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1.
Mol Biol Rep ; 51(1): 303, 2024 Feb 15.
Artigo em Inglês | MEDLINE | ID: mdl-38356030

RESUMO

BACKGROUND: This study aimed to assess silymarin's anticancer and antifibrotic potential through in silico analysis and investigate its impact on in vitro arecoline-induced fibrosis in primary human buccal fibroblasts (HBF). METHODS & RESULTS: The study utilized iGEMDOCK for molecular docking, evaluating nine bioflavonoids, and identified silymarin and baicalein as the top two compounds with the highest target affinity, followed by subsequent validation through a 100ns Molecular Dynamic Simulation demonstrating silymarin's stable behavior with Transforming Growth Factor Beta. HBF cell lines were developed from tissue samples obtained from patients undergoing third molar extraction. Arecoline, a known etiological factor in oral submucous fibrosis (OSMF), was employed to induce fibrogenesis in these HBFs. The inhibitory concentration (IC50) of arecoline was determined using the MTT assay, revealing dose-dependent cytotoxicity of HBFs to arecoline, with notable cytotoxicity observed at concentrations exceeding 50µM. Subsequently, the cytotoxicity of silymarin was assessed at 24 and 72 h, spanning concentrations from 5µM to 200µM, and an IC50 value of 143µM was determined. Real-time polymerase chain reaction (qPCR) was used to analyze the significant downregulation of key markers including collagen, epithelial-mesenchymal transition (EMT), stem cell, hypoxia, angiogenesis and stress markers in silymarin-treated arecoline-induced primary buccal fibroblast cells. CONCLUSION: Silymarin effectively inhibited fibroblast proliferation and downregulated genes associated with cancer progression and EMT pathway, both of which are implicated in malignant transformation. To our knowledge, this study represents the first exploration of silymarin's potential as a novel therapeutic agent in an in vitro model of OSMF.


Assuntos
Arecolina , Fibrose Oral Submucosa , Humanos , Arecolina/efeitos adversos , Arecolina/metabolismo , Mucosa Bucal/metabolismo , Simulação de Acoplamento Molecular , Fibrose Oral Submucosa/induzido quimicamente , Fibrose Oral Submucosa/tratamento farmacológico , Fibrose Oral Submucosa/metabolismo , Fibroblastos/metabolismo , Fibrose
2.
J Biomol Struct Dyn ; 41(11): 4863-4872, 2023 07.
Artigo em Inglês | MEDLINE | ID: mdl-35575483

RESUMO

Obesity is considered a global crisis because of its increased risk factors triggered by lifestyle changes. The prevalence of this condition is increasing at an alarming rate, giving rise to development of novel drugs. Pancreatic lipase possesses higher efficacy in inhibiting this condition among the other drug targets. In this study, virtual screening of 126 plant-derived anti-obesity compounds and 1110 marine algal compounds from seaweed metabolite database were screened and targeted against pancreatic lipase and ranked based on their binding affinity values. A total of 530 compounds that possessed best docked scores of less than -6 kcal/mol were checked for Lipinski's properties through Swiss ADME. Furthermore, these compounds were subjected to toxicity prediction using PROTOX II server. As much as 38 compounds were found to be non-toxic and were subjected to molecular docking analysis. Based on the binding energy, the following compounds RG012 (-10.15 kcal/mol), LIG42 (-9.7 kcal/mol), BC010 (-8.47 kcal/mol), RL073 (-8.2 kcal/mol), and LIG46 (-8.03 kcal/mol) were selected exhibiting higher binding affinity when compared to the standard drug (Orlistat) and hence these compounds were subjected to molecular dynamics simulation using GROMACS. BC010 complex revealed a stable interaction within the binding pocket and the binding free energy is -158.208 kJ/mol which is higher when compared to other complexes in 100 ns simulation. BC010 ((7S,11S,12S,14R)-4',14-dimethoxyamentol) from brown algae Cystophora fibrosa could be considered as a potential drug candidate to suppress obesity by inhibiting pancreatic lipase.Communicated by Ramaswamy H. Sarma.


Assuntos
Manejo da Obesidade , Humanos , Simulação de Acoplamento Molecular , Lipase , Simulação de Dinâmica Molecular , Obesidade
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