Abstract
Epidermal growth factor receptor (EGFR) is a transmembrane glycoprotein that is overexpressed in a variety of human malignancies and is often associated with chemoresistance and a poor clinical outcome. It is overexpressed in as many as 60% cases of breast and other cancers. EGFR signaling is not only critical for cell proliferation but also contribute to other processes that are crucial to cancer progression, including angiogenesis, metastatic spread, and the inhibition of apoptosis. In this study, hit identification was performed by virtual screening of commercial and in-house compound libraries. Docking studies using AutoDock 3.0 for the hits were performed, and scoring functions were used to evaluate the docking results and to rank the ligand binding affinities. Subsequently, hit optimization for potent and selective candidate of EGFR inhibitors was performed through focused library design and docking analysis. Consequently, compound of Andrographis paniculata nees which is Neoandrographolide is highly selective for EGFR in comparison to Dehydroandrographolide and other Andrographis paniculata nees compounds. Neoandrographolide exert anti-proliferative effect on EGFR-expressing breast cancer, with calculated inhibition constant values of 102.04nM. This inhibition constant value is compared with Lapatinib inhibition constant values of 141. 71 nM. Moreover, other Andrographis paniculata nees compounds expressed the phosphorylation of extracellular signal-regulated kinases with the range of inhibition constant values of 7.91 uM to 773.52nM. The docking structure of Neoandrographolide with EGFR disclosed that the pyrrolidine ring appeared to fit tightly into the hydrophobic pocket of EGFR, with a minimum free binding energy of -9.54 kcal/mol. Additionally, it forms hydrogen bonds with Thr854 and Asp855. These results confirm the successful application of virtual screening studies in the lead discovery process, and suggest that Neoandrographolide can be an effective EGFR inhibitor candidate for further lead optimization.
Metadata
Item Type: | Thesis (Degree) |
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Creators: | Creators Email / ID Num. Tajor Amar, Sayangku Aini UNSPECIFIED |
Contributors: | Contribution Name Email / ID Num. Thesis advisor Mohd Shah, Ismail UNSPECIFIED |
Subjects: | H Social Sciences > HD Industries. Land use. Labor > Special industries and trades > Pharmaceutical industry R Medicine > RC Internal Medicine > Cancer |
Divisions: | Universiti Teknologi MARA, Selangor > Puncak Alam Campus > Faculty of Pharmacy |
Programme: | Bachelor of Pharmacy |
Keywords: | drug modeling, andrographis paniculata nees (hempedu bumi), breast cancer |
Date: | 2009 |
URI: | https://ir.uitm.edu.my/id/eprint/107053 |
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