In silico identification of EGFR-T790M inhibitors with novel scaffolds: start with extraction of common features
Mingli Xiang,1,* Kai Lei,1,* Wenjie Fan,1 Yuchun Lin,2 Gu He,1 Mingli Yang,3 Lijuan Chen,1 Yirong Mo4
1The State Key Laboratory of Biotherapy, West China Hospital, West China Medical School, Sichuan University, Chengdu, People’s Republic of China; 2Department of Chemical and Biomolecular Engineering, University of California, Berkeley, CA, USA; 3Institute of Atomic and Molecular Physics, Sichuan University, Chengdu, People’s Republic of China; 4Department of Chemistry, Western Michigan University, Kalamazoo, MI, USA
*These authors contributed equally to this work
Background: Epidermal growth factor receptor (EGFR) is an attractive therapeutic target for a number of human tumors including non-small cell lung cancer (NSCLC). Most patients with NSCLC and somatic mutations have shown a dramatic initial clinical response to reversible EGFR inhibitors. The clinical efficacy of reversible inhibitors is, however, ultimately limited due to the emergence of drug resistance, which is usually conferred by the EGFR T790M mutation. Importantly, irreversible, synthetic small molecule inhibitors are currently evaluated and some of them have been shown to overcome the acquired resistance that is oftentimes observed in these patients. Thus far, irreversible EGFR inhibitors as a drug class have not received regulatory approval due in part to their poor effectiveness at clinically achievable concentrations. Therefore, there is an urgent need to discover and develop novel, potent irreversible inhibitors against the EGFR T790M mutation.
Material and methods: In the following study, we report a novel “hybrid strategy” to identify irreversible EGFR inhibitors with active scaffolds starting with the identification and extraction of a common chemical reactive feature and a pharmacophore feature. The chemical reactive feature was elucidated by investigating 138 currently known irreversible inhibitors at B3LYP/6-31G(d) level using the density function theory method. The pharmacophore feature was extracted from the same inhibitors using pharmacophore modeling. Based on these unique features, two constraints were set while calibrating the protocols of in silico screening. Compounds bearing these specific features were obtained from the National Cancer Institute diversity database to form our subsequent library. Finally, a structure based virtual screening against the library was conducted using standard protocols validated in our lab.
Results: Twenty-eight candidate compounds that demonstrated antitumor activity and that had novel scaffolds different from commonly known quinazoline/quinoline analogs were obtained. The interaction modes between three representative candidates and our model system are similar to that between the model system and the reference compound T-001, which has previously been reported to be one of the most potent of the 138 irreversible inhibitors.
Conclusion: The hybrid strategy starting with the extraction of common features is an effective approach to design potential irreversible inhibitors with novel scaffolds and therefore to obtain lead molecules in the selection process. These candidates possessing unique scaffolds have a strong likelihood to act as further starting points in the preclinical development of potent irreversible T790M EGFR inhibitors.
Keywords: mutant EGFR, NCI database, virtual screening, drug resistant, quantum chemical calculation, pharmacophore modeling
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