Effect of Caryophyllene rich betel leaf extract on Triple Negative Breast Cancer cells: an in-silico and in-vitro approach

Effect of Caryophyllene rich betel leaf extract on Triple Negative Breast Cancer cells: an in-silico and in-vitro approach

Registration ID: IJNRD_200362

Published ID: IJNRDTH00059

DOI: http://doi.one/10.1729/Journal.35004

Disha Mohanty , Kamaljit Nag , Luna Samanta

β-Caryophyllene, CB2R, Triple Negative Breast Cancer, MTT, Live Dead Assay

Triple-Negative Breast Cancer (TNBC) is a more advanced subtype of breast cancer that does not express the estrogen receptor, progesterone receptor and HER2/neu receptor. It is a kind of breast cancer which lacks all of those receptors that are commonly found in breast cancer. Because TNBC lacks the three receptors that are commonly targeted in breast cancer treatment, it can be more difficult to treat than other subtypes of breast cancer. This underscores the importance of investigating other factors that contribute to TNBC progression and developing novel therapies to target these factors. On the other hand, there is a growing body of research aimed at identifying new targets and therapies for TNBC. This ongoing research has been focused on the anticancer effects of Caryophyllene, which has been derived from the Piper betle leaf extracts. Caryophyllene, better known as β-caryophyllene, is a cannabis derived compound, which directly binds to cannabinoid receptors. These receptors have broadly been categorized into two receptors - Cannabinoid Receptor-1 (CB1R) and Cannabinoid Receptor-2 (CB2R). This study aims to identify the protein-ligand interaction between the CB2R and Caryophyllene, through an in-silico approach. It also aims to find the stimulating parameter between the protein and the ligand through an in-vitro approach on Piper betle leaves, which can detect the anticancer effects of Caryophyllene and its potent applications in TNBC treatment. For the in-silico work, a range of bioinformatics tools was utilized, such as PyMOL, AutoDockTools-1.5.7, and AutoDock Vina. Additionally, a few websites were utilized for compound screening, including PDB Database, Pubchem and UniprotKB. For the in-vitro research, two methods, which consisted of MTT Assay and Live Dead Assay, were notably used for analyzing Piper betle leaf extract. It was discovered that upon docking with the CB2R, the β-caryophyllene ligand does not form any polar hydrogen bonds with amino acid residues. It only engages in π-π stacking interactions with hydrophobic amino acid residues, particularly with phenylalanine. The MTT & Live Dead Assay was conducted using the MDA-MB-231 cell line, and the IC50 value was observed to be 0.3%. The compound β-caryophyllene drastically decreased the number of viable cells in the MDA-MB-231 cell line. These novel techniques identify the efficacy of Caryophyllene towards the prognosis and treatment of TNBC.

Published Paper   E-Certificate

"Effect of Caryophyllene rich betel leaf extract on Triple Negative Breast Cancer cells: an in-silico and in-vitro approach", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.8, Issue 6, page no.738-794, June-2023, Available :https://ijnrd.org/papers/IJNRDTH00059.pdf

Volume 8 Issue 6, June-2023

Pages : 738-794

Paper Reg. ID: IJNRD_200362

Published Paper Id: IJNRDTH00059

Downloads: 000121234

Research Area: Biological Science

Country: Cuttack, Odisha, India

Published Paper PDF: https://ijnrd.org/papers/IJNRDTH00059.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRDTH00059

DOI: http://doi.one/10.1729/Journal.35004

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

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This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition

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