Computational virtual screening and structure-based design of some epidermal growth factor receptor inhibitors

Abstract Background The foremost cause of cancer mortality worldwide was lung cancer. Lung cancer is divided into small cell lung cancer and non-small cell lung cancer (NSCLC). The latter is the main type of lung cancer that account for about 90% of the cancer issues and estimate about 25% of the cancer mortality each year in the world. Among the types of lung cancer with about 1.5 million patients and less than 20% survival rate is NSCLC. Overexpression of EGFR tyrosine kinase was recognized to be the cause of NSCLC. Therefore, there is a need to develop more EGFR inhibitors due to drug-resistance development by the mutation. Result Computational virtual screening on some epidermal growth factor receptor inhibitors (EGFR L858R/T790M inhibitors or NSCLC therapeutic agents) against their target protein (EGFR tyrosine kinase receptor pdb entry 3IKA ) was performed via molecular docking simulation and pharmacokinetics to identify hit compounds with a promising affinity toward their target. The hit compounds discovered were compound 22 with −9.8 kcal/mol, 24 with −9.7 kcal/mol, 17 with −9.7 kcal/mol, and 19 with −9.5 kcal/mol respectively. These lead compounds were further subjected to drug-likeness and ADME prediction and found to be orally bioavailable. Six (6) new EGFR L858R/T790M inhibitors using compound 22 with the highest binding affinity as a template were designed. Conclusion The six newly EGFR L858R/T790M inhibitors were found to have a better binding affinity than the template used in the designing process and AZD9291 (the positive control). None of the designed compounds was found to violate more than the permissible limit set by RO5 thereby predicting their easy transportation, absorption, and diffusion. More so, the designed compounds were found to have good synthetic accessibility which indicates that these designed compounds can be easily synthesized in the laboratory.