Impact of EGFR point mutations on the sensitivity to gefitinib: insights from comparative structural analyses and...

Emergence of resistant mutations in drug targets represents a serious problem in the targeted chemotherapy. One challenging issue is to understand the atomic-detailed effect of the mutation on the target. Another intriguing issue is how to predict specific mutations that would show up in the clinical setting, leading to drug resistance. By computational approaches, we have investigated structural, dynamics and energetic effects of a series of EGFR mutations identified from the lung cancer patients. We demonstrated mutation L858R caused gefitinib move closer to the hinge region, whereas T790M caused the ligand escape from the binding pocket. In particular, the T790M decreased the size of the hydrophobic slot formed by L718 and G796. This suggests that, to be effective against the T790M mutant, the inhibitors should avoid interactions with the hydrophobic slot. Mutations T790M, L858R, and their combinations are found to cause different conformational redistribution and to perturb the electrostatic potential at the ATP-binding pocket. Normal mode analysis revealed the mutations resulted in changes in the correlated movements in the protein. In an attempt to develop a computational descriptor for predicting the functional effect of EGFR mutations, we have developed a Plarm algorithm, and the Plarm score was found to be an excellent predictor of the functional impact of six clinical relevant mutations in EGFR tyrosine kinase domains, including T790M, L858R, G719C, L861Q, T790M + L858R double mutant, and delL747-P753insS. The Plarm algorithm could be readily extended to investigate other drug targets.