Comprehensive pharmacokinetic profiling and molecular docking analysis of natural bioactive compounds targeting oncogenic biomarkers in breast cancer

Breast cancer is one of the leading causes of death in women worldwide, highlighting the crucial need for novel and effective treatments. In this study, we look at the ability of four natural compounds i.e. Berberine, Curcumin, Withaferin A, and Ellagic Acid to target important breast cancer biomarkers such as B-cell lymphoma 2 (BCL-2), programmed death-ligand 1 (PDL-1), cyclin-dependent kinase 4/6 (CDK4/6) and fibroblast growth factor receptor (FGFR). These indicators have important roles in tumor development, survival, immune response, and cell cycle control, making them potential targets for future cancer treatments. Our study employs a variety of techniques, including pharmacokinetic profiling (ADME), molecular docking, and molecular dynamics simulations, to determine how successful these drugs could be in therapy. The pharmacokinetic investigation found that Berberine and Ellagic Acid stand out due to their high absorption and solubility, implying that they could be suitable for clinical application. When we ran docking simulations, we discovered substantial connections between these chemicals and the target proteins. Additionally, Berberine has a binding affinity of - 9.3 kcal/mol for BCL-2, indicating that it can impair the protein's cancer cell-protective activities. Ellagic Acid, on the other hand, has an even higher binding affinity for PDL-1 of - 9.8 kcal/mol, showing that it may be able to increase immune responses against tumors. Molecular dynamics simulations over 100 ns demonstrated the stability of these protein-ligand complexes. Interestingly, Ellagic Acid was found to be more structurally stable than Berberine throughout these simulations. We found consistent interactions between the chemicals and key residues in the target proteins. For example, Ellagic Acid (CID: 5281855) established persistent linkages with LYS43, ASP163, and VAL27, whereas Berberine (CID: 2353) interacted with VAL27, ALA41, and LEU152 throughout the simulation. In conclusion, the combination of good pharmacokinetics, robust interactions with cancer biomarkers, and stable complexes makes Berberine and Ellagic Acid interesting candidates for further investigation as natural inhibitors in breast cancer treatment. These findings establish the framework for future research into novel and inventive techniques to effectively combating breast cancer.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2025-02-13
DOI
https://doi.org/10.1038/s41598-024-84401-4
Citations
22
Primary Topic
Cancer Genomics and Diagnostics
Type
article
Field-Weighted Citation Impact
20.60
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Comprehensive pharmacokinetic profiling and molecular docking analysis of natural bioactive compounds targeting oncogenic biomarkers in breast cancer

Mohammad A. Albanghali, Basim Othman, Hina Rashid, Yasser Kofiah et al.
22 citations
Scientific Reports
Cancer Genomics and Diagnostics
20.60
article

Comprehensive pharmacokinetic profiling and molecular docking analysis of natural bioactive compounds targeting oncogenic biomarkers in breast cancer

Mohammad A. Albanghali, Basim Othman, Hina Rashid, Yasser Kofiah, Mohammed A. Shanawaz, Saba Beigh, Abdulmajeed Abdulghani A. Sindi, Dina Marghani, Nuzhat Iqbal, Mohamed Awad Elkarim Mohamed Ibahim
article en
22 citations

Abstract

Breast cancer is one of the leading causes of death in women worldwide, highlighting the crucial need for novel and effective treatments. In this study, we look at the ability of four natural compounds i.e. Berberine, Curcumin, Withaferin A, and Ellagic Acid to target important breast cancer biomarkers such as B-cell lymphoma 2 (BCL-2), programmed death-ligand 1 (PDL-1), cyclin-dependent kinase 4/6 (CDK4/6) and fibroblast growth factor receptor (FGFR). These indicators have important roles in tumor development, survival, immune response, and cell cycle control, making them potential targets for future cancer treatments. Our study employs a variety of techniques, including pharmacokinetic profiling (ADME), molecular docking, and molecular dynamics simulations, to determine how successful these drugs could be in therapy. The pharmacokinetic investigation found that Berberine and Ellagic Acid stand out due to their high absorption and solubility, implying that they could be suitable for clinical application. When we ran docking simulations, we discovered substantial connections between these chemicals and the target proteins. Additionally, Berberine has a binding affinity of - 9.3 kcal/mol for BCL-2, indicating that it can impair the protein's cancer cell-protective activities. Ellagic Acid, on the other hand, has an even higher binding affinity for PDL-1 of - 9.8 kcal/mol, showing that it may be able to increase immune responses against tumors. Molecular dynamics simulations over 100 ns demonstrated the stability of these protein-ligand complexes. Interestingly, Ellagic Acid was found to be more structurally stable than Berberine throughout these simulations. We found consistent interactions between the chemicals and key residues in the target proteins. For example, Ellagic Acid (CID: 5281855) established persistent linkages with LYS43, ASP163, and VAL27, whereas Berberine (CID: 2353) interacted with VAL27, ALA41, and LEU152 throughout the simulation. In conclusion, the combination of good pharmacokinetics, robust interactions with cancer biomarkers, and stable complexes makes Berberine and Ellagic Acid interesting candidates for further investigation as natural inhibitors in breast cancer treatment. These findings establish the framework for future research into novel and inventive techniques to effectively combating breast cancer.

Scientific ReportsVol. 15(1)
Islamia University of Bahawalpur (PK), Taibah University (SA), Al Baha University (SA), Jazan University (SA)
Openalex Percentile: Top 0%
Cancer Genomics and Diagnostics
20.60
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.