IDENTIFICATION OF POTENTIAL NOVEL EGFR INHIBITORS USING A COMBINATION OF PHARMACOPHORE AND DOCKING METHODS

Objective: Identifying new inhibitors of Epidermal Growth Factor Receptor (EGFR) by virtual screening using a pharmacophore model followed by docking. Methods: A pharmacophore model was developed using a dataset of 77 chemically diverse EGFR inhibitors using PHASE. Statistically valid Three Dimensional Quantitative Structure Activity Relationship (3D-QSAR) equations were generated for the pharmacophore model. This was followed by database screening to obtain probable hits. Docking of the probable hits into the crystal structure of EGFR was used as a second filter. Docking studies were carried out using GLIDE. Calculation of ADME properties of the probable hits arising out of docking further reduced the number of hits. Results: A five-point pharmacophore was generated for EGFR inhibitors reported in literature. The pharmacophore indicated that the presence of two aromatic ring features (R), one acceptor feature (A), one donor feature (D) and one hydrophobic feature (H) is necessary for potent inhibitory activity. The generated pharmacophore yielded statistically significant 3D-QSAR model, with a correlation coefficient r 2 of 0.9905 and q 2 of 0.8764. Virtual screening using the best pharmacophore model resulted in 372 hits. Docking studies as a second filter reduced the hits to 8. Application of drug-likeness as a third filter gave 6 leads. Conclusion: 6 leads with satisfactory pharmacokinetics properties were identified as potential EGFR inhibitors. This study may facilitate development of some new potential EGFR inhibitors.