Exploring Therapeutic Potentials of Natural Agents Against Breast Cancer Using Molecular Modeling

Yıl 2025, Cilt: 35 Sayı: 1, 52 - 69, 28.02.2025

Nil Sazlı Deniz Karataş

https://doi.org/10.54005/geneltip.1494859

Öz

Abstract
Background/Aims:
Cancer occurs when cells divide and multiply uncontrollably as a result of changes in hereditary materials such as DNA. There are many types of cancer, and breast cancer is the most common type worldwide, causing high mortality rates among women. This disease occurs when normal breast cells become abnormal, grow, and multiply uncontrollably, resulting in malignant cells. When examining literature studies, mutations in the BRCA1 (Breast Cancer Type 1 susceptibility protein) gene appear to be associated with breast cancer. Mutations in this gene cause the formation and progression of breast cancer. Therefore, understanding the mechanisms of mutations in the BRCA1 gene at the atomistic level is very important for breast cancer treatment. In recent years, it has become very popular to investigate the effect of target proteins mutated by molecular insertion on breast cancer. Thus, searching for alternative treatment methods for many diseases, especially breast cancer, from a different perspective allows the development of new strategies.
In this study, the aim was to discover alternative natural agents to the chemical drug 5-Fluorouracil (5FU) and to reveal their therapeutic potential on breast cancer by selecting the crystal receptor structure associated with the BRCA1 gene and examining the relationships of this gene with breast cancer-related natural agents curcumin, resveratrol, and quercetin.
Methods:
In this study, the crystal structure of the BRCA1 gene with PDB ID 3FA2, obtained from the Protein Data Bank, was chosen as the receptor. To examine the relationship of the BRCA1 gene with breast cancer, the 3FA2 receptor was mutated to obtain two receptors: wild-type and mutant-type 3FA2. The binding affinities and structural stability of the complex structures obtained by applying molecular docking and molecular dynamics simulation with the natural ligands curcumin, quercetin, and resveratrol, as well as the chemical ligand 5FU, were evaluated. To determine the drug potential of alternative natural agents to the chemical drug 5FU in the treatment of breast cancer caused by BRCA1 gene mutation, ADMET analyses were performed, and their pharmacodynamic and pharmacokinetic properties were analyzed.
Results:
As a result of molecular placements using mutant-type and wild-type 3FA2 receptors with natural agents and chemical drug ligands, the binding affinities of the natural agents were found to be -6.6 kcal/mol and below, while the affinity score of the chemical drug ligand was -5.6 kcal/mol. This proves that natural agents have much better interactions with breast cancer-associated receptors. RMSD, RMSF, Rg, and RDF analyses performed as a result of molecular dynamics simulation show that the receptor-ligand complex structures formed, especially with natural agents, have very good stability. It was found that curcumin, which has the lowest binding score and stable values among these structures, has a strong binding affinity with receptors, a stable structure, and pharmacokinetic properties, making it a potential good drug candidate compared to other ligands.
Conclusion:
This study, based on molecular docking and molecular dynamics simulation approaches, shows that the natural agents curcumin, quercetin, and resveratrol may be alternative therapeutic drug candidates to the chemical drug 5FU in the treatment of breast cancer caused by BRCA1 gene mutation. In particular, the fact that curcumin has a good binding interaction score with receptors associated with BRCA1 genes, forms a stable structure, and has the expected pharmacokinetic profile is promising for the discovery of new therapeutic natural agents for breast cancer treatment.

Anahtar Kelimeler

Breast Cancer, BRCA1, Molecular Docking, Molecular Dynamics Simulation

Teşekkür

Computing resources used in this work for molecular docking and MD simulations were totally provided by the National Center for High Performance Computing of Turkey (UHeM) under grant numbers 1013972022 and 4016782023.

Kaynakça

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