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Assessment of Resistance to Tyrosine Kinase Inhibitors by an Interrogation of Signal Transduction Pathways by Antibody Arrays
Published on: September 19, 2018
Comparative docking analysis of tyrosine kinase inhibitors with HER2 and HER4 receptors
Priyanka Sonar1, Karimunnisa Shaikh1, Sangeeta Ballav2
1Department of Pharmaceutics, Progressive Education Society's, Modern College of Pharmacy, Nigdi, Pune, M.S, India.
Abstract:
Tyrosine kinase receptors promote the growth and differentiation of normal breast and malignant human breast cancer cells, known as ERBB receptors. Various ERBB receptors are EGFR/ErbB1 and ErbB2/neu, which get over expressed in different solid tumors that activate upon binding of ligand to the extra cellular domain of these receptors. Of note, the epidermal growth factor receptor (EGFR) is a prime contributor to cancer through the involvement of four receptor tyrosine kinases (RTKs), namely, HER1, HER2, HER3, and HER4. Among them, HER2 and HER4 are majorly associated with breast cancer. Non-peptide quinazoline compounds homologous of the adenosine triphosphate (ATP) are competitively inhibited to RTKs to prevent cancer growth and metastasis. Various small drug molecule that targets the RTKs having the same scaffold, includes Lapatinib, Tivozanib, Erlotinib, Gefitinib, Crizotinib, and Ceritinib. The present study aims to investigate the comparative potential of structurally similar TKIs against HER2 and HER4 receptor receptors-silico molecular docking using FlexX software (LeadIT 2.3.2). Each docked complex's interaction profile was performed using BIOVIA Discovery Studio Visualizer 4.0. Molecular docking analysis was performed in order to get deeper insights into the interaction and binding pattern of the ligands with HER2 and HER4 receptors. The docking results revealed the Lapatinib compound acquired the relatively highest binding score of -32.36 kcal/mol and -35.76 kcal/mol with HER2 and HER4 proteins, respectively, concerning other compounds. Lapatinib is identified as a potential inhibitor for both the RTKs. Our study thus suggests the probable direction that could be further explored in inhibiting EGFR protein harboring breast cancer.
Insights
Lapatinib shows potential as a dual inhibitor for HER2 and HER4 receptor tyrosine kinases (RTKs), crucial in breast cancer progression. This study highlights Lapatinib
Area of Science:
- Oncology
- Molecular Biology
- Pharmacology
Background:
- Tyrosine kinase receptors, specifically ERBB receptors like EGFR, play a critical role in breast cancer growth and metastasis.
- Overexpression of HER2 and HER4 is significantly associated with human breast cancer development.
- Small molecule inhibitors targeting receptor tyrosine kinases (RTKs) offer a therapeutic strategy against cancer.
Purpose of the Study:
- To comparatively evaluate the inhibitory potential of structurally similar tyrosine kinase inhibitors (TKIs) against HER2 and HER4 receptors.
- To investigate the molecular interactions and binding patterns of these TKIs with HER2 and HER4 using in-silico methods.
Main Methods:
- Utilized in-silico molecular docking with FlexX software to assess TKI binding to HER2 and HER4.
- Analyzed docked complex interaction profiles using BIOVIA Discovery Studio Visualizer.
- Compared binding scores of various small molecule TKIs, including Lapatinib, Tivozanib, Erlotinib, Gefitinib, Crizotinib, and Ceritinib.
Main Results:
- Lapatinib demonstrated the highest binding scores (-32.36 kcal/mol with HER2 and -35.76 kcal/mol with HER4) among the tested compounds.
- Molecular docking analysis provided insights into the binding patterns and interactions of Lapatinib with both HER2 and HER4.
- Lapatinib was identified as a potent inhibitor for both HER2 and HER4 receptor tyrosine kinases.
Conclusions:
- Lapatinib is a promising candidate for inhibiting both HER2 and HER4, suggesting its potential in treating breast cancers driven by these RTKs.
- The findings support further investigation into Lapatinib's efficacy for inhibiting EGFR-family proteins in breast cancer.
- This study provides a computational basis for developing targeted therapies against HER2 and HER4 in breast cancer.
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