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Year 2025, Volume: 29 Issue: 4, 1468 - 1484, 05.07.2025
https://doi.org/10.12991/jrespharm.1734539

Abstract

References

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  • [2] Chávez-Reyes J, Escárcega-González CE, Chavira-Suárez E, León-Buitimea A, Vázquez-León P, Morones-Ramírez JR, Villalón CM, Quintanar-Stephano A, Marichal-Cancino BA. Susceptibility for some infectious diseases in patients with diabetes: The key role of glycemia. Front Public Health. 2021; 9: 559595. https://doi.org/10.3389/fpubh.2021.559595
  • [3] Leggio M, Lombardi M, Caldarone E, Severi P, D'emidio S, Armeni M, Bravi V, Bendini MG, Mazza A. The relationship between obesity and hypertension: an updated comprehensive overview on vicious twins. Hypertens Res. 2017; 40: 947-963. https://doi.org/10.1038/hr.2017.75
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  • [5] Kunjiappan S, Panneerselvam T, Prasad P, Sukumaran S, Somasundaram B, Sankaranarayanan M, Murugan I, Parasuraman P. Design, graph theoretical analysis and in silico modeling of Dunaliella bardawil biomass encapsulated keratin nanoparticles: A scaffold for effective glucose utilization. Biomed Mat. 2018; 13: 045012. http://dx.doi.org/10.1088/1748-605X/aabcea.
  • [6] Kim J, Kwon HS. Not control but conquest: strategies for the remission of type 2 diabetes mellitus. Diabet Metabolism J. 2022; 46: 165-180. https://doi.org/10.4093/dmj.2021.0377
  • [7] Martín-Timón I, Sevillano-Collantes C, Segura-Galindo A, del Cañizo-Gómez FJ. Type 2 diabetes and cardiovascular disease: have all risk factors the same strength? World J Diabet. 2014; 5: 444. https://doi.org/10.4239%2Fwjd.v5.i4.444
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  • [9] Artasensi A, Pedretti A, Vistoli G, Fumagalli L. Type 2 diabetes mellitus: A review of multi-target drugs. Molecules. 2020; 25: 1987. https://doi.org/10.3390/molecules25081987
  • [10] Al-Mrabeh A. β-Cell dysfunction, hepatic lipid metabolism, and cardiovascular health in type 2 diabetes: new directions of research and novel therapeutic strategies. Biomedicines. 2021;9(2):226. https://doi.org/10.3390/biomedicines9020226
  • [11] Dinda B, Saha S. Obesity and Diabetes. In Natural Products in Obesity and Diabetes: Therapeutic Potential and Role in Prevention and Treatment; Springer: 2022; pp. 1-61.
  • [12] Kunjiappan S, Theivendren P, Pavadai P, Govindaraj S, Sankaranarayanan M, Somasundaram B, Arunachalam S, Ram Kumar Pandian S, Ammunje DN. Design and in silico modeling of indoloquinoxaline incorporated keratin nanoparticles for modulation of glucose metabolism in 3T3‐L1 adipocytes. Biotechnol Prog. 2020; 36: e2904. https://doi.org/10.1002/btpr.2904
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  • [14] Shao X, Wang M, Wei X, Deng S, Fu N, Peng Q, Jiang Y, Ye L, Xie J, Lin Y. Peroxisome proliferator-activated receptor-γ: master regulator of adipogenesis and obesity. Curr Stem Cell Res Ther. 2016; 11: 282-289. https://doi.org/10.2174/1574888x10666150528144905
  • [15] Muhammad G, Hussain MA, Jantan I, Bukhari SNA. Mimosa pudica L., a high‐value medicinal plant as a source of bioactives for pharmaceuticals. Compr Rev Food Sci Food Saf. 2016; 15: 303-315. https://doi.org/10.1111/1541 4337.12184
  • [16] Palanichamy C, Nayak Ammunje D, Pavadai P, Ram Kumar Pandian S, Theivendren P, Kabilan SJ, Babkiewicz E, Maszczyk P, Kunjiappan S. Mimosa pudica Linn. extract improves aphrodisiac performance in diabetes-induced male Wister rats. J Biomol Struct Dyn. 2025;43(4):1621-1640. https://doi.org/10.1080/07391102.2023.2292302
  • [17] Chaudhury A, Duvoor C, Reddy Dendi VS, Kraleti S, Chada A, Ravilla R, Marco A, Shekhawat NS, Montales MT, Kuriakose K. Clinical review of antidiabetic drugs: Implications for type 2 diabetes mellitus management. Front Endocrinol. 2017; 8: 6. https://doi.org/10.3389%2Ffendo.2017.00006
  • [18] Ansari P, Akther S, Hannan J, Seidel V, Nujat NJ, Abdel-Wahab YH. Pharmacologically active phytomolecules isolated from traditional antidiabetic plants and their therapeutic role for the management of diabetes mellitus. Molecules. 2022; 27: 4278. https://doi.org/10.3390%2Fmolecules27134278
  • [19] Shehadeh MB, Suaifan GA, Abu-Odeh AM. Plants secondary metabolites as blood glucose-lowering molecules. Molecules. 2021; 26: 4333. https://doi.org/10.3390/molecules26144333
  • [20] Kalimuthu AK, Panneerselvam T, Pavadai P, Pandian SRK, Sundar K, Murugesan S, Ammunje DN, Kumar S, Arunachalam S, Kunjiappan S. Pharmacoinformatics-based investigation of bioactive compounds of Rasam (South Indian recipe) against human cancer. Sci Rep. 2021; 11: 21488. https://doi.org/10.1038/s41598-021-01008-9
  • [21] Palanichamy C, Pavadai P, Panneerselvam T, Arunachalam S, Babkiewicz E, Ram Kumar Pandian S, Shanmugampillai Jeyarajaguru K, Nayak Ammunje D, Kannan S, Chandrasekaran J. Aphrodisiac performance of bioactive compounds from Mimosa pudica Linn.: In silico molecular docking and dynamics simulation approach. Molecules. 2022; 27: 3799. https://doi.org/10.3390/molecules27123799
  • [22] Houseknecht KL, Cole BM, Steele PJ. Peroxisome proliferator-activated receptor gamma (PPARγ) and its ligands: a review. Domest Anim Endocrinol. 2002; 22: 1-23. https://doi.org/10.1016/S0739-7240(01)00117-5
  • [23] Anwar N, Teo YK, Tan JBL. The role of plant metabolites in drug discovery: Current challenges and future perspectives. In: Natural Bio-active Compounds: Volume 2: Chemistry, Pharmacology and Health Care Practices. Springer, Singapore, 2019, pp.25-51. https://doi.org/10.1007/978-981-13-7205-6_2.
  • [24] Benet LZ, Kroetz D, Sheiner L, Hardman J, Limbird L. Pharmacokinetics: the dynamics of drug absorption, distribution, metabolism, and elimination. In: Goodman and Gilman’s the Pharmacological Basis of Therapeutics, 9th Edition. Mcgraw-Hill, New York, 1996, 3, e27.
  • [25] Dehelean CA, Marcovici I, Soica C, Mioc M, Coricovac D, Iurciuc S, Cretu OM, Pinzaru I. Plant-derived anticancer compounds as new perspectives in drug discovery and alternative therapy. Molecules. 2021; 26: 1109. https://doi.org/10.3390/molecules26041109
  • [26] Daniel DJP, Shanmugasundaram S, Chandra Mohan KS, Siva Bharathi V, Abraham JK, Anbazhagan P, Pavadai P, Ram Kumar Pandian S, Sundar K, Kunjiappan S. Elucidating the role of phytocompounds from Brassica oleracea var. italic (Broccoli) on hyperthyroidism: an in-silico approach. In Silico Pharmacol. 2024; 12: 6. https://doi.org/10.1007/s40203-023-00180-2
  • [27] Chandrasekaran J, Elumalai S, Murugesan V, Kunjiappan S, Pavadai P, Theivendren P. Computational design of PD-L1 small molecule inhibitors for cancer therapy. Mol Divers. 2023; 27: 1633-1644. https://doi.org/10.1007/s11030-022-10516-3
  • [28] 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: 42717. https://doi.org/10.1038/srep42717
  • [29] Pampalakis G. Underestimations in the In Silico-Predicted Toxicities of V-Agents. J Xenobiotics. 2023; 13: 615-624. https://doi.org/10.3390%2Fjox13040039
  • [30] Prieto-Martínez FD, Galván-Ciprés, Y. Colín-Lozano, B. Molecular simulation in drug design: An overview of molecular dynamics methods. In: Applied Computer-Aided Drug Design: Models and Methods, 2023, p.202. https://doi.org/10.2174/9789815179934123010009
  • [31] Gopinath P, Kathiravan, M. Docking studies and molecular dynamics simulation of triazole benzene sulfonamide derivatives with human carbonic anhydrase IX inhibition activity. RSC Adv. 2021; 11: 38079-38093. https://doi.org/10.1039/D1RA07377
  • [32] Espinosa JR, Wand CR, Vega, C. Sanz, E. Frenkel, D. Calculation of the water-octanol partition coefficient of cholesterol for SPC, TIP3P, and TIP4P water. J Chem Phy. 2018; 149. https://doi.org/10.1063/1.5054056
  • [33] Lippert RA, Predescu C, Ierardi DJ, Mackenzie KM, Eastwood MP, Dror RO, Shaw DE. Accurate and efficient integration for molecular dynamics simulations at constant temperature and pressure. J Chem Phy. 2013; 139. https://doi.org/10.1063/1.4825247
  • [35] Janek J, Kolafa J. Novel barostat implementation for molecular dynamics. J Chem Phy. 2024; 160. https://doi.org/10.1063/5.0193281
  • [36] Piston K. Atomistic Investigation of Nucleosomal H3 Histone Tail in Unmodified and Epigenetically Modified States. Syracuse University, 2022.

Identification of potential antidiabetic inhibitor from Mimosa pudica Linn. through in silico molecular modeling and DFT tools

Year 2025, Volume: 29 Issue: 4, 1468 - 1484, 05.07.2025
https://doi.org/10.12991/jrespharm.1734539

Abstract

Presently prescribed synthetic antidiabetic drugs effectively manage type 2 diabetes mellitus (T2DM) and, at the same time, cause severe toxic side effects. Generating novel molecules is significantly hampered by their longer time and insufficient physicochemical, pharmacokinetic, and intrinsic properties. In this view, a potential antidiabetic inhibitor from Mimosa pudica L. can be identified via in silico molecular modeling and Density Functional Theory (DFT) tools for effi-ciently managing T2DM with minimal side effects. Primarily, we evaluated the network analysis to observe the genes, proteins, and enzymes contributing to the signaling network of Peroxisome proliferator-activated receptors (PPARs) family proteins and identified PPARγ as a potential antidiabetic receptor protein. Thirty-six bioactive molecules were picked from M. pudica L. ethanolic extract through LC-MS and GC-MS analysis of our previous study report. Based on the pilot study, the selected molecule’s structure was drawn using Chemsketch software and docked against the PPARγ receptor. Interestingly, three high-scoring molecules were observed, namely, apigetrin (-8.6 kcal/mol), orientin ( 8.5 kcal/mol), isoquercetin (-8.3 kcal/mol), whereas compared to standard reference drug pioglitazone (-8.3 kcal/mol). In addition, molecular dynamics (MD) simulation research to discover intermolecular interactions and the stability of protein-ligand complexes. The in silico ADME&T studies displayed that apigetrin showed drug-like behaviours and less toxic effects. Further, MD simulation studies established the stability of apigetrin and orientin with the PPARγ protein binding pockets. According to these discoveries, the top-scored molecule, apigetrin, might be used as a potential antidiabetic inhibitor and can be used as a new optional medicine for the therapy of T2DM.

References

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  • [3] Leggio M, Lombardi M, Caldarone E, Severi P, D'emidio S, Armeni M, Bravi V, Bendini MG, Mazza A. The relationship between obesity and hypertension: an updated comprehensive overview on vicious twins. Hypertens Res. 2017; 40: 947-963. https://doi.org/10.1038/hr.2017.75
  • [4] Pradeepa R, Mohan V. Epidemiology of type 2 diabetes in India. Ind J Ophthalmol. 2021; 69: 2932-2938. https://doi.org/10.4103/ijo.ijo_1627_21
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  • [19] Shehadeh MB, Suaifan GA, Abu-Odeh AM. Plants secondary metabolites as blood glucose-lowering molecules. Molecules. 2021; 26: 4333. https://doi.org/10.3390/molecules26144333
  • [20] Kalimuthu AK, Panneerselvam T, Pavadai P, Pandian SRK, Sundar K, Murugesan S, Ammunje DN, Kumar S, Arunachalam S, Kunjiappan S. Pharmacoinformatics-based investigation of bioactive compounds of Rasam (South Indian recipe) against human cancer. Sci Rep. 2021; 11: 21488. https://doi.org/10.1038/s41598-021-01008-9
  • [21] Palanichamy C, Pavadai P, Panneerselvam T, Arunachalam S, Babkiewicz E, Ram Kumar Pandian S, Shanmugampillai Jeyarajaguru K, Nayak Ammunje D, Kannan S, Chandrasekaran J. Aphrodisiac performance of bioactive compounds from Mimosa pudica Linn.: In silico molecular docking and dynamics simulation approach. Molecules. 2022; 27: 3799. https://doi.org/10.3390/molecules27123799
  • [22] Houseknecht KL, Cole BM, Steele PJ. Peroxisome proliferator-activated receptor gamma (PPARγ) and its ligands: a review. Domest Anim Endocrinol. 2002; 22: 1-23. https://doi.org/10.1016/S0739-7240(01)00117-5
  • [23] Anwar N, Teo YK, Tan JBL. The role of plant metabolites in drug discovery: Current challenges and future perspectives. In: Natural Bio-active Compounds: Volume 2: Chemistry, Pharmacology and Health Care Practices. Springer, Singapore, 2019, pp.25-51. https://doi.org/10.1007/978-981-13-7205-6_2.
  • [24] Benet LZ, Kroetz D, Sheiner L, Hardman J, Limbird L. Pharmacokinetics: the dynamics of drug absorption, distribution, metabolism, and elimination. In: Goodman and Gilman’s the Pharmacological Basis of Therapeutics, 9th Edition. Mcgraw-Hill, New York, 1996, 3, e27.
  • [25] Dehelean CA, Marcovici I, Soica C, Mioc M, Coricovac D, Iurciuc S, Cretu OM, Pinzaru I. Plant-derived anticancer compounds as new perspectives in drug discovery and alternative therapy. Molecules. 2021; 26: 1109. https://doi.org/10.3390/molecules26041109
  • [26] Daniel DJP, Shanmugasundaram S, Chandra Mohan KS, Siva Bharathi V, Abraham JK, Anbazhagan P, Pavadai P, Ram Kumar Pandian S, Sundar K, Kunjiappan S. Elucidating the role of phytocompounds from Brassica oleracea var. italic (Broccoli) on hyperthyroidism: an in-silico approach. In Silico Pharmacol. 2024; 12: 6. https://doi.org/10.1007/s40203-023-00180-2
  • [27] Chandrasekaran J, Elumalai S, Murugesan V, Kunjiappan S, Pavadai P, Theivendren P. Computational design of PD-L1 small molecule inhibitors for cancer therapy. Mol Divers. 2023; 27: 1633-1644. https://doi.org/10.1007/s11030-022-10516-3
  • [28] 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: 42717. https://doi.org/10.1038/srep42717
  • [29] Pampalakis G. Underestimations in the In Silico-Predicted Toxicities of V-Agents. J Xenobiotics. 2023; 13: 615-624. https://doi.org/10.3390%2Fjox13040039
  • [30] Prieto-Martínez FD, Galván-Ciprés, Y. Colín-Lozano, B. Molecular simulation in drug design: An overview of molecular dynamics methods. In: Applied Computer-Aided Drug Design: Models and Methods, 2023, p.202. https://doi.org/10.2174/9789815179934123010009
  • [31] Gopinath P, Kathiravan, M. Docking studies and molecular dynamics simulation of triazole benzene sulfonamide derivatives with human carbonic anhydrase IX inhibition activity. RSC Adv. 2021; 11: 38079-38093. https://doi.org/10.1039/D1RA07377
  • [32] Espinosa JR, Wand CR, Vega, C. Sanz, E. Frenkel, D. Calculation of the water-octanol partition coefficient of cholesterol for SPC, TIP3P, and TIP4P water. J Chem Phy. 2018; 149. https://doi.org/10.1063/1.5054056
  • [33] Lippert RA, Predescu C, Ierardi DJ, Mackenzie KM, Eastwood MP, Dror RO, Shaw DE. Accurate and efficient integration for molecular dynamics simulations at constant temperature and pressure. J Chem Phy. 2013; 139. https://doi.org/10.1063/1.4825247
  • [35] Janek J, Kolafa J. Novel barostat implementation for molecular dynamics. J Chem Phy. 2024; 160. https://doi.org/10.1063/5.0193281
  • [36] Piston K. Atomistic Investigation of Nucleosomal H3 Histone Tail in Unmodified and Epigenetically Modified States. Syracuse University, 2022.
There are 35 citations in total.

Details

Primary Language English
Subjects Pharmaceutical Biotechnology
Journal Section Articles
Authors

Chandrasekar Palanichamy This is me

Parasuraman Pavadai

Panneerselvam Theivendren This is me

Madasamy Sundar This is me

Alagarsamy Santhana Krishna Kumar This is me

Selvaraj Kunjiappan This is me

Publication Date July 5, 2025
Submission Date July 12, 2024
Acceptance Date August 22, 2024
Published in Issue Year 2025 Volume: 29 Issue: 4

Cite

APA Palanichamy, C., Pavadai, P., Theivendren, P., … Sundar, M. (2025). Identification of potential antidiabetic inhibitor from Mimosa pudica Linn. through in silico molecular modeling and DFT tools. Journal of Research in Pharmacy, 29(4), 1468-1484. https://doi.org/10.12991/jrespharm.1734539
AMA Palanichamy C, Pavadai P, Theivendren P, Sundar M, Santhana Krishna Kumar A, Kunjiappan S. Identification of potential antidiabetic inhibitor from Mimosa pudica Linn. through in silico molecular modeling and DFT tools. J. Res. Pharm. July 2025;29(4):1468-1484. doi:10.12991/jrespharm.1734539
Chicago Palanichamy, Chandrasekar, Parasuraman Pavadai, Panneerselvam Theivendren, Madasamy Sundar, Alagarsamy Santhana Krishna Kumar, and Selvaraj Kunjiappan. “Identification of Potential Antidiabetic Inhibitor from Mimosa Pudica Linn. Through in Silico Molecular Modeling and DFT Tools”. Journal of Research in Pharmacy 29, no. 4 (July 2025): 1468-84. https://doi.org/10.12991/jrespharm.1734539.
EndNote Palanichamy C, Pavadai P, Theivendren P, Sundar M, Santhana Krishna Kumar A, Kunjiappan S (July 1, 2025) Identification of potential antidiabetic inhibitor from Mimosa pudica Linn. through in silico molecular modeling and DFT tools. Journal of Research in Pharmacy 29 4 1468–1484.
IEEE C. Palanichamy, P. Pavadai, P. Theivendren, M. Sundar, A. Santhana Krishna Kumar, and S. Kunjiappan, “Identification of potential antidiabetic inhibitor from Mimosa pudica Linn. through in silico molecular modeling and DFT tools”, J. Res. Pharm., vol. 29, no. 4, pp. 1468–1484, 2025, doi: 10.12991/jrespharm.1734539.
ISNAD Palanichamy, Chandrasekar et al. “Identification of Potential Antidiabetic Inhibitor from Mimosa Pudica Linn. Through in Silico Molecular Modeling and DFT Tools”. Journal of Research in Pharmacy 29/4 (July2025), 1468-1484. https://doi.org/10.12991/jrespharm.1734539.
JAMA Palanichamy C, Pavadai P, Theivendren P, Sundar M, Santhana Krishna Kumar A, Kunjiappan S. Identification of potential antidiabetic inhibitor from Mimosa pudica Linn. through in silico molecular modeling and DFT tools. J. Res. Pharm. 2025;29:1468–1484.
MLA Palanichamy, Chandrasekar et al. “Identification of Potential Antidiabetic Inhibitor from Mimosa Pudica Linn. Through in Silico Molecular Modeling and DFT Tools”. Journal of Research in Pharmacy, vol. 29, no. 4, 2025, pp. 1468-84, doi:10.12991/jrespharm.1734539.
Vancouver Palanichamy C, Pavadai P, Theivendren P, Sundar M, Santhana Krishna Kumar A, Kunjiappan S. Identification of potential antidiabetic inhibitor from Mimosa pudica Linn. through in silico molecular modeling and DFT tools. J. Res. Pharm. 2025;29(4):1468-84.