#4 Computer-aided drug discovery: From small compounds to protein inhibitors against tyrosine kinase of EGFR for cancer therapy

Abstract

Computational studies are an essential part of research in Biochemistry today. The goal of the theoretical investigation of biochemical processes is to gain a deeper insight into the molecular mechanism behind the process of study. It can further be used to predict the results of experiments. Protein Bioinformatics is a useful technique to understand biochemical processes of proteins on various levels including protein modeling, protein docking, and protein molecular dynamics. In our group, we focus on the anticancer targeted protein, the epidermal growth factor receptor (EGFR). This protein plays a crucial role in cellular signaling pathways that regulates key functions, especially proliferation. EGFR abnormalities have been associated with several types of human cancer. Nowadays, there are cancer-treated drugs that inhibit the activity of the tyrosine kinase (TK) domain of EGFR – a signaling part of this protein. However, each drug specifically treats with each cancer type and some tumor patients have resisted to those drugs. The Discovery of better new efficient inhibitors is extremely needed. The virtual screening of medicinal plant compound databases against EGFR-TK has been used to discover new inhibitors. These compounds were tested on enzymatic inhibiting assay and non-small cell lung cancer cells, A549.