027
• 48 Liu Q, Che D, Huang Q, Cao Z, Zhu R. Multi-target QSAR study in the analysis and design of HIV-1 inhibitors. Chin J Chem 2010; 28 (09) 1587-1592
• 49 Andrae-Marobela K, Ghislain FW, Okatch H, Majinda RRT. Polyphenols: a diverse class of multi-target anti-HIV-1 agents. Curr Drug Metab 2013; 14 (04) 392-413
• 50 Karami TK, Hailu S, Feng S, Graham R, Gukasyan HJ. Eyes on Lipinski's Rule of Five: a new “rule of thumb” for physicochemical design space of ophthalmic drugs. J Ocul Pharmacol Ther 2022; 38 (01) 43-55
• 51 Rockwood AL, Kushnir MM, Clarke NJ. 2 - Mass spectrometry. In: Rifai N, Horvath AR, Wittwer CT. eds. Principles and Applications of Clinical Mass Spectrometry. Elsevier; 2018: 33-65

Publication History

Received: 21 March 2025

Accepted: 24 October 2025

Article published online:
25 November 2025