Computational discovery of novel human LMTK3 inhibitors by high throughput virtual screening using NCI database

Breast cancer is the most common cause for women’s deaths worldwide. LMTK3 has been demonstrated as critical biomarker for ERα positive breast cancer. It regulates breast cancer by phosphorylating estrogen receptor. Association of LMTK3 in breast cancer is connected with disease free and poor overall survival. In this current computational study, virtual screening was accomplished on human LMTK3 using a large library of NCI database in Schrodinger. From the ligand library, the best compounds were selected and evaluated based on molecular docking using Glide module and their relative molecular dynamics using Desmond. Different parameters like binding energy and interactions like hydrogen bond and hydrophobic contacts have a significant impact on LMTK3 inhibition. Based on docking score, the best lead molecules were separated and analyzed for ADME properties using QikProp tool. Overall, our results confirmed the compounds NCI26194 had been screened from the NCI database, which has the potential to act as key drug molecule for ERα positive breast cancer. In conclusion, our computer aided technique on human LMTK3 has high perspective for the development of novel anticancer agent for breast cancer treatment.