Abstract
Background:
The oncogenic potential of HPV remains a major global public health challenge and various natural therapeutics are being investigated to prevent cancer. The natural components of the Alchemilla vulgaris plant have various anti-inflammatory, antioxidant, antiviral, and anticancer effects.
Objective:
Therefore, the aim of this study was to bioinformatically examine the potential inhibitory effect of A. vulgaris compounds on the HPV target protein.
Methods:
The structures of quercetin, catechin, apigenin, luteolin, caffeic and gallic acid were taken from the PubChem database, and the protein structure of the target HPV 16 E6 oncoprotein (PDB ID: 4XR8) from the Protein Data Bank. Virtual screening and docking analysis were performed in AutoDock Vina. Protein-ligand complexes were visualized using Discovery Studio. The molecular dynamics simulation of 4XR8 in complex with quercetin was performed using Desmond.
Results:
Docking analysis showed that quercetin has the strongest binding affinity with 4XR8 (quercetin -8.9 kcal/mol, apigenin -8.7 kcal/mol, luteolin -8.7 kcal/mol, catechin -8.4 kcal/mol, caffeic acid -7.3 kcal/mol, gallic acid -6.8 kcal/mol). The molecular dynamics simulation results reinforce the stability and strong binding affinity of quercetin within the HPV 16 E6 oncoprotein.
Conclusion:
Natural components of Alchemilla vulgaris, especially quercetin, have shown promising potential for the treatment of HPV infection and additional in vitro and in vivo studies are needed for their further research.
Keywords: Human papillomavirus, Alchemilla, quercetin, in silico, docking, molecular simulation
1. BACKGROUND
Among women worldwide, cervical cancer ranks fourth among malignant tumors and is the fourth most frequent type of cancer (1). The burden is particularly high in countries of low and medium development. Its occurrence is linked to a number of risk factors including smoking, having several sexual partners, poor personal hygiene, having a low socioeconomic status, and co-infection with another pathogenic microorganism. These factors together raise the likelihood of occurrence. In addition to the above factors, the highest oncogenic potential has been proven in high-risk HPV (human papillomavirus) infection (2). The most studied high-risk HPV genotypes 16, 18, 45 and 33 lead to the formation and development of premalignant lesions and, if persistent, progression to malignant lesions. Cervical cancer is one of the most preventable malignancies, therefore treating premalignant lesions is particularly challenging. HPV oncoproteins E6 and E7 lead to disruption of the cell cycle, cell proliferation and apoptosis by their expression (3).
HPV is a small, non-enveloped virus with a DNA molecule and a genome that encodes 8 proteins. The HPV genome is a small, circular, double-stranded DNA molecule approximately 8,000 base pairs in length. It is organized into three main regions: the early (E) region, the late (L) region, and the long control region (LCR). The early genes (E1–E7) are involved in viral replication, transcription regulation, and manipulation of the host cell cycle - particularly through proteins like E6 and E7, which can disrupt tumor suppressors such as p53 and Rb, which leads to the formation of cervical lesions. The late genes (L1 and L2) encode the structural proteins that form the viral capsid. The LCR, a non-coding region, regulates viral DNA replication and transcription. The genome is tightly linked to the differentiation of the host epithelial cells, allowing HPV to persist and replicate in a tissue-specific manner. Therefore, the goal of many recent studies has been identifying potential inhibitors of the HPV oncoprotein, taking into account the fact that there is still the lack of specific treatment of HPV infection (4, 5).
Previous studies have shown that one in three men is infected with HPV (6). In 2022, 662 301 women were diagnosed with cervical cancer worldwide, which is further challenging given HPV's oncogenic potential (7). In order to prevent the development of premalignant and malignant lesions, various natural substances have been tested as therapeutics for HPV infection. Several studies have so far offered some of the natural inhibitors for HPV with a relatively new approach - in silico, using computer simulations, which are a good basis for in vitro and in vivo studies (8, 9).
Alchemilla vulgaris, commonly known as lady’s mantle, is a perennial herb native to Europe and parts of Asia. It belongs to the Rosaceae family. Traditionally used in folk medicine, the plant has been valued for its astringent, anti-inflammatory, and wound-healing properties - especially in women’s health for treating menstrual disorders and aiding postpartum recovery. Chemically, it is rich in tannins, flavonoids, and phenolic acids, contributing to its antioxidant and antimicrobial effects. Today, it continues to attract scientific interest for its potential therapeutic roles supported by both traditional use and emerging pharmacological studies.
A. vulgaris is a plant that exhibits its inhibitory antioxidant, antiviral and anticancer effects in several studies. The phenolic compounds quercetin, catechin, apigenin, luteolin, caffeic, and gallic acid are the basis for this plant's biological actions. All of these substances have shown anti-inflammatory, antioxidant and/or anticancer effects in previous studies. Alchemilla v. components have shown antiviral and immunomodulatory potential (10-13).
2. OBJECTIVE
Therefore, the aim of this study was to examine the inhibitory potential of the compounds of Alchemilla v. using in silico methods with the HPV 16 E6 oncoprotein. After the docking analysis, the component with the lowest binding energy will be further examined and evaluated.
3. MATERIAL AND METHODS
Molecular docking
The target protein structure was retrieved from the Protein Data Bank (http://www.rcsb.org/pdb) in PDB format. Prior to docking, the protein was prepared by removing unnecessary molecules such as water and heteroatoms while retaining essential ions if relevant to the active site. The structure was optimized by adding polar hydrogens and assigning appropriate atomic charges using AutoDock Tools to ensure accurate docking predictions. Energy minimization was performed to refine the structure and eliminate steric clashes. The final processed protein structure was saved in pdbqt format for molecular docking.
The selected ligands, including apigenin, caffeic acid, catechin, gallic acid, luteolin, and quercetin, were sourced from PubChem in .sdf format. The structures were converted into 3D formats and optimized using Open Babel to minimize energy and ensure proper geometry. Partial atomic charges were assigned, and rotatable bonds were defined to allow flexibility during docking. The optimized ligands were subsequently converted into pdbqt format to be compatible with the docking software.
The docking site was defined based on known active site residues based on prior literature or known binding sites. A grid box was set around this region using AutoDock Tools to ensure complete coverage of the binding pocket, allowing proper ligand accommodation. The grid box dimensions were adjusted to encapsulate the entire active site while maintaining computational efficiency. The center coordinates of the grid were determined to optimize ligand positioning and enhance the accuracy of docking predictions.
Molecular docking was conducted using AutoDock Vina version 1.1.2. to predict potential binding affinities between the target protein and selected ligands. The prepared protein and ligand files were used as inputs, and docking was performed under default parameters with an exhaustiveness value set to ensure thorough exploration of binding poses. The docking algorithm generated multiple binding conformations ranked by binding energy scores, with the lowest energy conformation indicating the most favorable interaction (14). The docking results were analyzed to determine the binding pose, orientation, and stability of the ligand-protein complexes.
Post-docking analysis
The resulting protein-ligand complexes were visualized using Discovery Studio (15) to analyze key molecular interactions. Hydrogen bonds, pi interactions, van der Waals forces, and hydrophobic contacts were identified and evaluated to understand their contributions to binding stability (16). Structural alignment of the docked complexes was performed to compare the binding modes of different ligands. Additionally, the root-mean-square deviation (RMSD) of ligand conformations was assessed to measure variations in binding positions. The binding affinities of all ligands were compared, and the highest-ranking ligand was identified for further validation.
Molecular dynamics simulation
The molecular dynamics (MD) simulation of 4XR8 in complex with quercetin was performed using Desmond (Schrödinger Suite) to assess the structural stability and dynamic behavior of the protein-ligand complex (17). The protein and ligand were preprocessed using the Protein Preparation Wizard, where missing hydrogen atoms were added, bond orders were assigned, and the system was minimized. The OPLS4 force field was applied to parameterize the system. The ligand topology was generated using the LigPrep module, ensuring correct protonation states at physiological pH. The complex was solvated in an explicit TIP3P water model within an orthorhombic simulation box, maintaining a 10 Å buffer region around the protein. Counter ions (Na+ and Cl−) were added to neutralize the system, and 0.15 M NaCl was used to mimic physiological conditions. Energy minimization was performed to remove steric clashes, followed by equilibration under the NPT ensemble (300 K temperature and 1 atm pressure) using the Berendsen thermostat and barostat. The production MD run was carried out for 100 ns with a 2fs time step, employing the Martyna-Tobias-Klein barostat and Nose-Hoover thermostat for stable temperature and pressure control. Long-range electrostatics were handled using the Particle Mesh Ewald (PME) method, and a cutoff of 9 Å was used for van der Waals interactions (18, 19).
4. RESULTS
Interaction profiles of ligands with HPV 16 E6 oncoprotein
Molecular docking studies were conducted to evaluate the binding affinity and interaction profile of six selected ligands apigenin, caffeic acid, catechin, gallic acid, luteolin, and quercetin with the maltose-binding periplasmic protein (PDB ID: 4XR8), as shown in Figure 1. The docking results provided insights into the nature and strength of ligand-protein interactions, which were assessed based on binding energy values, hydrogen bonding, pi interactions, and van der Waals forces.
Figure 1. 2D interaction diagrams of selected phytochemicals showing key binding interactions with the target protein.
Among the six ligands, quercetin exhibited the highest binding affinity (-8.9 kcal/mol), followed by apigenin and luteolin (-8.7 kcal/mol each), catechin (-8.4 kcal/mol), caffeic acid (-7.3 kcal/mol), and gallic acid (-6.8 kcal/mol), as shown in table 1. Paclitaxel, used as a positive control, showed a high binding affinity (-9.1 kcal/mol). Apigenin demonstrated strong hydrogen bonding with Lys16 and Asp66, with additional stabilization through pi interactions such as pi-pi stacking with Tyr156 and pi-anion interactions with Asp15. Caffeic acid also exhibited stable binding, primarily via hydrogen bonds with Lys16 and Arg67 and a network of pi interactions involving Tyr156 and Trp341. Gallic acid’s stability was enhanced by hydrogen bonds with Asp66, Arg67, and Glu154, along with a pi-pi stacking interaction with Trp341. Luteolin displayed key hydrogen bonds with Lys16 and Glu112, and a unique pi-sulfur interaction with Met331, contributing to its strong binding potential. Catechin exhibited a playebalanced interaction profile, featuring hydrogen bonding with Asp66 and Asn13, as well as prominent pi interactions such as pi-pi stacking with Tyr156 and pi-sulfur interactions with Met331.
Table 1. Binding affinities of selected ligands with 4XR8.
| Ligand | PubChem CID | Binding affinity (kcal/mol) |
|---|---|---|
| Paclitaxel (positive control) | 36314 | -9.1 |
| Quercetin | 5280343 | -8.9 |
| Apigenin | 5280443 | -8.7 |
| Luteolin | 5280445 | -8.7 |
| Catechin | 9064 | -8.4 |
| Caffeic Acid | 689043 | -7.3 |
| Gallic Acid | 370 | -6.8 |
Quercetin exhibited the strongest binding affinity, followed closely by apigenin and luteolin. Catechin also demonstrated significant binding potential, while caffeic acid and gallic acid showed comparatively lower affinities. Quercetin, the top-performing ligand, formed hydrogen bonds with Glu45, Glu154, Arg67, and Met331, along with multiple pi interactions that reinforced its strong affinity. The extensive interactions observed among these ligands suggest their significant potential for binding with 4XR8, with quercetin, apigenin, and luteolin emerging as the most promising candidates.
Molecular dynamics simulation of protein-ligand complex
Molecular dynamics simulations were conducted to evaluate the stability and dynamic behavior of the maltose-binding periplasmic protein (4XR8) in complex with quercetin over a 100 ns trajectory. The Root Mean Square Deviation analysis indicated that the protein maintained a stable conformation throughout the simulation, with RMSD values fluctuating between 2.0 and 2.4 Å for most of the trajectory, as shown in Figure 2 (A). A slight increase was observed after 80 ns, reaching approximately 3.2 Å, which could be attributed to localized flexibility within specific regions of the protein. The ligand RMSD exhibited higher fluctuations, ranging from 1.2 to 5.0 Å, with significant deviations occurring between 40 and 80 ns, likely due to conformational adjustments within the binding pocket. After 80 ns, the ligand stabilized around 4.5 to 5.0 Å, indicating that while quercetin remained bound, it explored multiple binding poses.
Figure 2. RMSD analysis of 4XR8 in complex with quercetin over a 100 ns MD simulation (A) RMSF analysis of 4XR8 in complex with quercetin over a 100 ns MD simulation (B) SSE analysis of 4XR8 in complex with quercetin over 100 ns (C).
Root Mean Square Fluctuation analysis provided insights into the local flexibility of individual residues, as shown in Figure 2 (B). Most residues exhibited minimal fluctuations (~0.5 to 1.5 Å), suggesting overall structural stability, while moderate fluctuations (~1.5 to 2.5 Å) were observed in loop regions. Notably, the C-terminal region showed higher fluctuations (~4.5 Å), which is expected due to its inherent flexibility. Residues between indices 150-250 displayed moderate fluctuations, suggesting potential involvement in ligand accommodation.
The secondary structure analysis via the SSE histogram and timeline revealed that the overall secondary structure remained intact, with alpha-helices and beta-sheets maintaining consistent stability, as shown in Figure 2 (C). The SSE timeline demonstrated that structured elements were preserved throughout the 100 ns simulation, indicating that quercetin binding did not cause significant conformational alterations.
The protein-ligand interaction analysis provided crucial insights into the nature of quercetin's binding stability. The interaction fraction graph showed persistent hydrogen bonding interactions with key residues, including Asp-15, Lys-16, Glu-112, Asp-66, and Trp-231, contributing significantly to the ligand’s stability, as shown in Figure 5. Water-bridged interactions were also observed, particularly with residues like Asp-66 and Asn-228, further reinforcing ligand retention. Hydrophobic interactions with residues such as Tyr-156 and Phe-157 helped maintain the ligand’s orientation within the binding site.
The ligand torsion profile analysis indicated that most rotatable bonds maintained stable conformations, with only minor flexibility observed in certain regions, which might contribute to quercetin’s adaptive binding behavior, as shown in Figure 3 (B).
Figure 3. Protein-ligand interaction analysis of 4XR8 with quercetin over 100 ns, highlighting key residues involved in hydrogen bonding, water bridges, and hydrophobic interactions contributing to binding stability (A) Ligand torsion profile of quercetin in complex with 4XR8 over 100 ns, showing the flexibility and conformational stability of rotatable bonds within the binding pocket (B) Analysis of quercetin's structural properties over 100 ns, including RMSD, SASA, PSA, rGyr, intraHB, and MolSA, highlighting its stability and binding behavior within the 4XR8 complex (C).
Other molecular properties such as Solvent Accessible Surface Area (SASA), Polar Surface Area (PSA), and Radius of Gyration (rGyr) remained stable throughout the simulation, further confirming the ligand's structural integrity, as shown in Figure 3 (C).
5. DISCUSSION
The connection between HPV infection and cervical cancer has been proven. There are various therapeutic procedures used in the treatment of infection, many of which have recently been intensively researched. Bioinformatics analyses are methods that have found application in testing new therapeutics using computer bioanalytical programs (17). These in vitro analyses have so far examined different groups of natural bioactive substances in the treatment of various viral infections (18-20).
Several studies have been conducted that also aimed to find potential natural inhibitors of the HPV by targeting target domains through in silico screening. Withaferin A (-5.85 kcal/mol), artemisin (-5.68 kcal/mol), ginkgetin (-8.46 kcal/mol) and lobeline (-7.9 kcal/mol) are examples of natural substances with strong binding affinity and inhibitory role (9, 11, 21). In our study, all six ligands (apigenin, caffeic acid, catechin, gallic acid, luteolin and quercetin) demonstrate strong binding potential with the protein, each exhibiting a combination of hydrogen bonds, pi interactions, and van der Waals forces contributing to their stability and specificity. Quercetin stands out with the highest binding energy (-8.9 kcal/mol).
The molecular docking results provide key insights into the stability and specificity of flavonoid-based ligands in binding with the HPV 16 E6 oncoprotein. The superior binding energy of quercetin can be attributed to its extensive hydrogen bonding network and multiple stabilizing pi interactions, positioning it as a strong candidate for further computational and experimental validation. The presence of pi-sulfur interactions in catechin, luteolin, and quercetin complexes highlights the importance of sulfur-based stabilization in ligand-protein interactions. Hydrogen bonding was found to be a crucial determinant of ligand specificity, with additional reinforcement from van der Waals forces ensuring ligand stability within the binding site. The comparative binding affinities suggest that flavonoid ligands, particularly quercetin, apigenin, and luteolin, have significant potential in therapeutic applications. In our molecular docking analysis, we used paclitaxel (chemotherapy drug) as a positive control, following the study by Elfiky AA et al (22). These findings warrant further validation through molecular dynamics simulations to assess the dynamic behavior and long-term stability of these ligand-protein complexes under physiological conditions.
Studies have shown that Alchemilla v. possesses a range of biological activities. Research supports its antioxidant effects, helping to neutralize free radicals and reduce oxidative stress (23). Its anti-inflammatory effects have been observed through downregulation of pro-inflammatory markers such as TNF-α and IL-1β (24). Several in vitro and in vivo studies also report antimicrobial activity, particularly against Gram-positive bacteria (25). In cancer models, the plant has shown pro-apoptotic and antiproliferative effects on tumor cells, suggesting a role in supporting anticancer strategies (26). Emerging cardiovascular research indicates it may also modulate oxidative stress and inflammation in cardiac tissue, hinting at possible cardioprotective properties (12).
Quercetin as a flavonoid has shown its multiple benefits for human health. One of its characteristics and biopotentials is its antiviral activity, which has been tested against many viruses. Its combined antiviral and anti-inflammatory effects have been proven to disrupt the life cycle of the virus, thereby reducing the inflammation caused by the viral infection. It has shown its antiviral effect against Hepatitis C virus, Ebola and Influenza A virus (27-30). In previously conducted studies, quercetin has also shown promising potential within the framework of molecular simulation (31,32).
The molecular dynamics simulation results reinforce the stability and strong binding affinity of quercetin with 4XR8. The RMSD analysis suggests that while the protein remained stable, the ligand exhibited moderate conformational flexibility, likely aiding in optimizing interactions within the binding site. RMSF findings support the idea that loop regions and solvent-exposed residues contribute to minor structural flexibility, yet the overall integrity of the protein was maintained. The persistence of secondary structural elements over 100 ns highlights the robustness of the complex, suggesting that quercetin binding does not cause significant unfolding or destabilization.
The protein-ligand interaction analysis further supports quercetin’s strong binding potential, as evidenced by stable hydrogen bonds, water-bridged interactions and hydrophobic contacts. The presence of highly conserved interactions with Asp-15, Glu-112, and Trp-231 suggests that these residues play a crucial role in stabilizing the ligand within the binding site. The ligand torsion profile and SASA analysis confirm that quercetin maintains an optimal binding pose while allowing minor flexibility, which may enhance its adaptability within the active site.
6. CONCLUSION
This study provides strong evidence supporting the stable and strong binding affinity of quercetin to HPV 16 E6 oncoprotein, as demonstrated through molecular dynamics simulations. The structural stability of the protein-ligand complex over a 100 ns trajectory, with well-maintained secondary structural integrity and persistent key interactions, underscores quercetin’s potential as a robust ligand. While the ligand exhibited moderate conformational flexibility, this adaptability likely contributes to its ability to optimize interactions within the binding site. The presence of conserved hydrogen bonding, hydrophobic interactions, and water-bridged contacts further reinforces quercetin’s role as a promising molecular candidate for further exploration. Further validation using MM-GBSA, MM-PBSA, and advanced computational methods is required. Moreover, in vitro and in vivo studies are essential to confirm quercetin’s potential as a viable candidate for therapeutic applications in HPV infection treatment.
Patient Consent Form:
Not applicable.
Author's Contribution::
The all authors were involved in all steps of preparation of this article. Final proofreading was made by the first author.
Conflicts of interest:
There are no conflicts of interest.
Financial support and sponsorship:
None.
REFERENCES
- 1.Bray F, Laversanne M, Sung H, Ferlay J, Siegel RL, Soerjomataram I, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2024;74(3):229–263. doi: 10.3322/caac.21834. [DOI] [PubMed] [Google Scholar]
- 2.Pimple S, Mishra G. Cancer cervix: Epidemiology and disease burden. Cytojournal. 2022;19:21. doi: 10.25259/CMAS_03_02_2021. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Okunade KS. Human papillomavirus and cervical cancer. J Obstet Gynaecol. 2020;40(5):602–608. doi: 10.1080/01443615.2020.1713592. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Burk RD, Harari A, Chen Z. Human papillomavirus genome variants. Virology. 2013;445(1-2):232–243. doi: 10.1016/j.virol.2013.07.018. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Wolf J, Kist LF, Pereira SB, Quessada MA, Petek H, Pille A, et al. Human papillomavirus infection: Epidemiology, biology, host interactions, cancer development, prevention, and therapeutics. Rev Med Virol. 2024;34(3):e2537. doi: 10.1002/rmv.2537. [DOI] [PubMed] [Google Scholar]
- 6.Bruni L, Albero G, Rowley J, Alemany L, Arbyn M, Giuliano AR, et al. Global and regional estimates of genital human papillomavirus prevalence among men: a systematic review and meta-analysis. Lancet Glob Health. 2023;11(9):e1345–e1362. doi: 10.1016/S2214-109X(23)00305-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.International Agency for Research on Cancer, World Health Organization Cancer today. GLOBOCAN. 2022 [Google Scholar]
- 8.Vani V, Venkateshappa S, Nishitha R, Shashidhar H, Hegde AB, Alagumuthu M. In silico Analysis of Natural Inhibitors against HPV E6 Protein. Curr Comput Aided Drug Des. 2024;20(3):303–311. doi: 10.2174/1573409919666230310144550. [DOI] [PubMed] [Google Scholar]
- 9.Kumar S, Jena L, Sahoo M, Kakde M, Daf S, Varma AK. In Silico Docking to Explicate Interface between Plant-Originated Inhibitors and E6 Oncogenic Protein of Highly Threatening Human Papillomavirus 18. Genomics Inform. 2015;13(2):60–67. doi: 10.5808/GI.2015.13.2.60. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Vlaisavljević S, Jelača S, Zengin G, Mimica-Dukić N, Berežni S, Miljić M, et al. Alchemilla vulgaris agg. (Lady's mantle) from central Balkan: antioxidant, anticancer and enzyme inhibition properties. RSC Adv. 2019;9(64):37474–37483. doi: 10.1039/c9ra08231j. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Nabati F, Moradi M, Mohabatkar H. In silico analyzing the molecular interactions of plant-derived inhibitors against E6AP, p53, and c-Myc binding sites of HPV type 16 E6 oncoprotein. Mol Biol Res Commun. 2020;9(2):71–82. doi: 10.22099/mbrc.2020.36522.1483. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Anajirih N, Abdeen A, Taher ES, Abdelkader A, Abd-Ellatieff HA, Gewaily MS, et al. Alchemilla vulgaris modulates isoproterenol-induced cardiotoxicity: interplay of oxidative stress, inflammation, autophagy, and apoptosis. Front Pharmacol. 2024;15:1394557. doi: 10.3389/fphar.2024.1394557. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.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(2):455–461. doi: 10.1002/jcc.21334. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Morris GM, Goodsell DS. Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function. J Comput Chem. 1998;19:1639–1662. doi: 10.1002/(SICI)1096-987X(19981115)19:14<1639::AID-JCC10>3.0CO;2-B. [DOI] [Google Scholar]
- 15.Sharma S, Sharma A, Gupta U. Molecular Docking Studies on the Anti-Fungal Activity of Allium Sativum (Garlic) Against Mucormycosis (Black Fungus) by BIOVIA Discovery Studio Visualizer 21.1.0.0. Annals of Antivirals and Antiretrovirals. 2021;5(1):028–032. doi: 10.21203/rs.3rs-888192/v1. [DOI] [Google Scholar]
- 16.Rehman HM, Sajjad M, Ali MA, Gul R, Irfan M, Naveed M, et al. Identification of NS2B-NS3 Protease Inhibitors for Therapeutic Application in ZIKA Infection: A Pharmacophore-Based High-Throughput Virtual Screening and MD Simulations Approaches. Vaccines. 2023;11(1):131. doi: 10.3390/vaccines11010131. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Cui H, Ma R, Hu T, Xiao GG, Wu C. Bioinformatics Analysis Highlights Five Differentially Expressed Genes as Prognostic Biomarkers of Cervical Cancer and Novel Option for Anticancer Treatment. Front Cell Infect Microbiol. 2022 17;12:926348. doi: 10.3389/fcimb.2022.926348. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Dassanayake MK, Khoo TJ, Chong CH, Di Martino P. Molecular Docking and In-Silico Analysis of Natural Biomolecules against Dengue, Ebola, Zika, SARS-CoV-2 Variants of Concern and Monkeypox Virus. Int J Mol Sci. 2022;23(19):11131. doi: 10.3390/ijms231911131. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Shaikh IA, Muddapur UM, Krithika C, Badiger S, Kulkarni M, Mahnashi MH, et al. In Silico Molecular Docking and Simulation Studies of Protein HBx Involved in the Pathogenesis of Hepatitis B Virus-HBV. Molecules. 2022;27(5):1513. doi: 10.3390/molecules27051513. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Saric B, Tomic N, Kalajdzic A, Pojskic N, Pojskic L. In silico analysis of selected components of grapefruit seed extract against SARS-CoV-2 main protease. The EuroBiotech J. 2021;5(s1):5–12. doi: 10.2478/ebtj-2021-0015. [DOI] [Google Scholar]
- 21.Jothi J, Balagurusamy K, Suresh S, Jeeva Gladys R. Molecular Interactions of Plant-Derived Inhibitors from Euphorbia Hirta Against Binding Sites of HPV E6 and E7 Oncoproteins - An in-Silico Analysis. International Journal of Ayurvedic Medicine. 2024;15(3):666–672. doi: 10.47552/ijam.v15i3.4765. [DOI] [Google Scholar]
- 22.Elfiky AA, Saied HR, Ali MA. Targeting of HPV E6 at the binding sites to the host-cell E6AP, p53, and the endoplasmic reticulum-resident chaperone, GRP78. J Biomol Struct Dyn. 2024;42(22):12385–12395. doi: 10.1080/07391102.2023.2270067. [DOI] [PubMed] [Google Scholar]
- 23.Kanak S, Krzemińska B, Celiński R, Bakalczuk M, Dos Santos Szewczyk K. Phenolic Composition and Antioxidant Activity of Alchemilla Species. Plants. 2022;11(20):2709. doi: 10.3390/plants11202709. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Korun ZEU, Gocmez SS, Furat S, Sarihan KK, Eraldemir FC, Akpulat HA, et al. Beneficial Effects of Alchemilla vulgaris in DHEA-Induced Rat Model of Polycystic Ovary Syndrome. Reprod Sci. 2025 Jun 23; doi: 10.1007/s43032-025-01885-9. Online first. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Edrah SM. Evaluation of antimicrobial activities of Alchemilla vulgaris and Portulaca oleracea ethanolic extracts and correlation with their phytochemical profiles. Biofarmasi J Nat Prod Biochem. 2017;15(2):91–94. doi: 10.13057/biofar/f150205. [DOI] [Google Scholar]
- 26.Moqidem Y. American University in Cairo; 2021. Evaluation of the Anticancer Potential of Alchemilla vulgaris Extract Against Human Neuroblastoma Cells. Master's Thesis. AUC Knowledge Fountain. [Google Scholar]
- 27.Di Petrillo A, Orrù G, Fais A, Fantini MC. Quercetin and its derivates as antiviral potentials: A comprehensive review. Phytother Res. 2022;36(1):266–278. doi: 10.1002/ptr.7309. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Mirza MA, Mahmood S, Hilles AR, Ali A, Khan MZ, Zaidi SAA, et al. Quercetin as a Therapeutic Product: Evaluation of Its Pharmacological Action and Clinical Applications-A Review. Pharmaceuticals (Basel) 2023;16(11):1631. doi: 10.3390/ph16111631. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Korić E, Gušić I, Durić K, Žiga-Smajić N, Osmanović A, Kapo N, et al. Anti-inflammatory potential of polyphenols: Combining in silico prediction and in vivo data. JHSCI. 2024;14(2):84–91. doi: 10.17532/jhsci.2024.2481. [DOI] [Google Scholar]
- 30.Mahmutović-Dizdarević I, Mesić A, Jerković-Mujkić A, Žujo B, Avdić M, Hukićc M, et al. Biological potential, chemical profiling, and molecular docking study of Morus alba L. extracts. Fitoterapia. 2024;177:106114. doi: 10.1016/j.fitote.2024.106114. [DOI] [PubMed] [Google Scholar]
- 31.Shaw S, Chourasia M, Nayak R, Kumeria T, Ghosh MP, Santoshi S, et al. Molecular interaction of quercetin and its derivatives against nucleolin in breast cancer: in-silico and in-vitro study. J Biomol Struct Dyn. 2024;11:1–12. doi: 10.1080/07391102.2024.2326668. [DOI] [PubMed] [Google Scholar]
- 32.Maran M, Gangadharan S, Emerson IA. Molecular dynamics study of quercetin families and its derivative compounds from Carica papaya leaf as breast cancer inhibitors. Chem Phys Let. 2022;793:139470. doi: 10.1016/j.cplett.2022.139470. [DOI] [Google Scholar]