ABSTRACT

Background: Human immunodeficiency virus (HIV)-2 does not spread as rapidly as HIV-1; however, it poses a threat because it has a higher mutation rate and is resistant to existing antiretroviral drugs. Hence, it is vital to design inhibitors that specifically target HIV-2 to reduce the occurrence of HIV-2 infections. Methods: In this study, we focused on natural products from a probiotic, namely plantaricins D, BN, JLA-9, and W from Lactobacillus plantarum, due to their reported ability to inhibit viral replication and trigger an enhanced immune response in viral infections, and the lack of resistance to these compounds. We screened these compounds for anti-HIV-2 activity using an in silico methodology, which consisted of collecting and preparing data from online databases, identifying ligand-binding sites via docking simulations, performing molecular interactions analyses, visualizing the three-dimensional structures of the ligand-target complexes and determining their stability, and calculating the translocation probability of the ligand. Results: The results showed that plantaricin JLA-9 from L. plantarum may inhibit three essential HIV-2 enzymes: protease, reverse transcriptase, and integrase. Conclusion: This in silico study establishes plantaricin JLA-9 as a highly promising multi-target candidate for HIV-2 inhibitor development, demonstrating effective binding to protease, reverse transcriptase, and integrase. Its natural origin and predicted efficacy against multiple drug targets make it a standout lead compound. We therefore advocate for its prioritization in subsequent in vitro and in vivo validation studies to accelerate the development of specific HIV-2 therapeutics.

Key words: antiviral, bioinformatics, human immunodeficiency virus-2, Lactobacillus plantarum, plantaricin

INTRODUCTION

Despite the development of effective antiviral drugs, human immunodeficiency virus (HIV)-1 continues to pose a threat to human health.[1] In addition, an estimated one to two million people are infected with HIV-2 worldwide.[2] HIV-2 spreads less rapidly than HIV-1; however, its high mortality rate and resistance to antiretroviral drugs contribute to the persistence of HIV-2 infections.[3,4] HIV-2 is highly resistant to current antiretroviral drugs, including protease inhibitors (PIs), non-nucleoside reverse transcriptase inhibitors (NNRTIs), and integrase strand transfer inhibitors.[5,6] Furthermore, the use of antiretroviral drug combinations has been shown to result in adverse reactions and other issues.[7–9]

Several studies have revealed that probiotics have antiviral effects.[10–12] Thus, they may have potential as anti-HIV-2 agents. Probiotics are bacteria that are beneficial to the host, and they have been shown to have a range of effects. For example, probiotics have been shown to stimulate the immune system to respond effectively to pathogens.[13] More specifically, probiotics help fight viral infections by changing the host cell membrane permeability, modulating the immune system, and generating metabolic products that inhibit viral replication.[14] In addition, probiotics have potential as therapeutic agents due to the positive effects some of their metabolic products have on diseases such as dermatitis, cancer, and inflammatory bowel disease.[13] Lactobacillus plantarum is a probiotic, rod-shaped Gram-positive species found in foods and beverages generated via fermentation that provides various pharmacological benefits.[15]

Several studies have shown that lactic acid bacteria (LAB), such as Lactiplantibacillus plantarum KAU007, can reduce the viral load of H1N1 influenza A and have low cytotoxicity.[16] It was also shown that administering a mix of LAB (L. plantarum, Bifidobacterium longum, and Lactococcus lactis spp.) could induce anti-coronavirus disease 2019 (COVID-19) cytokines, such as interleukin-18 (IL-18), IL-1β, tumor necrosis factor-α (TNF-α), IL-8, and IL-6.[17] L. plantarum Probio-88 strain P88-CFS was found to hinder Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection by inhibiting viral replication and reducing the levels of reactive oxygen species and proinflammatory cytokines (e.g., IL-6, interferon-α [IFN-α], and IFN-β).[18,19] L. plantarum strain SN35N isolated from pear fruit reportedly has anti-inflammatory activity and antiviral activity against influenza A and feline calicivirus.[20] While evidence suggests that L. plantarum has anti-HIV-1 activity, with a slight increase in the cluster of differentiation (CD) 4+/CD8+ T-cell ratio reported after exposure to L. plantarum, further research is needed to confirm this finding.[21]

In terms of the specific L. plantarum compounds responsible for the observed antiviral activity of this probiotic, plantaricins D, BN, JLA-9, and W have been identified as exhibiting anti-SARS-CoV-2 activity. Using an in silico approach, these plantaricins were determined to have potential as anti-COVID-19 agents.[11] Previous studies have not shown the potential of plantaricin for anti-HIV-2.

Given that other studies have shown that L. plantarum may be an effective anti-HIV-1 agent and that its plantaricins D, BN, JLA-9, and W may have anti-SARS-CoV-2 activity, we aimed to (1) determine whether these plantaricins can inhibit three essential HIV-2 enzymes and thus prevent viral replication, (2) identify the molecular mechanisms underlying the antiviral activity, and (3) evaluate their potential as antiretroviral compounds. To achieve these objectives, we adopted an in silico approach.

MATERIALS AND METHODS

Ligand retrieval and preparation

Data on L. plantarum plantaricin W (CID 139586573), plantaricin JLA-9 (CID 132535900), plantaricin D (CID 139586697), and plantaricin BN (CID 380907) were retrieved from the PubChem database (https://pubchem.ncbi.nlm.nih.gov/).[11] These compounds were used as ligands. Energy minimization, in preparation for the docking experiments, was performed using OpenBabel integrated with PyRx v.1.1.0 (The Scripps Research Institute, La Jolla, CA, USA) with an academic license and the following parameters: force field = uff, optimization algorithm = conjugate gradient, total number of steps = 200, number of steps for update = 1, and stop if energy difference is less than = 0.1.[22,23]

Target retrieval and preparation

Data on three HIV-2 enzymes were retrieved from the Research Collaboratory for Structural Bioinformatics Protein Data Bank (PDB) database (https://www.rcsb.org/): protease (PDB ID: 3EBZ),[24] reverse transcriptase (PDB ID: 1MU2),[25] and integrase (PDB ID: 3F9K).[26] These proteins were used as targets. Native ligands and water molecules were removed from the targets using PyMol v.2.5.0 (Schrödinger, LLC, Cambridge, MA, USA; https://pymol.org/) with an academic license for molecular docking optimization.[27]

Molecular docking simulations

Molecular docking experiments are performed to determine the strength of interactions within ligand-target complexes via binding affinity values.[28] We performed molecular docking simulations to determine the strength with which the L. plantarum plantaricins bound to the target enzymes and their capacity to inhibit enzymatic activity. We utilized the screening docking method, which involved directing the docking grid to cover the entire target area. This method was also used to identify new binding regions for antiretroviral candidates on the target enzymes and to avoid mutation domains on the targets.[11] The molecular docking simulations were performed using PyRx v.1.1.0 software (with an academic license).[29]

Identification of molecular interactions

Molecular interactions within ligand-target complexes were identified using LigPlot+ v2.2.4 software (https://www.ebi.ac.uk/thornton-srv/software/LigPlus/). Hydrogen bonds and hydrophobic interactions are relatively weak interactions; however, they contribute to the stability of ligand-target complexes and can mediate ligand-induced biological responses. These types of interactions can be detected using LigPlot+ v2.2.4.[30] Molecular interaction data can be used to identify strategic ligand-binding domains.[31]

Visualization of the ligand, target, and complex structures

The three-dimensional (3D) structures of the ligands, targets, and ligand-target complexes were visualized using PyMol v2.5 software (https://pymol.org/). The structural elements and colors used to visualize the compounds were selected to ensure alignment with publication standards (i.e., use of cartoons, surfaces, and sticks).[32]

Molecular dynamics simulations

The molecular docking results were validated via molecular dynamics simulations performed using the CABS-flex v2.0 server (https://biocomp.chem.uw.edu.pl/CABSflex2/index). Each root mean square fluctuation (RMSF) value (down to < 3 Å[10-10 m]) was reviewed to determine the stability of the associated interaction hotspot. Ligands involved in stable interactions are predicted to trigger specific biological activities via the target.[33]

Membrane translocation probability

The CELLPM tool (https://cellpm.org/) was used to simulate passive translocation through the cell membrane. The methodology reflected naturally occurring membrane-peptide interactions with biological responses, such as penetration due to polarity and molecular charge factors without harming the cell membrane.[34]

Toxicity prediction

The toxicity of the ligands was evaluated using ProTox v3.0 (https://tox.charite. de/protox3/). Computational methods are often used to estimate the toxicity of compounds to reduce the need for animal experimentation. The median lethal dose (LD50), class, accuracy, query similarity, and toxicity type of compounds can all be estimated using computational methods.[35]

RESULTS

Structural properties of the L. plantarum plantaricins and HIV-2 enzymes

L. plantarum is a probiotic species with many health benefits, including antiviral activity.[15] Among its secondary metabolites are plantaricins W, JLA-9, D, and BN,[11] which were used as ligands in this study. Information on each plantaricin was retrieved from the PubChem database, including the compound name, CID, molecular weight, formula, canonical simplified molecular input line entry system (SMILE), and 3D structure (Table 1). Two-dimensional images obtained from the database were edited using Canva (https://www.canva.com/) and downloaded in portable network graphics (PNG) format to obtain the representative images shown in Figure 1.

Figure 1

Figure 1. Structures of plantaricins W, JLA-9, D, and BN produced by L. plantarum.

Table 1: Details of the L. plantarum plantaricins included in this study
Ligand CID Molecular weight
(g/mol) 		Formula Canonical SMILE
Plantaricin W 139586573 1751.1 C75H131N25O21S CCC (C) C (C (= O) NC (C) C (= O) NC (CC[= O] N) C (= O) NC (CC1= CC= C (C= C1]O) C (= O) NC (CC (C]C) C= O) NC (= O) C (C) NC (= O) C (CC (= O]N) NC (= O) C (CCCCN) NC (= O) C (CCCN= C [N] N) NC (= O) C (CCCN= C (N]N) NC (= O) C (CO) NC (= O) C (C (C]O) NC (= O) C (CCCCN) NC (= O) C (C [C] O) NC (= O) C (CCSC) N
Plantaricin JLA-9 132535900 1044.2 C51H69N11O11S CC (C[= O] O) NC (= O) C (CC1= CC= CC= C1) NC (= O) C (CO) NC (= O) C (CCSC) NC (= O) C (CCCCN) NC (= O) C (CCC (= O] N) NC (= O) C (CC2= CNC3= CC= CC= C32) NC (= O) C (CC4= CC= CC= C4) N
Plantaricin D 139586697 946.1 C40H71N11O13S CCC (C) C (C= O) NC (= O) C (C) NC (= O) C (C (C] O) NC (= O) C (C) NC (= O) CNC (= O) C (CCSC) NC (= O) C (CCC (= O]N) NC (= O) C (CC [C] C) NC (= O) C (CO) NC (= O) C (C) N
Plantaricin BN 380907 484.5 C24H36O10 C1CCCCC (C (= O) C (= O) C (CCC1) (CCC[= O] O) CCC (= O) O) (CCC[= O] O) CCC (= O) O
SMILE, simplified molecular input line entry system.

The targets consisted of HIV-2 protease (PDB ID: 3EBZ), integrase (PDB ID: 3F9K), and reverse transcriptase (PDB ID: 1MU2). The 3D protein structures were obtained from the RCSB PDB database and visualized using PyMol v2.5.0 software (Figure 2).

Figure 2

Figure 2. Visualization of the 3D structures of the HIV-2 enzymes used as targets in this study. Chain A: green; chain B: cyan. HIV-2, human immunodeficiency virus.

Binding affinity of plantaricins for HIV-2 enzymes

Plantaricins W, JLA-9, D, and BN were found to interact with HIV-2 protease, reverse transcriptase, and integrase, with binding affinity values below –6.0 kcal/mol (Table 2). Among these, plantaricin JLA-9 exhibited the strongest binding to all three enzymes, with affinity values of –9.0, –9.8, and –7.4 kcal/mol for HIV-2 protease, reverse transcriptase, and integrase, respectively. Based on this result, which indicated that plantaricin JLA-9 bound with the highest affinity to HIV-2 enzymes, we selected this ligand for all subsequent experiments, while excluding the others, to focus on the most promising candidate. The structures of the ligand-target complexes involving plantaricin JLA-9 generated from the molecular docking results are displayed in Figure 3. These results support those of a previous in silico study, which showed plantaricins from probiotics could potentially inhibit SARS-CoV-2 replication,[11] and those of a study in which probiotics were found to inhibit influenza virus infection by enhancing the immune response.[36]

Figure 3

Figure 3. Visualization of the ligand-target complex structures involving plantaricin JLA-9 generated from the molecular docking results. (A) Plantaricin JLA-9 and protease, (B) plantaricin JLA-9 and reverse transcriptase, and (C) plantaricin JLA-9 and integrase. The ligand is shown with a green backbone, and the targets are shown in blue.

Table 2: Binding affinity between each plantaricin (ligand) and HIV-2 enzyme (target)
Ligand CID Minimization energy (kcal/mol) Binding affinity (kcal/mol)
Protease
(PDB ID: 3EBZ) 		Reverse transcriptase (PDB ID: 1MU2) Integrase
(PDB ID: 3F9K)
Plantaricin W 139586573 +1751.06 -6.1 -6.7 -6.7
Plantaricin JLA-9 132535900 +1044.23 -9.0 -9.8 -7.4
Plantaricin D 139586697 +946.12 -7.3 -6.6 -7.2
Plantaricin BN 380907 +484.54 -6.5 -7.5 -7.1
PDB, Protein Data Bank.

Molecular interactions and dynamics of the ligand-target complexes involving plantaricin JLA-9

Weak molecular interactions, such as hydrogen bonds and hydrophobic contacts, play a critical role in stabilizing ligand–target complexes and mediating biological activity.[37–39] To better understand how plantaricin JLA-9 interacts with HIV-2 enzymes, we analyzed its molecular interactions and dynamic behavior when bound to protease, reverse transcriptase, and integrase. Our analysis focused on hydrogen bonding and hydrophobic interactions occurring at domains with RMSF values < 3 Å (Table 3). The molecular interaction plots are presented in Figure 4, and the stability of the amino acids within the identified interaction hotspots is shown in Figure 5.

Figure 4

Figure 4. Two-dimensional molecular interaction plots of the ligand-target complexes involving plantaricin JLA-9. (A) Plantaricin JLA-9 and protease, (B) plantaricin JLA-9 and reverse transcriptase, and (C) plantaricin JLA-9 and integrase. Hydrogen bonds are shown as green lines, hydrophobic interactions are shown as eyelash-like structures, and the amino acids of the target are labeled.

Figure 5

Figure 5. Dynamic fluctuation plots of the ligand-target complexes formed with plantaricin JLA-9. (A) Plantaricin JLA-9 and protease, (B) plantaricin JLA-9 and reverse transcriptase, and (C) plantaricin JLA-9 and integrase. RMSF, root mean square fluctuation.

Table 3: Molecular interaction sites and RMSF values of ligand-target complexes formed with plantaricin JLA-9
Natural product Interaction hotspots and RMSF
Protease
(PDB ID: 3EBZ) 		Reverse transcriptase
(PDB ID: 1MU2) 		Integrase
(PDB ID: 3F9K)
Plantaricin JLA-9 Hydrogen bonds: Gly48, Asp29, Arg87
Hydrophobic interactions: Arg108, Glu58, Lys45, Lys107, Asp30, Trp106, Thr91, Asn88		 RMSF (Å): 1.134 Hydrogen bonds: Arg22, Leu92, Glu139, Ser134
Hydrophobic interactions: Trp24, Val380, Asn136, Pro133, Leu26, Lys376, Ile31, Asn137, Pro140, Gly141, Gln23, Val135, Pro25, Leu379		 RMSF (Å): 0.887 Hydrogen bonds: Lys25, Gly134, His181, Ile133
Hydrophobic interactions: Thr111, Ile110, Lys186, Leu58, Pro109, Gly59		 RMSF (Å): 0.897
PDB, Protein Data Bank.

Membrane translocation probability and toxicity of plantaricin JLA-9

In membrane translocation prediction studies, compounds with a log permeability coefficient (logPcalc) value greater than -5 are generally predicted to cross the cell membrane when their surface area is approximately 10 Å.[40,41] In this study, plantaricin JLA-9 had a logPcalc value of -22.56 (Figure 6), which indicates that it possesses the ability to cross the cell membrane.

Figure 6

Figure 6. Dynamic fluctuation of the ligand-target complexes formed with plantaricin JLA-9.

When the toxicity of plantaricin JLA-9 was evaluated, it was predicted to have an LD50 value of 5000 mg/kg and was categorized in toxicity class 5, with an average similarity value of 57.62% and a prediction accuracy of 67.38%. Organ-level toxicities were predicted, including hepatotoxicity, neurotoxicity, and cardiotoxicity, whereas nephrotoxicity was not predicted. The compound was also predicted to have carcinogenic, immunotoxic, mutagenic, and cytotoxic potential. No effect on the blood–brain barrier (BBB) was predicted, and the compound was not expected to be ecotoxic. This preliminary information may help guide wet-lab experiments in animal models.[42]

DISCUSSION

Probiotics are known to have multiple health benefits. For example, they have been shown to inhibit viral infection, induce an enhanced mucosal immune response to support viral elimination without acute inflammation, and produce compounds that inhibit essential viral proteins.[43] In this study, we identified a natural product of a probiotic that may inhibit the activity of three essential HIV-2 enzymes, as well as its potential mechanism of action. Given that existing antiretroviral drugs have limited effects on HIV-2, it is of paramount importance to identify and develop compounds that are active against HIV-2.[44] Previous studies have shown that integrase inhibitors disrupt HIV replication by forming hydrogen bonds in the integrase catalytic domain,[45–47] and that NNRTIs participate in hydrophobic interactions in the active site of HIV reverse transcriptase, inhibiting its activity.[48,49]

In this study, plantaricins W, JLA-9, D, and BN were found to bind to HIV-2 protease, reverse transcriptase, and integrase, with the strongest binding affinities observed between plantaricin JLA-9 and protease (-9.0 kcal/mol), reverse transcriptase (-9.8 kcal/mol), and integrase (-7.4 kcal/mol). Since these binding affinity values were all below -6.0 kcal/mol, it is predicted that plantaricin JLA-9 has an effect on each of these enzymes.[10] Our results align with those of previous studies that found that the binding affinity values of candidate HIV inhibitors ranged from -10.3 kcal/mol to -6.4 kcal/mol.[50] The HIV-1 PI amprenavir was found to have a binding affinity value of -9.0 kcal/mol, which is similar to that of plantaricin JLA-9 in our study; however, plantaricin JLA-9 had a more negative binding affinity value than nevirapine, an NNTRI.[51] It has been reported that the optimal binding affinity value for HIV-1 integrase inhibitors is below -7.0 kcal/mol.[52]

Our molecular dynamics simulations showed that plantaricin JLA-9 likely participates in hydrogen bonds and hydrophobic interactions at all interaction sites with RMSF values < 3 Å. Thus, it is proposed that plantaricin JLA-9 inhibits the activity of all the target enzymes by forming stable ligand-target complexes via weak interactions. In computational studies, the presence of weak interactions is taken into account when determining the effectiveness of candidate antiviral compounds.[53] In addition, our results indicate that plantaricin JLA-9 can translocate across the cell membrane (logPcalc value > -5) and thereby access the target enzymes.

Thus, our findings indicate that plantaricin JLA-9 has several advantages over other antiviral compounds. First, it is predicted to have low toxicity and few side effects. Second, it is a natural product of probiotic bacteria. Third, it likely forms stable ligand-target complexes with the target enzymes through weak interactions. Fourth, there is a high probability that it can translocate across the cell membrane. Finally, based on our results, plantaricin JLA-9 may inhibit three HIV-2 enzymes.

CONCLUSION

In this in silico study, L. plantarum plantaricin JLA-9 was found to have potential as an inhibitor of HIV-2 protease, reverse transcriptase, and integrase. Its strong binding affinity for the target enzymes is likely mediated by hydrogen bonds and hydrophobic interactions, and it is predicted to form stable ligand-target complexes. Our results indicate that plantaricin JLA-9 has low toxicity and can translocate across the cell membrane to reach the target enzymes. Hence, plantaricin JLA-9 is a candidate triple inhibitor of HIV-2.

The data that support the findings of this study are available from the corresponding author upon reasonable request.

DECLARATION

Acknowledgement

We thank Jalan Tengah (https://jalantengah.site) for editing the manuscript.

Author contributions

Kharisma VD: Conceptualization, Methodology, Data Curation, Writing—Original Draft Preparation. Sahadewa S: Investigation, Formal Analysis, Visualization. Fara Disa Durry: Resources, Data Curation, Validation. Wiradana PA: Software, Formal Analysis, Visualization. Turista DDR: Supervision, Writing—Review & Editing, Project Administration. Jakhmola V: Validation, Resources, Writing—Review & Editing. Rebezov M: Funding Acquisition, Project Administration, Writing—Review & Editing. Khairullah AR: Supervision, Writing—Review & Editing, Project Administration. Ansori ANM: Conceptualization, Supervision, Writing—Review & Editing, Final Approval of Manuscript. All authors have read and agreed to the published version of the manuscript.

Source of funding

This study was funded by the Virtual Research Center for Bioinformatics and Biotechnology, Surabaya, Indonesia (RG/2025/01).

Ethics approval

Not applicable.

Conflicts of interest

The authors declare no conflicts of interest in any capacity, including competing or financial interests.

Use of large language models, AI and machine learning tools

None declared.

Data availability statement

No additional data.

REFERENCES

  1. Moranguinho I, Taveira N, Bártolo I. Antiretroviral treatment of HIV-2 infection: available drugs, resistance pathways, and promising new compounds. Int J Mol Sci. 2023;24(6):5905.
  2. van Tienen C, van der Loeff MS. Epidemiology of HIV-2 infection in West Africa. In: Hope TJ, Stevenson M, Richman D (eds). Encyclopedia of AIDS. Springer; 2016, 1-11.
  3. Ntemgwa ML, Toni TD, Brenner BG, Camacho RJ, Wainberg MA. Antiretroviral drug resistance in human immunodeficiency virus type 2. Antimicrob Agents Chemother. 2009;53(9):3611-3619.
  4. Tzou PL, Descamps D, Rhee SY, et al. Expanded spectrum of antiretroviral-selected mutations in human immunodeficiency virus type 2. J Infect Dis. 2020;221(12):1962-1972.
  5. de Mendoza C, Requena S, Caballero E, et al. Antiretroviral treatment of HIV-2 infection. Future Virol. 2017;12:461-472.
  6. Meanwell NA, Krystal MR, Nowicka-Sans B, et al. Inhibitors of HIV-1 attachment: The discovery and development of temsavir and its prodrug fostemsavir. J Med Chem. 2018;61(1):62-80.
  7. Rather ZA, Chowta MN, Prakash Raju GJ, et al. Evaluation of the adverse reactions of antiretroviral drug regimens in a tertiary care hospital. Indian J Pharmacol. 2013;45(2):145-148.
  8. Pennings PS. HIV drug resistance: Problems and perspectives. Infect Dis Rep. 2013;5(Suppl 1):e5.
  9. Temereanca A, Ruta S. Strategies to overcome HIV drug resistance-current and future perspectives. Front Microbiol. 2023;14:1133407.
  10. Dicks LMT, Grobbelaar MJ. Double-barrel shotgun: Probiotic lactic acid bacteria with antiviral properties modified to serve as vaccines. Microorganisms. 2021;9(8):1565.
  11. Anwar F, Altayb HN, Al-Abbasi FA, Al-Malki AL, Kamal MA, Kumar V. Antiviral effects of probiotic metabolites on COVID-19. J Biomol Struct Dyn. 2021;39(11):4175-4184.
  12. Wang YJ, Moon A, Huang JS, Sun Y, Qiu HJ. Antiviral effects and underlying mechanisms of probiotics as promising antivirals. Front Cell Infect Microbiol. 2022;12:928050.
  13. Tomkinson S, Triscott C, Schenk E, Foey A. The potential of probiotics as ingestible adjuvants and immune modulators for antiviral immunity and management of SARS-CoV-2 infection and COVID-19. Pathogens. 2023;12(7):928.
  14. Lopez-Santamarina A, Lamas A, Del Carmen Mondragón A, et al. Probiotic effects against virus infections: New weapons for an old war. Foods. 2021;10(1):130.
  15. Seddik HA, Bendali F, Gancel F, Fliss I, Spano G, Drider D. Lactobacillus plantarum and its probiotic and food potentialities. Probiotics Antimicrob Proteins. 2017;9(2):111-22.
  16. Rather IA, Kamli MR, Sabir JSM, Paray BA. Potential antiviral activity of Lactiplantibacillus plantarum KAU007 against influenza virus H1N1. Vaccines (Basel). 2022;10(3):456.
  17. Kageyama Y, Nishizaki Y, Aida K, et al. Lactobacillus plantarum induces innate cytokine responses that potentially provide a protective benefit against COVID-19: A single-arm, double-blind, prospective trial combined with an in vitro cytokine response assay. Exp Ther Med. 2022;23(1):20.
  18. Rather IA, Choi SB, Kamli MR, et al. Potential adjuvant therapeutic effect of Lactobacillus plantarum Probio-88 postbiotics against SARS-COV-2. Vaccines (Basel). 2021;9(10):1067.
  19. Sunmola AA, Ogbole OO, Faleye TOC, Adetoye A, Adeniji JA, Ayeni FA. Antiviral potentials of Lactobacillus plantarum, Lactobacillus amylovorus, and Enterococcus hirae against selected Enterovirus. Folia Microbiol (Praha). 2019;64(2):257-264.
  20. Noda M, Danshiitsoodol N, Sakaguchi T, Kanno K, Sugiyama M. Exopolysaccharide produced by plant-derived Lactobacillus plantarum SN35N exhibits antiviral activity. Biol Pharm Bull. 2021;44(12):1886-1890.
  21. Blázquez-Bondia C, Parera M, Català-Moll F, et al. Probiotic effects on immunity and microbiome in HIV-1 discordant patients. Front Immunol. 2022;13:1066036.
  22. Kharisma VD, Ansori ANM, Widyananda MH, Utami SL. Molecular simulation: The potency of conserved region on E6 HPV-16 as a binding target of black tea compounds against cervical cancer. Biochem Cellular Arch. 2020;20:2795-2802.
  23. Mawaddani N, Sutiyanti E, Widyananda MH, et al. In silico study of entry inhibitor from Moringa oleifera bioactive compounds against SARS-CoV-2 infection. Pharmacognosy J. 2022;14(5):565-574.
  24. Kovalevsky AY, Louis JM, Aniana A, Ghosh AK, Weber IT. Structural evidence for effectiveness of darunavir and two related antiviral inhibitors against HIV-2 protease. J Mol Biol. 2008;384(1):178-192.
  25. Ren J, Bird LE, Chamberlain PP, Stewart-Jones GB, Stuart DI, Stammers DK. Structure of HIV-2 reverse transcriptase at 2.35-a resolution and the mechanism of resistance to non-nucleoside inhibitors. Proc Natl Acad Sci USA. 2002;99(22):14410-14415.
  26. Hare S, Shun MC, Gupta SS, Valkov E, Engelman A, Cherepanov P. A novel co-crystal structure affords the design of gain-of-function lentiviral integrase mutants in the presence of modified PSIP1/LEDGF/p75. PLoS Pathog. 2009;5(1):e1000259.
  27. Nugraha AP, Rahmadhani D, Puspitaningrum MS, Rizqianti Y, Kharisma VD, Ernawati DS. Molecular docking of anthocyanins and ternatin in Clitoria ternatea as coronavirus disease oral manifestation therapy. J Adv Pharm Technol Res. 2021;12(4):362-367.
  28. Kurnia D, Putri SA, Tumilaar SG, Zainuddin A, Dharsono HDA, Amin MF. In silico study of antiviral activity of polyphenol compounds from Ocimum basilicum by molecular docking, ADMET, and drug-likeness analysis. Adv Appl Bioinform Chem. 2023;16:37-47.
  29. Aini NS, Kharisma VD, Widyananda MH, et al. In silico screening of bioactive compounds from Garcinia mangostana L. against SARS-CoV-2 via tetra inhibitors. Pharmacognosy J. 2022;14(5):575-579.
  30. Gul I, Hassan A, Haq E, et al. An investigation of the antiviral potential of phytocompounds against avian infectious bronchitis virus through template-based molecular docking and molecular dynamics simulation analysis. Viruses. 2023;15(4):847.
  31. Mushebenge AG, Ugbaja SC, Mbatha NA, B Khan R, Kumalo HM. Assessing the potential contribution of in silico studies in discovering drug candidates that interact with various SARS-CoV-2 receptors. Int J Mol Sci. 2023;24(21):15518.
  32. Ben Hlima H, Farhat A, Akermi S, et al. In silico evidence of antiviral activity against SARS-CoV-2 main protease of oligosaccharides from Porphyridium sp. Sci Total Environ. 2022;836:155580.
  33. Wijaya RM, Hafidzhah MA, Kharisma VD, Ansori ANM, Parikesit AA. COVID-19 in silico drug with Zingiber officinale natural product compound library targeting the Mpro protein. Makara J Sci. 2021;25(3):162-171.
  34. Guo XL, Chen LL, Wang LD, et al. In silico identification and experimental validation of cellular uptake and intracellular labeling by a new cell penetrating peptide derived from CDN1. Drug Deliv. 2021;28(1):1722-1736.
  35. Banerjee P, Kemmler E, Dunkel M, Preissner R. ProTox 3.0: a webserver for the prediction of toxicity of chemicals. Nucleic Acids Res. 2024;52(W1):W513-W520.
  36. Xing JH, Shi CW, Sun MJ, et al. Lactiplantibacillus plantarum 0111 protects against influenza virus by modulating intestinal microbial-mediated immune responses. Front Microbiol. 2022;13:820484.
  37. Valencia E, Galvis M, Nisperuza J, Ballesteros V, Mesa F. In silico evaluation of potential NDM-1 inhibitors: an integrated docking and molecular dynamics approach. Pharmaceuticals (Basel). 2024;17(12):1715.
  38. Adegbola PI, Fadahunsi OS, Adegbola AE, Semire B. In silico studies of Potency and safety assessment of selected trial drugs for the treatment of COVID-19. In Silico Pharmacol. 2021;9(1):45.
  39. Elkaeed EB, Youssef FS, Eissa IH, et al. Multi-step in silico discovery of natural drugs against COVID-19 targeting main protease. Int J Mol Sci. 2022;23(13):6912.
  40. Skog AE, Paracini N, Gerelli Y, Skepö M. Translocation of antimicrobial peptides across model membranes: the role of peptide chain length. Mol Pharm. 2024;21(8):4082-4097.
  41. Chen LL, Guo XL, Wang LD, et al. In silico identification and experimental validation of cellular uptake by a new cell penetrating peptide P1 derived from MARCKS. Drug Deliv. 2021;28(1):1637-1648.
  42. Ford KA. Refinement, reduction, and replacement of animal toxicity tests by computational methods. ILAR J. 2016;57(2):226-233.
  43. Lehtoranta L, Latvala S, Lehtinen MJ. Role of probiotics in stimulating the immune system in viral respiratory tract infections: A narrative review. Nutrients. 2020;12(10):3163.
  44. Wahab S, Almaghaslah D, Mahmood SE, et al. Pharmacological efficacy of probiotics in respiratory viral infections: A comprehensive review. J Pers Med. 2022;12(8):1292.
  45. Weber IT, Agniswamy J. HIV-1 protease: Structural perspectives on drug resistance. Viruses. 2009;1(3):1110-1136.
  46. Weber IT, Wang YF, Harrison RW. HIV protease: Historical perspective and current research. Viruses. 2021;13(5):839.
  47. Hajimahdi Z, Zarghi A. Progress in HIV-1 integrase inhibitors: A review of their chemical structure diversity. Iran J Pharm Res. 2016;15(4):595-628.
  48. Singh K, Marchand B, Kirby KA, Michailidis E, Sarafianos SG. Structural aspects of drug resistance and inhibition of HIV-1 reverse transcriptase. Viruses. 2010;2(2):606-638.
  49. Singh AK, Das K. Insights into HIV-1 reverse transcriptase (RT) inhibition and drug resistance from thirty years of structural studies. Viruses. 2022;14(5):1027.
  50. Ugwu-Korie N, Quaye O, Wright E, et al. Structure-based identification of natural-product-derived compounds with potential to inhibit HIV-1 entry. Molecules. 2023;28(2):474.
  51. Sillapachaiyaporn C, Rangsinth P, Nilkhet S, et al. 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.
  52. Quashie PK, Han YS, Hassounah S, Mesplède T, Wainberg MA. Structural studies of the HIV-1 integrase protein: compound screening and characterization of a DNA-binding inhibitor. PLoS One. 2015;10(6):e0128310.
  53. Piplani S, Singh P, Petrovsky N, Winkler DA. Computational repurposing of drugs and natural products against SARS-CoV-2 main protease (Mpro) as potential COVID-19 therapies. Front Mol Biosci. 2022;9:781039.