QSAR of clinically important EGFR mutant L858R/T790M pyridinylimidazole inhibitors

EGFR is a clinically important drug target in Lung cancer. However, occurrence of secondary mutation makes first‐generation inhibitors ineffective and thus new inhibitors are needed. Therefore, we have generated QSAR models of pyridinylimidazole based TMLR inhibitors to identify descriptors that regulate bioactivity. We discuss contributions of important descriptors and provide clues for design of newer inhibitors. We also design few derivatives that exhibit better inhibitory activity and thus expect the study to provide insight for designing of potent EGFR mutant inhibitors.

Abstract

EGFR is a well‐established therapeutic target of clinical relevance in cancer. However, acquisition of secondary mutation (T790M) makes first generation inhibitors ineffective. Therefore, to circumvent the problem of resistance new T790M/L858R double mutants (TMLR) inhibitors are required. In this study, fragment based QSAR models (GQSAR) were generated for pyridinylimidazole derivatives having biological activity against TMLR mutants. The GQSAR model developed using partial least squares regression via stepwise forward‐backward variable selection technique showed best results as judged using statistical parameters (r², q² and pred_r²). Additionally, applicability domain of the model was verified using Williams's plot, which indicated that the predicted data is reliable. The GQSAR provided site‐specific clues wherein modifications related to decreasing lipophilic character, rotatable bonds and increasing SaaCHE‐index are required for improving inhibitory activity. Overall, the study indicated that presence of acrylamide at R5 is essential for covalent bond formation with Cys797 and occurrence of aromatic residue at R2 is required for occupying hydropbhobic region next to Met790 gatekeeper residue. Based on this information, new derivatives were designed that show better inhibitory activity than the experimentally reported most active molecules. Thus, the model developed can be used to design new pyridinylimidazole derivatives with improved TMLR bioactivity.

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