Deciphering multifaceted molecular mechanisms of matairesinol in inhibiting triple-negative breast cancer through comprehensive systems biology investigations

Triple-negative breast cancer (TNBC), characterized by the absence of Estrogen Receptor (ER), Progesterone Receptor (PR), and amplified HER2, represents an aggressive subtype devoid of targeted therapies, contributing to heightened mortality rates. Matairesinol (MAT) has demonstrated anti-cancer, anti-inflammatory, immunomodulatory, anti-migratory, and antiangiogenic activities. This study investigates MAT's therapeutic potential for TNBC, employing network pharmacology, molecular docking, and molecular dynamics simulations. Through the integration of MAT and TNBC targets from public databases, we identified 47 potential therapeutic targets. Top 10 hub targets, including HIF1A, ESR1, AKT1, EGFR, HSP90AA1, Src, ERBB2, IGF1, ANXA5, and MAPK1, were revealed through protein-protein interaction analysis. Biological enrichments, encompassing GO and KEGG pathway analyses, unveiled insights into functional roles and associated pathways. The Compound-Targets-Pathways-Disease (C-T-P-D) network illustrated relationships between MAT, its targets, and pertinent pathways. Exploring protein-protein interactions with STRING, followed by validation and supplementation using the GeneMANIA-based functional association (GMFA) method and David web wizard, emphasized the MAPK signaling pathway as a more potential target of MAT against TNBC. The biological significance of these findings underscores MAT's potential as a multi-target inhibitor within multiple signaling pathways related to TNBC, showcasing its efficacy against TNBC. Molecular docking and dynamics simulations substantiated the interaction between MAT and the identified hub targets. In conclusion, our in-silico analysis proposes that MAT could mediate a multi-target and multi-pathway anti-TNBC effect with the MAPK pathway as its novel target pathway. These insights into the potential therapeutic mechanisms of MAT offer valuable directions for further research and the development of interventions against TNBC.

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Journal
Journal of Biomolecular Structure and Dynamics
Published
2025-03-26
DOI
https://doi.org/10.1080/07391102.2025.2480259
Citations
1
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
1.50
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article

Deciphering multifaceted molecular mechanisms of matairesinol in inhibiting triple-negative breast cancer through comprehensive systems biology investigations

Amol Chaudhary, Aniket Mali, Prajakta Patil, Vishwambhar Vishnu Bhandare et al.
1 citations
Journal of Biomolecular Structure and Dynamics
Computational Drug Discovery Methods
1.50
article

Deciphering multifaceted molecular mechanisms of matairesinol in inhibiting triple-negative breast cancer through comprehensive systems biology investigations

Amol Chaudhary, Aniket Mali, Prajakta Patil, Vishwambhar Vishnu Bhandare, Rajesh B. Patil, Amrita Ulhe, Nidhi Sharma, Akanksha Mahajan
article en
1 citations

Abstract

Triple-negative breast cancer (TNBC), characterized by the absence of Estrogen Receptor (ER), Progesterone Receptor (PR), and amplified HER2, represents an aggressive subtype devoid of targeted therapies, contributing to heightened mortality rates. Matairesinol (MAT) has demonstrated anti-cancer, anti-inflammatory, immunomodulatory, anti-migratory, and antiangiogenic activities. This study investigates MAT's therapeutic potential for TNBC, employing network pharmacology, molecular docking, and molecular dynamics simulations. Through the integration of MAT and TNBC targets from public databases, we identified 47 potential therapeutic targets. Top 10 hub targets, including HIF1A, ESR1, AKT1, EGFR, HSP90AA1, Src, ERBB2, IGF1, ANXA5, and MAPK1, were revealed through protein-protein interaction analysis. Biological enrichments, encompassing GO and KEGG pathway analyses, unveiled insights into functional roles and associated pathways. The Compound-Targets-Pathways-Disease (C-T-P-D) network illustrated relationships between MAT, its targets, and pertinent pathways. Exploring protein-protein interactions with STRING, followed by validation and supplementation using the GeneMANIA-based functional association (GMFA) method and David web wizard, emphasized the MAPK signaling pathway as a more potential target of MAT against TNBC. The biological significance of these findings underscores MAT's potential as a multi-target inhibitor within multiple signaling pathways related to TNBC, showcasing its efficacy against TNBC. Molecular docking and dynamics simulations substantiated the interaction between MAT and the identified hub targets. In conclusion, our in-silico analysis proposes that MAT could mediate a multi-target and multi-pathway anti-TNBC effect with the MAPK pathway as its novel target pathway. These insights into the potential therapeutic mechanisms of MAT offer valuable directions for further research and the development of interventions against TNBC.

Journal of Biomolecular Structure and DynamicsVol. 44(2)
Shivaji University (IN), Sinhgad Dental College and Hospital (IN), Bharati Vidyapeeth (Deemed to be University) (IN)
Good health and well-being
Openalex Percentile: Top 18%
Computational Drug Discovery Methods
1.50
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