INTRODUCTION:

Extensive use of skin-whitening cosmetics by individuals of all age groups, is indicative of the awareness regarding aesthetic appearance in current times. Routine exposure of skin to sunlight and occupational hazards can lead to disorders related to skin pigmentation; for instance, hyperpigmentation, dark skin, melasma, age spots, freckles, solar lentigo, etc.¹

Synthetic skin whitening agents such as hydroquinone, corticosteroids, kojic acid, arbutin, and niacinamide are popular for management of these disorders²; however, their safety is still in question since these agents are recognized to be associated with development of issues like ochronosis, mutagenicity, carcinogenesis, and other local and systemic side effects, etc.³. To manage these impediments, both dermatologists and patients desire skin-whitening products which shall be safe for long-term use⁴. Thus, in recent times, the demand for skin-whitening cosmetics has increased progressively across the globe. Under such circumstances, the potential skin whitening phytoactives become the agents of choice for long-term usage with least safety concerns⁵. The benefits offered by natural and botanical extracts are expected to provide better opportunities for the progress of new products for addressing pigmentation-related disorders^{6, 7}. If such skin whitening agents are a part of food or nutrient items, then they deem to be additionally safe^8-10.

The reported data suggests that, in India, about 60% of skin whitening products are offered in the skincare range. The survey also suggest that about 40% of women use skin whitening products twice a day, however, 17% among them experience adverse effects¹¹. Considering the increased use of cosmetics, the development of plant-based cosmetics offering lesser side effects coupled with cost-effectiveness seems imperative¹².

Before the research plan was envisaged, the cardinal role of melanin in hyper pigmentation needed to be reviewed. Essentially, melanin is the dominant pigment responsible for the color of skin and hair. Melanin is produced within the skin through a biochemical process, melanogenesis. It takes place in melanosomes, membrane-bound organelle located within the melanocytes at the stratum basale in the epidermis¹³. The elaborate mechanism of melanogenesis has been depicted in (figure 1).

Figure 1. Pathways for the process of melanogenesis.

A strategy had been devised to inhibit melanin synthesis as a prospective mean for skin whitening. Initially, the structures of the active melanin inhibiting phyto compounds were collected after thorough search from the scientific literature. Subsequently, molecular docking protocols were developed using V-Life Molecular Design Suite (MDS) version 4.6 (V-Life Technologies, India). Thereafter, 112 structures were retrieved from natural source databases and were virtually analyzed to obtain the skin whitening ‘hits’. The obtained hits were scrutinized further to understand the crucial structural features essential for good protein-ligand interactions for antimelanogenic activity¹⁴. The pharmacophore modeling of active molecules was performed for gaining a better understanding of the structural components accountable for the antimelanogenic activity. This would further necessary for the development of lead molecules in drug discovery¹⁵. Based on virtual screening of phytoconstituents (docking scores and PASS online), plants extract i.e. Mulberry (Morus alba L.), Tulsi (Ocimum tenuiflorum), and White Sesame (Sesamum indicum L.), were chosen for the development of the formulation. The nanoemulsion (o/w) based on the plant extracts was formulated and evaluated for globule size, polydispersity, zeta potential, and antimelanogenic potential on the B16F10 Cell line¹⁶.

METHODS:

In silico screening of phytoconstituents for antimelanogenic activity:

Based on traditional claims, Mulberry (Morus alba L.), Black Sesame (Sesamum radiatum), White Sesame (Sesamum indicum L.), Aloe (Aloe barbadensis), Tulsi (Ocimum tenuiflorum), and Saffron (Crocus sativus) were chosen and a total of 112 phytoconstituents from these plants were chosen as ligands for the current study. Molecular modeling studies were completed by V-life MDS software, using the tyrosinase enzyme. The crystal structure of tyrosinase complexed with kojic acid (PDB: 3NQ1) was downloaded from Protein Data Bank in PDB format, from a web source (www.rcsb.org)¹⁷.

Protein structure preparation and Ramachandran plot analysis

The reference ligand KOJ-13518 was extracted from the protein structure using the Biopredicta tool of V-LifeMDS. The Biopredicta module was utilized to find out the active spots of the protein. The module having the utility to display the distribution of amino acids in allowed and disallowed regions using Ramachandran plot analysis was also explored¹⁸.

Ligand preparation

For docking studies, the two dimentional structures of selected 112 phytoconstituents were downloaded from the PubChem database in (SDF) format and then energy optimized using the Merck Molecular Force Field (MMFF) method. Analogues with the lowest energies were nominated for the docking study¹⁹.

Molecular docking studies

In silico screening of 112 phytoconstituents was performed to seek the best possible tyrosinase inhibitor (skin whitening agent) using the GRIP based Batch Docking protocol of the Biopredicta module. A flexible docking mode was chosen, wherein internal ligand torsions were allowed to change, while the protein remained fixed. All energy minimized ligands were scrutinized for their best-predicted poses of the interaction with the enzyme. Docking was completed by keeping convergence factor of 0.001 for 10,000 generations with dock score and using 30 placements of the structure with a rotation angle of 10°. Finally, the enzyme-specific composite model was formed based on the parameters like through a hydrogen bond, π–π, charge interactions, and docked compound alignment within the active site, having least binding energy^20-22.

Pharmacophore modeling

Using the MolSign module of V-LifeMDS, a set of potent compounds was found and aligned with the clinically described active tyrosinase inhibitor (kojic acid) by pharmacophore modeling. At least of three pharmacophoric features were required to create the pharmacophore model, which includes a set of three-dimensional attributes significant for the bioactive ligand. The tolerance limit was set at 10 Å, indicating the ﬂexibility for comparison between two feature combinations across two molecules, and 10 Å as the extreme distance allowed between two features^15,
23.

In silico prediction of skin whitening activity

Few phytochemicals were selected based on molecular docking studies for in silico prediction of skin whitening activity. PASS (Prediction of Activity Spectra for Substances) software was utilized (https://www.way2drug.com/passonline/predict.php) to estimate the skin whitening activity profiles for selected molecules (accessed on 29 January 2024). Pa value and Pi value were determined for selected chemical structures using PASS online and prediction was made²⁴.

Development of nanoemulsion and its evaluation for antimelanogenic activity:

Initially, the plants were authenticated viz; Sesamum indicum L., Ocimum tenuiflorum L., and Morus alba L., and nominated plant fragments were dried after spraying the formalin, and herbarium sheets were prepared (29 x 42 cm sheet) after 1 week. The herbarium sheets were submitted to Botany Department, Shivaji University, Kolhapur (MS), India. Further, the extraction of plant parts was performed by the soxhlet extraction method²⁵. At the outset, plant fragments were collected, dried, and crushed using a mechanical grinder. Extraction of Ocimum tenuiflorum L., and Morus alba L. was performed using ethanol, and Sesamum indicum L. was extracted using n-Hexane, at 78℃ and 60℃ respectively. The extracts were dried using a rotary vacuum evaporator (Heidolph, Germany), at 40-45℃ and collected in vials, and stored in a refrigerator for further use²⁶.

For formulation of nanoemulsion, the surfactant (tween 80) and co-surfactant (ethanol) were designated based on the solubility studies of extracts. A pseudo ternary phase diagram was created using sesame oil (oil phase), Tween 80:Ethanol i.e., S_mix (surfactant), and distilled water (aqueous phase) by aqueous titration method. The ratios of S_mix used were 1:1, 2:2, 3:1, and 4:1. For generating the phase diagram, oil and S_mix were used in the ratio, from 1:9 and 9:1. The Pseudoternary phase diagram of nanoemulsion (o/w) formulation was plotted by CHEMIX School software (Chemistry Software – Science Education) to determine the suitable combination of surfactants and oil by aqueous titration method. Further, the o/w type nanoemulsion was prepared by homogenizing (High-Pressure homogenizer method) a mixture of the sesame oil, water, tween 80, ethanol, and plant extracts. Total four nanoformulation batches (A, B, C, and D) were examined visually for creaming, clarity and phase separation. Subsequently, all the samples were diluted with water to 10 ml and assessed for particle size, zeta potential, and polydispersity index (PDI) by dynamic light scattering in a zetasizer (HORIBA scientific SZ-100 by quartz cuvette cell 4 openings). The measurements were executed in triplicate to avoid errors²⁷.

MTT Assay:

The B16F10 melanoma cell line was used to investigate the antimelanogenic activity of formulated nanoemulsion. In this study, cells were incubated at a concentration of 1 × 10⁴cells/ml in a culture medium for 24 hrs at 37°C and 5% CO₂. Further, cells were seeded at a concentration (70µl) 10⁴ cells/well in 100 µl culture medium, and 100µl sample A (marketed gel formulation) and test nanoformulation batch B (10, 30, 100µL) into microplates respectively (tissue culture grade, and 96 wells). Cell cultures were allowed to incubate at 37°C and 5% CO₂for 24 h, in a CO₂incubator (Thermo Scientific BB150). After incubation, the medium was completely removed, and 20 µl of MTT reagent (5mg/min PBS) was added. Upon the addition of MTT, cells were incubated for 4 hrs at 37℃ in a CO₂ incubator. The wells were observed for formazan crystals under a microscope. Only viable cells were capable to turn the yellowish MTT into a dark-colored formazan. After removing the medium completely, 200µl of DMSO was added (kept for 10 min) and incubated at 37℃ (wrapped with aluminum foil). Finally, the absorbance of each sample was measured by a microplate reader (Benesphera E21) at a wavelength of 550 nm²⁸.

RESULTS AND DISCUSSION:

In silico screening of phytoconstituents for antimelanogenic activity:

In the discovery of lead compounds, the role of in silico phytochemical screening is of paramount importance. Mainly, the molecular docking study unfolds the interactions between ligands (phytoconstituents) and proteins through binding energy (BE), and interactions like π–π, hydrogen, electrostatic/charge, etc.²⁹. The virtual interaction study (docking) carried out in our laboratory, revealed varying patterns for the binding energy, for test ligand and standard ligand kojic acid. It was detected that the protein residue GLU274A and MET277A were involved in H-bonding with the kojic acid molecule and had BE value of -36.301. Ramachandran plot analysis (figure 2) exhibited that, the 3NQ1 protein contains 1.42 % amino acid residues distributed in the disallowed region, 11.39% distributed in the allowed region, 83.99 % in the core region, 3.20% generously allowed region, suggesting the stability of selected peptide conformers.

Figure 2. Ramachandran plot for 3NQ1 protein.

Mainly, BE and at least one molecular interaction of phytoconstituents were the basis for further analysis of phytoconstituents. Out of 112 phytoconstituents as given in (Table S1 in supplementary material), 16 molecules, namely kuwanol, sesamolin, rosmarinic acid, astragalin, folic acid, riboflavin, sasaminol, albanol, rutin, morusin, mulberrofuran, moracin- O, mulberroside, crocin, picrocrocin, barbaloin showed tyrosinase inhibition activity. Amongst reported tyrosinase inhibitors, kuwanol showed promising BE (-81.294) and barbaloin showed a poor BE (-38.792)³⁰. The remaining phytoconstituents showed BE values between the values of kuwanol and barbaloin. The standard kojic acid value was observed to be -36.301 as shown in (Table S2 in supplementary material). Therefore, BE and molecular interaction data demonstrated that phytomolecules kuwanol, sesamolin, rosmarinic acid, astragalin, folic acid, riboflavin, sesaminol, albanol, rutin, morusin, mulberrofuran, moracin-O, mulberroside, barbaloin are potential ligands obtained from Sesamum indicum L., Ocimum tenuiflorum L., and Morus alba L. Hence, the aforementioned skin-whitening plants were selected, for the novel skin-whitening nanoformulation development.

Pharmacophore modeling:

The pharmacophore model defines the essential structural requirement of the chemical for the therapeutic/biological effect to be evoked³¹. Herein, we developed the pharmacophore for tyrosinase inhibitor as depicted in (figure 3) and that of kojic acid (standard) in (figure 4). The molecular structure of kojic acid essentially contains three pharmacophoric features, namely two H-bond acceptors and one H-bond donor, for tyrosinase inhibition. The phytochemicals folic acid, astragalin, and barbaloin have shown these three minimum pharmacophoric features in them. Even, RMSD for these molecules were found to be 0.677962, 0.795954, and 0.888255 respectively, indicating the similarity between the pharmacophoric features of these molecules with standard kojic acid.

Figure 3. Pharmacophore modeling of kojic acid with other molecules.

Figure 4. Pharmacophore modeling of kojic acid (standard).

In silico prediction of skin whitening activity

In silico prediction of skin whitening activity has been revealed from the high Pa value, probability "to be active" for skin whitening activity and low Pi value, probability "to be inactive". The (Table 1) deciphers the activities for selected phyto leads on the basis of role as a skin whitener, melanin inhibitor and antioxidant.

Table 1. PASS online results for selected phytochemicals.

Sr. No.	Name of compound	Pa value	Pi value	Activity
1	Kuwanol	0.319	0.008	Skin whitener
		0.275	0.015	Melanin inhibitor
		0.412	0.011	Antioxidant
2	Sesamolin	0.203	0.029	Skin whitener
		0.387	0.005	Melanin inhibitor
		0.964	0.002	Antioxidant
3	Rosmarinic acid	0.329	0.007	Skin whitener
		0.418	0.005	Melanin inhibitor
		0.539	0.005	Antioxidant
4	Astragalin	0.779	0.001	Skin whitener
		0.624	0.002	Melanin inhibitor
		0.907	0.003	Antioxidant
5	Folic acid	-	-	No skin whitening activity
6	Riboflavin	-	-	No skin whitening activity
7	Sesaminol	0.285	0.011	Skin whitener
		0.518	0.003	Melanin inhibitor
		0.584	0.005	Antioxidant
8	Albanol	0.306	0.009	Skin whitener
		0.258	0.018	Melanin inhibitor
		0.391	0.013	Antioxidant
9	Sesamin	0.198	0.031	Skin whitener
		0.375	0.006	Melanin inhibitor
		0.457	0.008	Antioxidant
10	Rutin	0.755	0.002	Skin whitener
		0.674	0.001	Melanin inhibitor
		0.923	0.003	Antioxidant
11	Moracin-O	0.280	0.012	Skin whitener
		0.322	0.010	Melanin inhibitor
		0.617	0.004	Antioxidant

From the PASS online data it has been evident that, kuwanol, sesamolin, rosmarinic acid, astragalin, sesaminol, albanol, sesamin, rutin and moracin-O have excellent skin whitening activity. They showed melanin inhibition and antioxidant potential, both, depicting their combined role in skin whitening. Predominantly, astragalin and rutin showed Pa value 0.779 and 0.755 respectively, thus may act as potent skin whiteners. astragalin and rutin demonstrated potent melanin inhibition as evident from its Pa values 0.624 and 0.674 respectively. Sesamolin (0.964), astragalin (0.907) and rutin (0.923) seems to be potent antioxidants, from the data obtained.

Development of nanoemulsion and its evaluation:

The pseudoternary phase diagram system was adopted to progress nanoemulsions comprising phytoactive-rich fractions of the selected plant extracts. In the case of km 3:1 ratio of tween 80 and ethanol, the maximum monophasic region was observed, amongst phase diagrams reported for all km values. Therefore, a 3:1 ratio of tween 80 and ethanol was selected for the formulation of nanoemulsion. Based on the phase diagram, the composition of water, oil, and surfactant was finalized for the nanoemulsion (o/w) formulation³². The phase diagram enabled the selection of four formulation batches of nanoemulsion, as shown in (figure 5) and (Table 2).

Figure 5. Pseudoternary phase diagram for nanoemulsion at Km 3:1.

Table 2. Composition of phytonanoemulsion formulation.

Formulation Code	Water (ml)	S_mix (ml)	Oil (ml)
A	69	30	1
B	60	35	5
C	35	60	5
D	35	55	10

The nanoemulsion formulations (A, B, C, D) on evaluation revealed that, formulation batch B has the least globule size 67.4 nm (figure 6), and satisfactory polydispersity index (PDI) 0.241,³³ and requisite zeta potential -21.0 mV, as shown in (figure 7). The globule size of batch B was significantly small than the rest formulation batches at p<0.05 (Table 3).³⁴ Thus, nanoemulsion formulation batch B can be inferred optimized batch, due to the smallest globule size with optimum zeta potential. Certainly, batch B reach melanocytes efficiently for antimelanogenic activity to be evoked, and will have reasonable stability on storage, as well.³⁵

Figure 6: Globule size graph for formulation batch B.

Figure 7: Zeta potential graph for formulation batch B.

Table 3. Evaluation data for nanoemulsion formulation batches.

Formulation Code	Globule Size (nm)	Polydispersity index (PDI)	Zeta Potential (mV)
A	106.4 ± 2.2	0.532 ± 0.1	-22.9 ± 1.2
B	67.4 ± 1.1	0.241 ± 0.9	-21.0 ± 0.5
C	426.6 ± 4.4	0.554 ± 1.2	-22.9 ± 0.9
D	219.8 ± 3.9	0.291 ± 0.6	-4.9 ± 0.7

MTT Assay:

The antimelanogenic activity of optimized phytonanoemulsion formulation batch B and standard marketed gel in B16F10 cell lines exhibited that formulation B possesses significant antimelanogenic activity.³⁶ The activity observed for the active-rich extract formulated as a nanoemulsion seemed promising, compared to marketed gel. Although the whole active-rich extract showed promising action on the B16F10 cell line, but, subsequent isolation of active constituents may demonstrate enhanced results. It was worth noting that, an insignificant difference (p>0.05) was observed between the antimelanogenic activity of marketed gel (100 µL) and test formulation batch B at a concentration of 10 µL (Table 4).

Table 4. MTT assay results for antimelanogenic activity on B16F10 Cell lines.

Sample	Concentration (µL)	% Inhibition
Marketed gel	100	63.60 ± 2.31
Batch B	10	65.80 ± 3.65
	30	70.31± 2. 90
	100	78.29 ± 3.01

As the quantity of test formulation was increased, the antimelanogenic activity was also suggestively improved at p<0.05, compared to marketed gel. It means that, the potential antimelanogenic activity of nanoemulsion was evident and well demonstrated through the cell line studies, advocating the suitability of rationally developed nanoemulsion, and opening up a new vista of antimelanogenic phytoactives, as well.³⁷

CONCLUSION:

Virtual screening of phytoconstituents for therapeutic activities has become a powerful tool in drug discovery and could be of great help in the rational design and development of antimelanogenic/skin whitening formulation. Studies performed in our laboratory, especially, in silico docking for the set of 112 phytoconstituents, helped to identify ‘hit’ phytoconstituents with antimelanogenic potential. The BE and interaction data could zero down three potential plants i.e. Sesamum indicum L., Ocimum tenuiflorum L., and Morus alba L., for antimelanogenic nanoformulation development. Interestingly, these plants have been consumed as a nutrient worldwide, and thus may be regarded as safe. The pharmacophore modeling data of the phytochemicals, folic acid, astragalin, and barbaloin, demonstrated excellent RMSD as 0.677962, 0.795954, and 0.888255 respectively. Finally, based on BE and Pa data for antimelanogenic activity, we concluded that kuwanol, sesamolin, rosmarinic acid, astragalin, folic acid, riboflavin, sesaminol, albanol, sesamin, rutin, moracin- O are potential antimelanogenic leads. Further, PASS results indicated that astragalin and rutin are principal constituents for skin whitening activity. The rationally developed nanoemulsion formulation, comprising the plant extracts containing aforesaid phyto leads could be a systematic approach from the formulation viewpoint. The monodispersed nanoformulation having globule size 50-60 nm, and requisite stability could be achievement. Further, the findings of the MTT assay, have confirmed the role of antimelanogenic nanoemulsion formulation, in comparison to marketed gel. Statistically, it has been confirmed that, the developed phytonanoemulsion formulation is more effective (p<0.05) than standard marketed gel, even at a lesser concentration. Hence, along with the development of potential antimelanogenic phytonanoemulsion formulation, the research has opened up an additional vista for discovery of potential skin whiteners from the natural domain.

CONFLICT OF INTEREST:

The authors have no relevant financial or non-financial interests to disclose.

ACKNOWLEDGEMENTS:

The authors would like to thank Dr. H. N. More, Principal, Bharati Vidyapeeth College of Pharmacy, Kolhapur, Maharashtra, India for providing facilities for the work.

REFERENCES:

1. Nautiyal A, Wairkar S. Management of hyperpigmentation: Current treatments and emerging therapies. Pigment Cell Melanoma Res. 2021; 34: 1000–1014. https://doi.org/10.1111/pcmr.12986

2. Sarkar R, Gokhale N, Godse K, Ailawadi P, Arya L, Sarma N et al. Medical management of melasma: A review with consensus recommendations by Indian pigmentary expert group. Indian J Dermatol. 2017; 62: 558. https://doi.org/10.4103/ijd.IJD_489_17

3. Chandorkar NI, Tambe SR, Amin PU, Madankar CS. Alpha arbutin as a skin lightening agent: a review. Int J Pharm Res. 2021; 13: 3502-3510. https://doi.org/10.31838/ijpr/2021.13.02.446

4. Hu S, Laughter MR, Anderson JB, Sadeghpour M. Emerging topical therapies to treat pigmentary disorders: An evidence-based approach. J Dermatolog Treat. 2022; 33: 1931-1937. https://doi.org/10.1080/09546634.2021.1940811

5. Nordin FN, Aziz A, Zakaria Z, Wan Mohamed Radzi CW. A systematic review on the skin whitening products and their ingredients for safety, health risk, and the halal status. J Cosme Dermatol. 2021; 20: 1050-1060. https://doi.org/10.1111/jocd.13691

6. Irfan M, Shafeeq A, Siddiq U, Bashir F, Ahmad T, Athar M et al. A mechanistic approach for toxicity and risk assessment of heavy metals, hydroquinone and microorganisms in cosmetic creams. J Hazard Mater. 2022; 433: 128806. https://doi.org/10.1016/j.jhazmat.2022.128806

7. Guanghui L, Yee YL, Xuanxuan L, Jing C, Ning L, Chaoying Q, Yong W. Simultaneous loading of (−)-epigallocatechin gallate and ferulic acid in chitosan-based nanoparticles as effective antioxidant and potential skin-whitening agents. International Journal of Biological Macromolecules. 2022; 219: 333-345. https://doi.org/10.1016/j.ijbiomac.2022.07.242

8. Masood SB, Akmal N, Sultan MT, Karin S. Morus alba L. nature's functional tonic. Trends in Food Science and Technology. 2008; 19: 505-512. https://doi.org/10.1016/j.tifs.2008.06.002

9. Sudip G, Dipan C, Subhankar M, Paramita B. Food application of an encapsulated phytochemically rich SC-CO2 extract of a polyherbal mix of tulsi, bay and cardamom: Shelf-life and frying stability of soybean oil. Journal of Food Engineering. 2016; 171: 194-199. https://doi.org/10.1016/j.jfoodeng.2015.10.023

10. Wei P, Zhao F, Wang Z, Wang Q, Chai X, Hou G, Meng Q. Sesame (Sesamum indicum L.): A comprehensive review of nutritional value, phytochemical composition, health benefits, development of food, and industrial applications. Nutrients. 2022; 14: 4079. https://doi.org/10.3390/nu14194079

11. Pollock S, Taylor S, Oyerinde O, Nurmohamed S, Dlova N, Sarkar R et al. The dark side of skin lightening: An international collaboration and review of a public health issue affecting dermatology. Int J Women's Dermatology. 2021; 7: 158-64. https://doi.org/10.1016/j.ijwd.2020.09.006

12. Feng J, Xiu Q, Huang Y, Troyer Z, Li B, Zheng L. Plant derived vesicle‐like nanoparticles as promising biotherapeutic tools: Present and future. Adv Mater. 2023; 35: 2207826. https://doi.org/10.1002/adma.202207826

13. Moreiras H, Seabra MC, Barral DC. Melanin transfer in the epidermis: The pursuit of skin pigmentation control mechanisms. Int J Mol Sci. 2021; 22: 4466. https://doi.org/10.3390/ijms22094466

14. Zia K, Ashraf S, Jabeen A, Saeed M, Nur-e-Alam M, Ahmed S et al. Identification of potential TNF-α inhibitors: from in silico to in vitro studies. Sci Rep. 2020; 10: 1-9. https://doi.org/10.1038/s41598-020-77750-3

15. Mali DP, Bhatia NM. Discovery of two novel hetero-tricyclic lead scaffolds as PDE5A inhibitor: virtual screening, molecular docking and pharmacophore modeling approach. Nat Prod Res. 2021; 35: 92-98. https://doi.org/10.1080/14786419.2019.1614582

16. Md. Sarfaraz Alam, Pankaj Sharma. Stability Study of Clobetasol Propionate Loaded Tea Tree Oil Nanoemulsion as Per ICH Guidelines. Research J. Pharm. and Tech. 2016; 9(11): 1999-2004. https://doi.org/10.5958/0974-360X.2016.00408.X

17. Mohamed Zerein Fathima, Shanmugarajan TS, Satheesh Kumar S, BVVenkata Nagarjuna Yadav. Comparative in Silico Docking Studies of Hinokitiol with Sorafenib and Nilotinib against Proto-Oncogene Tyrosine-Protein Kinase (ABL1) and Mitogen-activated Protein Kinase (MAPK) to Target Hepatocellular Carcinoma. Research J. Pharm. and Tech. 2017; 10(1): 257-262. https://doi.org/10.5958/0974-360X.2017.00053.1

18. Hatami S, Sirous H, Mahnam K, Najafipour A, Fassihi A. Preparing a database of corrected protein structures important in cell signaling pathways. Res Pharm Sci. 2023; 18: 67-77. https://doi.org/10.4103/1735-5362.363597

19. E. Shanmugapriya, V. Ravichandiran, M. Vijey Aanandhi. Molecular docking studies on naturally occurring selected flavones against protease enzyme of Dengue virus. Research J. Pharm. and Tech. 2016; 9(7): 929-932. https://doi.org/10.5958/0974-360X.2016.00178.5

20. De B, Bhandari K, Singla RK, Saha G, Goswami TK. In silico molecular GRIP docking of some secondary metabolites combating diabesity. Bull Natl Res Cent. 2020; 44: 1-3. https://doi.org/10.1186/s42269-020-00327-7

21. Mali DP, Gaikwad DT, Bhatia MS, Bhatia NM. Discovery of pyridoindole derivatives as potential inhibitors for phosphodiesterase 5A: In silico and in vivo studies. Nat Prod Res. 2022; 36: 2767-2776. https://doi.org/10.1080/14786419.2021.1925274

22. Mali DP, Bhatia NM. Hetero-tricyclic lead scaffold as novel PDE5A inhibitor for antihypertensive activity: In silico docking studies. Current Computer-Aided Drug Design. 2019; 15: 318-333. https://10.2174/1573409915666190214161221

23. Pascual R, Almansa C, Plata-Salamán C, Vela JM. A new pharmacophore model for the design of sigma-1 ligands validated on a large experimental dataset. Front Pharmacol. 2019; 31: 519. https://doi.org/10.3389/fphar.2019.00519

24. Uckaya F. In silico prediction and in vitro antioxidant activities of two jujube fruits from different regions. Turkish Journal of Nature and Science. 2022; 11: 12-23. https://doi.org/10.46810/tdfd.1113447

25. Debnath S, Kumar GV, Satayanarayana SV. Design, Development and Evaluation of Novel Nanoemulsion of Terbinafine HCl. Research J. Pharm. and Tech. 2012; 5(10): 1301-7.

26. Rajagukguk YV, Utcu MA, Islam M, Muzolf-Panek M, Tomaszewska-Gras J. Authenticity assessment from sesame seeds to oil and sesame products of various origin by differential scanning calorimetry. Molecules. 2022; 27: 7496. https://doi.org/10.3390/molecules27217496

27. Gaikwad D, Jadhav N. Development of stable emulsified formulations of Terminalia arjuna for topical application: evaluation of antioxidant activity of final product and molecular docking study. Drug Dev Ind Pharm. 2019; 45: 1740-1750. https://doi.org/10.1080/03639045.2019.1656732

28. Namdeo R Jadhav, Anant R Paradkar, Gourav N Shah. Adsorption Studies of Bromhexine Hydrochloride on Talc, Research J. Pharm. and Tech. 2013; 6(11): 1247-1250.

29. Garg S, Anand A, Lamba Y, Roy A. Molecular docking analysis of selected phytochemicals against SARS-CoV-2Mpro receptor. Vegetos,. 2020; 33: 766-781. https://doi.org/10.1007/s42535-020-00162-1

30. Pillaiyar T, Meenakshisundaram S, Manickam M, Sankaranarayanan M. A medicinal chemistry perspective of drug repositioning: Recent advances and challenges in drug discovery. Eur J Med Chem. 2020; 195: 112275. https://doi.org/10.1016/j.ejmech.2020.112275

31. Vasudev Pai , Muddukrishna B.S., Aravinda Pai. Computational Approach for the Design of Novel Tankyrase Inhibitors: A Rational Study based on Pharmacophore and Atom based 3D QSAR. Research J. Pharm. and Tech. 2017; 10(3): 778-784. https://doi.org/10.5958/0974-360X.2017.00146.9

32. Deore SK, Surawase RK, Maru A. Formulation and evaluation of o/w nanoemulsion of ketoconazole. Research Journal of Pharmaceutical Dosage Forms and Technology. 2019; 11: 269-274. https://doi.org/10.5958/0975-4377.2019.00045.4

33. Asha Patel, Mukesh Gohel, Tejal Soni. Partial Least Square Analysis and Mixture Design for the Study of the Influence of Composition Variables on Nanoemulsions as Drug Carriers. Research J. Pharm. and Tech. 2014; 7(12): 1446-1455.

34. Neeru Singh, Saurabh Manaswita Verma. Anti-Bacterial Screening and Optimization of Lipids for the Preparation of Nanoemulsions. Research J. Pharm. and Tech. 2015; 8(6): 713-718. https://doi.org/10.5958/0974-360X.2015.00113.4

35. Silva CC, Benati RB, Massaro TN, Pereira KC, Gaspar LR, Marcato PD. Antioxidant and anti-tyrosinase activities of quercetin-loaded olive oil nanoemulsion as potential formulation for skin hyperpigmentation. J Dispers Sci Technol. 2022; 23: 2628-2638. https://doi.org/10.1080/01932691.2022.2116715

36. Deeksha. K, Pavya, Sowmya Hari. Synthesis, Characterization and Antibacterial effect of Neem Oil Nanoemulsion. Research J. Pharm. and Tech. 2019; 12(9): 4400-4404. https://doi.org/10.5958/0974-360X.2019.00757.1

37. Sasikala M, Sundaraganapathy R, Mohan S. MTT Assay on Anticancer Properties of Phytoconstituents from Ipomoea aquatica forsskal using MCF–7 cell lines for breast cancer in Women. Research J. Pharm. and Tech. 2020; 13(3): 1356-1360. https://doi.org/10.5958/0974-360X.2020.00250.4

Received on 10.02.2025 Revised on 15.07.2025

Accepted on 25.10.2025 Published on 13.01.2026

Available online from January 17, 2026

Research J. Pharmacy and Technology. 2026;19(1):169-176.

DOI: 10.52711/0974-360X.2026.00026

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