Dataset Information

Macrocyclization of Quinazoline-Based EGFR Inhibitors Leads to Exclusive Mutant Selectivity for EGFR L858R and Del19.

ABSTRACT: Activating mutations in the epidermal growth factor receptor (EGFR) are frequent oncogenic drivers of non-small-cell lung cancer (NSCLC). The most frequent alterations in EGFR are short in-frame deletions in exon 19 (Del19) and the missense mutation L858R, which both lead to increased activity and sensitization of NSCLC to EGFR inhibition. The first approved EGFR inhibitors used for first-line treatment of NSCLC, gefitinib and erlotinib, are quinazoline-based. However, both inhibitors have several known off-targets, and they also potently inhibit wild-type (WT) EGFR, resulting in side effects. Here, we applied a macrocyclic strategy on a quinazoline-based scaffold as a proof-of-concept study with the goal of increasing kinome-wide selectivity of this privileged inhibitor scaffold. Kinome-wide screens and SAR studies yielded 3f, a potent inhibitor for the most common EGFR mutation (EGFR Del19: 119 nM) with selectivity against the WT receptor (EGFR: >10 μM) and the kinome.

SUBMITTER: Amrhein JA

PROVIDER: S-EPMC10410606 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature

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Macrocyclization of Quinazoline-Based EGFR Inhibitors Leads to Exclusive Mutant Selectivity for EGFR L858R and Del19.

Amrhein Jennifer A JA Beyett Tyler S TS Feng William W WW Krämer Andreas A Weckesser Janik J Schaeffner Ilse K IK Rana Jaimin K JK Jänne Pasi A PA Eck Michael J MJ Knapp Stefan S Hanke Thomas T

Journal of medicinal chemistry 20221116 23

Activating mutations in the epidermal growth factor receptor (EGFR) are frequent oncogenic drivers of non-small-cell lung cancer (NSCLC). The most frequent alterations in EGFR are short in-frame deletions in exon 19 (Del19) and the missense mutation L858R, which both lead to increased activity and sensitization of NSCLC to EGFR inhibition. The first approved EGFR inhibitors used for first-line treatment of NSCLC, gefitinib and erlotinib, are quinazoline-based. However, both inhibitors have sever ...[more]

PMID: 36384036

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Project description:Overexpression of EGFR is responsible for causing a number of cancers, including lung cancer as it activates various downstream signaling pathways. Thus, it is important to control EGFR function in order to treat the cancer patients. It is well established that inhibiting ATP binding within the EGFR kinase domain regulates its function. The existing quinazoline derivative based drugs used for treating lung cancer that inhibits the wild type of EGFR. In this study, we have made a systematic attempt to develop QSAR models for designing quinazoline derivatives that could inhibit wild EGFR and imidazothiazoles/pyrazolopyrimidines derivatives against mutant EGFR. In this study, three types of prediction methods have been developed to design inhibitors against EGFR (wild, mutant and both). First, we developed models for predicting inhibitors against wild type EGFR by training and testing on dataset containing 128 quinazoline based inhibitors. This dataset was divided into two subsets called wild_train and wild_valid containing 103 and 25 inhibitors respectively. The models were trained and tested on wild_train dataset while performance was evaluated on the wild_valid called validation dataset. We achieved a maximum correlation between predicted and experimentally determined inhibition (IC50) of 0.90 on validation dataset. Secondly, we developed models for predicting inhibitors against mutant EGFR (L858R) on mutant_train, and mutant_valid dataset and achieved a maximum correlation between 0.834 to 0.850 on these datasets. Finally, an integrated hybrid model has been developed on a dataset containing wild and mutant inhibitors and got maximum correlation between 0.761 to 0.850 on different datasets. In order to promote open source drug discovery, we developed a webserver for designing inhibitors against wild and mutant EGFR along with providing standalone (http://osddlinux.osdd.net/) and Galaxy (http://osddlinux.osdd.net:8001) version of software. We hope our webserver (http://crdd.osdd.net/oscadd/ntegfr/) will play a vital role in designing new anticancer drugs.

Dataset Information

Macrocyclization of Quinazoline-Based EGFR Inhibitors Leads to Exclusive Mutant Selectivity for EGFR L858R and Del19.

Publications

Macrocyclization of Quinazoline-Based EGFR Inhibitors Leads to Exclusive Mutant Selectivity for EGFR L858R and Del19.

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