Structure-activity Relationship Study on Therapeutically Relevant EGFR Double Mutant Inhibitors

Area of Science:

• Medicinal Chemistry
• Computational Chemistry
• Pharmacology

Background:

• Epidermal growth factor receptor (EGFR) is a key target in cancer therapy.
• First-generation EGFR inhibitors are effective against the L858R mutation in non-small cell lung cancer (NSCLC).
• Secondary T790M mutations confer resistance to existing EGFR inhibitors, leading to disease relapse.

Purpose of the Study:

• To develop novel reversible inhibitors targeting the T790M/L858R (TMLR) double mutant EGFR.
• To overcome acquired resistance to EGFR tyrosine kinase inhibitors in NSCLC.

Main Methods:

• Utilized Fragment-based Quantitative Structure-Activity Relationship (G-QSAR) modeling.
• Employed partial least squares regression with stepwise forward-backward variable selection.
• Analyzed amino-pyrimidine derivatives for biological activity against the TMLR mutant enzyme.

Main Results:

• Developed robust and predictive G-QSAR models (r² = 0.86, q² = 0.81, predicted r² = 0.62).
• Identified key molecular descriptors for enhancing bioactivity: increasing saturated carbon and retention index at R1, lipophilic character at R2, and polarizability at R3.
• Highlighted the importance of descriptor interactions (Sum(R1-SsssCHcount, R2-slogp) and Mult(R1-chi3, R3-polarizabilityAHC)) for inhibitory potency.

Conclusions:

• The study provides site-specific insights into chemical group variations influencing TMLR inhibitor potency.
• These findings can guide the rational design of new amino-pyrimidine derivatives with improved anti-cancer activity.
• The developed models offer a valuable tool for designing next-generation EGFR inhibitors.