Evaluation of Gymnema sylvestre R. Br. against Letrozole Induced Polycystic Ovarian Syndrome in rats

Pachiappan, Sudhakar; Ramalingam, Kothai; Balasubramanian, A.

doi:10.52711/0974-360x.2023.00066

Cited by 7 publications

(1 citation statement)

References 24 publications

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“…This machine learning method predicts the pharmacokinetics parameter based on the structural similarity of the chemical associated with known ADMET features. Moreover, this is the most trusted and well-known machine learning-based tool for forecasting ADMET ( 38 ). The essential data include water solubility Log S, human intestinal absorption, Caco-2 permeability, VDss (human), blood–brain barrier (BBB) permeability, CYP450 1A2 inhibitor, CYP450 2C9 substrate, total clearance (ml/min/kg), and renal OCT2 substrate.…”

Section: Methodsmentioning

confidence: 99%

Revolutionizing anti-cancer drug discovery against breast cancer and lung cancer by modification of natural genistein: an advanced computational and drug design approach

Akash,

Bibi,

Biswas

et al. 2023

Front. Oncol.

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Breast and lung cancer are two of the most lethal forms of cancer, responsible for a disproportionately high number of deaths worldwide. Both doctors and cancer patients express alarm about the rising incidence of the disease globally. Although targeted treatment has achieved enormous advancements, it is not without its drawbacks. Numerous medicines and chemotherapeutic drugs have been authorized by the FDA; nevertheless, they can be quite costly and often fall short of completely curing the condition. Therefore, this investigation has been conducted to identify a potential medication against breast and lung cancer through structural modification of genistein. Genistein is the active compound in Glycyrrhiza glabra (licorice), and it exhibits solid anticancer efficiency against various cancers, including breast cancer, lung cancer, and brain cancer. Hence, the design of its analogs with the interchange of five functional groups—COOH, NH2 and OCH3, Benzene, and NH-CH2-CH2-OH—have been employed to enhance affinities compared to primary genistein. Additionally, advanced computational studies such as PASS prediction, molecular docking, ADMET, and molecular dynamics simulation were conducted. Firstly, the PASS prediction spectrum was analyzed, revealing that the designed genistein analogs exhibit improved antineoplastic activity. In the prediction data, breast and lung cancer were selected as primary targets. Subsequently, other computational investigations were gradually conducted. The mentioned compounds have shown acceptable results for in silico ADME, AMES toxicity, and hepatotoxicity estimations, which are fundamental for their oral medication. It is noteworthy that the initial binding affinity was only −8.7 kcal/mol against the breast cancer targeted protein (PDB ID: 3HB5). However, after the modification of the functional group, when calculating the binding affinities, it becomes apparent that the binding affinities increase gradually, reaching a maximum of −11.0 and −10.0 kcal/mol. Similarly, the initial binding affinity was only −8.0 kcal/mol against lung cancer (PDB ID: 2P85), but after the addition of binding affinity, it reached −9.5 kcal/mol. Finally, a molecular dynamics simulation was conducted to study the molecular models over 100 ns and examine the stability of the docked complexes. The results indicate that the selected complexes remain highly stable throughout the 100-ns molecular dynamics simulation runs, displaying strong correlations with the binding of targeted ligands within the active site of the selected protein. It is important to further investigate and proceed to clinical or wet lab experiments to determine the practical value of the proposed compounds.

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Section: Methodsmentioning

confidence: 99%

Revolutionizing anti-cancer drug discovery against breast cancer and lung cancer by modification of natural genistein: an advanced computational and drug design approach

Akash,

Bibi,

Biswas

et al. 2023

Front. Oncol.

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Effect of Triclisia subcordata Oliv. (Menispermaceae) leaves on hormonal imbalance and genes expression in the ovaries of letrozole-induced polycystic rats via in vivo and computational approaches

Ogunlakin,

Ojo,

Gyebi

et al. 2024

Journal of Molecular Structure

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Gymnema sylvestre as a potential therapeutic agent for PCOS: insights from mRNA differential gene expression and molecular docking analysis

Vora,

Kapadia,

Dinesh

et al. 2023

Futur J Pharm Sci

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Background In spite of the increased prevalence of Polycystic Ovary Syndrome in bilateral ovaries (PCOS) in females globally (~ 20%), the rate of decisive treatment is limited due to late and invasive diagnostics and the unavailability of stand-alone drugs against phenotypic symptoms associated with PCOS. This study aims at unravelling molecular mechanisms allied with this disorder and identifying genes and pathways that are altered causing PCOS as a pre-requisite need. Furthermore, this study intends at assessing the therapeutic potentials of Gymnemasylvestre phytocompounds mainly triterpene saponins against targeted proteins and helps in seeking exemplar drug candidates. The study is designed in 2 major parts—firstly identifying key proteins involved in pathophysiology by tracing back the deregulated genes in mRNA expression profiles of PCOS Patients obtained from GEO datasets database further compared and analysed by GEO2R Analyzer and significantly deregulated genes were subjected to PPI network, KEGG and GO analysis using STRING and ShinyGO tools. The second half of the study involved molecular docking its visualisation and in silico pharmacological analysis of imminent phytocompounds revealing plausible drug candidates. Results In the study, most implied deregulated genes were MRP gene family, ICT1, NDUFA12, VDAC3, APOO, TOMM5, COX6C, COX7B, EDN1 and EDN3 genes whose functional enrichment suggests flawed metabolism of proteins and damaged mitochondrial translation. With high binding affinity, less toxicity at higher dose level Lupeol, Beta-Amyrin, Beta-Elemene, Stigmasterol, Gymnestrogenin and Dammarane proves to be efficient drug candidates. Conclusion The findings of this study imply better understanding of the molecular mechanism of the disorder and encourage further clinical studies pertaining to medicinal natural phytocompounds of Gymnemasylvestre.

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Evaluation of Gymnema sylvestre R. Br. against Letrozole Induced Polycystic Ovarian Syndrome in rats

Cited by 7 publications

References 24 publications

Revolutionizing anti-cancer drug discovery against breast cancer and lung cancer by modification of natural genistein: an advanced computational and drug design approach

Revolutionizing anti-cancer drug discovery against breast cancer and lung cancer by modification of natural genistein: an advanced computational and drug design approach

Effect of Triclisia subcordata Oliv. (Menispermaceae) leaves on hormonal imbalance and genes expression in the ovaries of letrozole-induced polycystic rats via in vivo and computational approaches

Gymnema sylvestre as a potential therapeutic agent for PCOS: insights from mRNA differential gene expression and molecular docking analysis

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