Author(s): Silviana Hasanuddin, Dolih Gozali, Muhammad Arba, Dwi Syah Fitra Ramadhan, Resmi Mustarichie

Email(s): silviana.hasanuddin@gmail.com

DOI: 10.52711/0974-360X.2022.00202   

Address: Silviana Hasanuddin1,4*, Dolih Gozali2, Muhammad Arba3, Dwi Syah Fitra Ramadhan4, Resmi Mustarichie1
1Pharmaceutical Analysis and Medicinal Chemistry Department, Faculty of Pharmacy, Universitas Padjadjaran, Sumedang, Indonesia.
2Pharmaceutical Department, Faculty of Pharmacy, Universitas Padjadjaran, Sumedang, Indonesia.
3Faculty of Pharmacy, Universitas Halu Oleo, Kendari, Indonesia.
4Department of Pharmacy, Universitas Mandala Waluya, Kendari, Indonesia.
*Corresponding Author

Published In:   Volume - 15,      Issue - 3,     Year - 2022


ABSTRACT:
Introduction: Alopecia is a hair loss that occur continuously and may occur in men, women and children. The causes of alopecia, including the use of cosmetics, medication, stress, postpartum period, hormonal disorders, and scalp infection. The purpose of this research is to determine the compounds contained in Petroselinum crispum that have the potential as antialopecia agents by predicting ligand-receptor binding and binding modes, predicting ADME by using Lipinski's rule, and also comparing the effectiveness with native ligand and minoxidil. Methodology: The process starts with protein and ligand structure preparation, then docking using Autodock Vina. Afterward, analyzed and visualized of the ligands docking, and predicted the ADME according to lipinski's rules using SwissADME and toxicity using PASS predistion. Result: There were 24 compounds found in Petroselinum crispum. Molecular docking simulation showed that six compounds had better binding affinities than minoxidil. Based on the results of prediction of ADMET values using the Lipinski rule and PASS Prediction, compound that are thought to have good activity is (+)–Marmesin compared to minoxidil. Conclusion: (+)–Marmesin to have better interactions with the androgen receptor, but not better than native ligands. thus, (+)–Marmesin can be used as antialopecia agents alternative terapy.


Cite this article:
Silviana Hasanuddin, Dolih Gozali, Muhammad Arba, Dwi Syah Fitra Ramadhan, Resmi Mustarichie. In Silico Prediction of Metabolite in Petroselinum Crispum in Inhibiting Androgen Receptor as Treatment for Alopecia. Research Journal of Pharmacy and Technology. 2022; 15(3):1211-8. doi: 10.52711/0974-360X.2022.00202

Cite(Electronic):
Silviana Hasanuddin, Dolih Gozali, Muhammad Arba, Dwi Syah Fitra Ramadhan, Resmi Mustarichie. In Silico Prediction of Metabolite in Petroselinum Crispum in Inhibiting Androgen Receptor as Treatment for Alopecia. Research Journal of Pharmacy and Technology. 2022; 15(3):1211-8. doi: 10.52711/0974-360X.2022.00202   Available on: https://www.rjptonline.org/AbstractView.aspx?PID=2022-15-3-45


REFERENCES:
1.    Javeth A. Mathur R G. Babu M. A Correlational Survey to Assess the Level of Stress, Coping Strategies, and Quality of Life of Female Cancer Patients Related to Chemotherapy Induced Alopecia in Amala Cancer Hospital, Thrissur, Kerala. Asian J. Nurs. Educ. Res. 2017; 7 (1): 1. doi.org/10.5958/2349-2996.2017.00001.5.
2.    Amurdhavani B S. Alopecia in Adolescents-A Survey. Res. J. Pharm. Technol. 2015; 8 (7): 915–918. doi.org/10.5958/0974-360X.2015.00150.X.
3.    Nnoruka N E. Hair Loss: Is There a Relationship with Hair Care Practices in Nigeria. Int. J. Dermatol. 2005; 44 (SUPPL. 1): 13–17. doi.org/10.1111/j.1365-4632.2005.02801.x.
4.    Horev L. Environmental and Cosmetic Factors in Hair Loss and Destruction. Curr. Probl. Dermatol. 2007; 35: 103–117. doi.org/10.1159/0000106418.
5.    Light A E. Patterned Loss of Hair in Man; Pathogenesis and Prognosis. Ann. N. Y. Acad. Sci. 1951; 53 (3): 729–734. doi.org/10.1111/j.1749-6632.1951.tb31972.x.
6.    Park S Y. Kim K B. Ahn S H. Kim H H. The Effects of Sm-215 on Androgeneticalopecia. Res. J. Pharm. Technol. 2018; 11 (5): 1745–1751. doi.org/10.5958/0974-360X.2018.00324.4.
7.    Nikita S. Rashmi P S. Yogendra P. Pranay W. Ankita W. Rai A K. Poly Herbal Hair Oil Preparation, Standardization, Treatment and Evaluation for Alopecia in Male Wistar Rats. Res. J. Pharm. Technol. 2019; 12 (2): 757–763. doi.org/10.5958/0974-360X.2019.00134.3.
8.    Olsen E A. Bergfeld W F. Cotsarelis G. Price V H. Shapiro J. Sinclair R. Solomon A. Sperling L. Stenn K. Whiting D A. Bernardo O. Bettencourt M. Bolduc C. Callendar V. Elston D. Hickman J. Ioffreda M. King, L. Linzon C. McMichael A. Miller J. Mulinari F. Trancik R. Summary of North American Hair Research Society (NAHRS) - Sponsored Workshop on Cicatricial Alopecia, Duke University Medical Center, February 10 and 11, 2001. J. Am. Acad. Dermatol. 2003; 48 (1): 103–110. doi.org/10.1067/mjd.2003.68.
9.    Mustarichie R. Wicaksono I A. Hayati C. Anti-Alopecia Characteristics of Ethanol Extract, n-Hexane, Ethyl Acetate and Water Fractions of Malvaviscus Arboreus Cav. Res. J. Pharm. Technol. 2018; 11 (11): 5066–5072. doi.org/10.5958/0974-360X.2018.00924.1.
10.    Kumar N. Singh S. Gupta R. Hair Growth Activity of Trichosanthes Dioica R. Leaves. Res. J. Pharmacogn. Phytochem. 2011; 3 (1): 30–33.
11.    Gozali D. Mustarichie R. Hair Tonic Formulation of Anti-Alopecia of Angiopteris Evecta Extract. Res. J. Pharm. Technol. 2019; 12 (3): 1079–1085. doi.org/10.5958/0974-360X.2019.00177.X.
12.    Yousofi A. Daneshmandi S. Soleimani N. Bagheri K. Karimi M H. Immunomodulatory Effect of Parsley (Petroselinum Crispum) Essential Oil on Immune Cells: Mitogen-Activated Splenocytes and Peritoneal Macrophages. Immunopharmacol. Immunotoxicol. 2012; 34 (2): 303–308. doi.org/10.3109/08923973.2011.603338.
13.    Pino J. A. Rosado A. Rosado A. Herb Oil of Parsley Petroselinum Crispum Mill.) from Cuba. J. Essent. Oil Res. 1997; 9(2): 241-242. doi.org/10.1080/10412905.1997.9699471.
14.    Intirach J. Junkum A. Lumjuan N. Chaithong U. Jitpakdi A. Riyong D. Wannasan A. Champakaew D. Muangmoon R. Chansang A. Pitasawat B. Antimosquito Property of Petroselinum Crispum (Umbellifereae) against the Pyrethroid Resistant and Susceptible Strains of Aedes Aegypti (Diptera: Culicidae). Environ. Sci. Pollut. Res. 2016; 23(23): 23994024008. doi.org/10.1007/s11356-016-7651-8.
15.    Kortagere, S.; Ekins, S. Troubleshooting Computational Methods in Drug Discovery. J. Pharmacol. Toxicol. Methods 2010, 61 (2), 67–75. https://doi.org/10.1016/j.vascn.2010.02.005.
16.    Du, X.; Li, Y.; Xia, Y. L.; Ai, S. M.; Liang, J.; Sang, P.; Ji, X. L.; Liu, S. Q. Insights into Protein–Ligand Interactions: Mechanisms, Models, and Methods. Int. J. Mol. Sci. 2016; 17 (2): 1–34. doi.org/10.3390/ijms17020144.
17.    Daina A. Michielin O. Zoete V. SwissADME: A Free Web Tool to Evaluate Pharmacokinetics, Drug-Likeness and Medicinal Chemistry Friendliness of Small Molecules. Sci. Rep. 2017; 7 (January): 1–13. doi.org/10.1038/srep42717.
18.    Thomas R. Hari R. Joy J. Krishnan S. Swathy A. N. Nair S S. Manakadan A A. Sathianarayanan. Saranya T S. In Silico Docking Approach of Coumarin Derivatives as an Aromatase Antagonist. Res. J. Pharm. Technol. 2015; 8 (12): 1673–1678. doi.org/10.5958/0974-360X.2015.00302.9.
19.    Hemalatha K. Selvin J. Girija K. Synthesis, In Silico Molecular Docking Study and Anti-Bacterial Evaluation of Some Novel 4-Anilino Quinazolines. Asian J. Pharm. Res. 2018; 8 (3): 125. doi.org/10.5958/2231-5691.2018.00022.9.
20.    Bajorath J. Computational Analysis of Ligand Relationships within Target Families. Curr. Opin. Chem. Biol. 2008; 12 (3): 352–358. doi.org/10.1016/j.cbpa.2008.01.044.
21.    Dimitrov S. Dimitrova G. Pavlov T. Dimitrova N. Patlewicz G. Niemela J. Mekenyan O. A Stepwise Approach for Defining the Applicability Domain of SAR and QSAR Models. J. Chem. Inf. Model. 2005; 45 (4): 839–849. doi.org/10.1021/ci0500381.
22.    Melville J. Burke E. Hirst J. Machine Learning in Virtual Screening. Comb. Chem. High Throughput Screen. 2009; 12 (4): 332–343. doi.org/10.2174/138620709788167980.
23.    O’Boyle N. M. Banck M. James C A. Morley C. Vandermeersch T. Hutchison G R. Open Babel. J. Cheminform. 2011; 3 (33): 1–14. doi.org/10.1186/1758-2946-3-33.
24.    Sousa S F. Ribeiro A. J. M. Coimbra J. T. S. Neves R. P. P. Martins S. A. Moorthy N. S. H. N. Fernandes P. A. Ramos M. J. Protein-Ligand Docking in the New Millennium – A Retrospective of 10 Years in the Field. Curr. Med. Chem. 2013; 20(18):2296-2314. doi.org/10.2174/0929867311320180002.
25.    Manly C. J. Chandrasekhar J. Ochterski J. W. Hammer J. D. Warfield B. B. Strategies and Tactics for Optimizing the Hit-to-Lead Process and beyond-A Computational Chemistry Perspective. Drug Discov. Today 2008; 13 (3–4): 99–109. doi.org/10.1016/j.drudis.2007.10.019.
26.    Sousa S. F. Cerqueira N.M.F.S.A.. Fernandes P.A. Ramos J. M. Virtual Screening in Drug Design and Development. Comb. Chem. High Throughput Screen. 2010; 13 (5): 442–453. doi.org/10.2174/138620710791293001.
27.    Zubair M. S. Anam S. Khumaidi A. Susanto Y. Hidayat M. Ridhay A. Molecular Docking Approach to Identify Potential Anticancer Compounds from Begonia (Begonia Sp). AIP Conf. Proc. 2016; 1755(1):1755. doi.org/10.1063/1.4958513.
28.    Buvana C. Sumathy A. Sukumar M. In Silico Identification of Potential Xanthine Oxidase Inhibitors for the Treatment of Gout and Cardiovascular Disease. Asian J. Res. Chem. 2013; 6 (11): 1049–1053.
29.    Arba M. Ruslin Ihsan S. Setyanto T W. Tjahjono D. H. Molecular Modeling of Cationic Porphyrin-Anthraquinone Hybrids as DNA Topoisomerase IIβ Inhibitors. Comput. Biol. Chem. 2017; 71: 129–135. doi.org/10.1016/j.compbiolchem.2017.10.002.
30.    Lipinski C. A. Lombardo F. Dominy B. W. Feeney P J. Experimental and Computational Approaches to Estimate Solubility and Permeability in Drug Discovery and Development Settings. Advanced Drug Delivery Reviews. 2012; 23(1-3):3-25. doi.org/10.1016/j.addr.2012.09.019.
31.    Megantara S. Utami D. Puspitasari L. Mustarichie R. Insilico Study of Thymoquinone as Peroxisome Proliferator Activated Receptor Gamma Agonist in the Treatment of Type 2 Diabetes Mellitus. J. Pharm. Sci. Res. 2017; 9 (9): 1478–1482.

Recomonded Articles:

Research Journal of Pharmacy and Technology (RJPT) is an international, peer-reviewed, multidisciplinary journal.... Read more >>>

RNI: CHHENG00387/33/1/2008-TC                     
DOI: 10.5958/0974-360X 

0.38
2018CiteScore
 
56th percentile
Powered by  Scopus


SCImago Journal & Country Rank


Recent Articles




Tags


Not Available