In vitro and in silico evaluation of Acalypha indica ethanolic extract on lipid metabolism-related protein expression on breast cancer cells

Dysregulated lipid metabolism has been recognized as one of the most significant metabolic changes in breast cancer development. Acalypha indica is a polyphenol-rich herbal plant with various medicinal applications such as antibacterial, antioxidant, and anticancer activities. However, studies on the inhibitory effect of A. indica ethanolic extract (AI) on breast cancer cells and its efficacy as an alternative lipogenesis inhibitor are still less explored. Therefore, this study was designed to investigate the possible inhibition mechanisms of selected phenolic acids and flavonoids from the extract against MCF-7 breast cancer. The antiproliferative effect of AI was determined using MTT assay. Immunocytochemical analysis was used to evaluate the inhibitory effect of AI on the expression of the three lipogenic enzymes; fatty acid synthase (FASN), acetyl-CoA carboxylase (ACCA), and ATP citrate lyase (ACLY). In addition, molecular docking of the phenolic acids (gallic acid, ferulic acid, and caffeic acid) and flavonoids (rutin and quercetin) were performed using AutoDock Tools, and their ADMET properties were determined using SwissADME and pKCSM web servers. AI treatment resulted in inhibition of cell viability of MCF-7 breast cancer cells after 24 and 48 h. In addition, immunocytochemistry revealed a significant decrease in the expression of FASN, ACCA, and ACLY in MCF-7 cells when compared to control. Docking studies demonstrated that AI phytochemical quercetin was considered the most potential lipogenesis inhibitor due to its lowest binding energy to FASN, ACCA, and ACLY compared to other phytochemicals. Nevertheless, results from ADMET analysis suggested that all compounds except rutin possessed acceptable ADME and toxicity properties. Collectively, these findings indicated that the chemoprevention by AI in breast cancer cells is associated with the inhibition of fatty acid synthesis.

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Journal
Journal of Materials in Life Sciences (JOMALISC)
Published
2024-11-30
DOI
https://doi.org/10.11113/jomalisc.v3.74
Primary Topic
Computational Drug Discovery Methods
Type
article
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0.00

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article

In vitro and in silico evaluation of Acalypha indica ethanolic extract on lipid metabolism-related protein expression on breast cancer cells

Rosnani Hasham, W. Hoo, Mohamad Khairul Hafiz Idris, Khairunadwa Jemon et al.
Journal of Materials in Life Sciences (JOMALISC)
Computational Drug Discovery Methods
article

In vitro and in silico evaluation of Acalypha indica ethanolic extract on lipid metabolism-related protein expression on breast cancer cells

Rosnani Hasham, W. Hoo, Mohamad Khairul Hafiz Idris, Khairunadwa Jemon, Nur Amanina Johari, Nurriza Ab Latif, Syazwani Itri Amran, Lois Tzu Hui Lo
article en

Abstract

Dysregulated lipid metabolism has been recognized as one of the most significant metabolic changes in breast cancer development. Acalypha indica is a polyphenol-rich herbal plant with various medicinal applications such as antibacterial, antioxidant, and anticancer activities. However, studies on the inhibitory effect of A. indica ethanolic extract (AI) on breast cancer cells and its efficacy as an alternative lipogenesis inhibitor are still less explored. Therefore, this study was designed to investigate the possible inhibition mechanisms of selected phenolic acids and flavonoids from the extract against MCF-7 breast cancer. The antiproliferative effect of AI was determined using MTT assay. Immunocytochemical analysis was used to evaluate the inhibitory effect of AI on the expression of the three lipogenic enzymes; fatty acid synthase (FASN), acetyl-CoA carboxylase (ACCA), and ATP citrate lyase (ACLY). In addition, molecular docking of the phenolic acids (gallic acid, ferulic acid, and caffeic acid) and flavonoids (rutin and quercetin) were performed using AutoDock Tools, and their ADMET properties were determined using SwissADME and pKCSM web servers. AI treatment resulted in inhibition of cell viability of MCF-7 breast cancer cells after 24 and 48 h. In addition, immunocytochemistry revealed a significant decrease in the expression of FASN, ACCA, and ACLY in MCF-7 cells when compared to control. Docking studies demonstrated that AI phytochemical quercetin was considered the most potential lipogenesis inhibitor due to its lowest binding energy to FASN, ACCA, and ACLY compared to other phytochemicals. Nevertheless, results from ADMET analysis suggested that all compounds except rutin possessed acceptable ADME and toxicity properties. Collectively, these findings indicated that the chemoprevention by AI in breast cancer cells is associated with the inhibition of fatty acid synthesis.

Journal of Materials in Life Sciences (JOMALISC)
University of Technology Malaysia (MY)
Universiti Teknologi Malaysia
Openalex Percentile: Top 71%
Computational Drug Discovery Methods
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