Design and identification of novel drug candidates targeting RET: Accurate drug affinity estimation using funnel...

Area of Science:

• Biochemistry and Molecular Biology
• Computational Chemistry
• Pharmacology

Background:

• Rearranged during Transfection (RET) receptor tyrosine kinase (RTK) is crucial for cell growth; mutations drive cancer.
• Existing targeted therapies face limitations due to RET-RTK mutations causing drug resistance.
• Understanding drug resistance mechanisms and identifying novel inhibitors are vital for effective cancer treatment.

Purpose of the Study:

• To design novel anilinoquinazoline derivatives as potential inhibitors of RET-RTK.
• To evaluate the binding affinity and resistance profiles of these derivatives against wild-type and mutant RET proteins.
• To utilize computational approaches for accurate estimation of receptor-ligand binding free energy.

Main Methods:

• Design and synthesis of anilinoquinazoline derivatives.
• Computational approaches, including funnel-metadynamics simulations, to estimate binding free energies.
• Comparison of binding affinities against wild-type and mutant RET proteins with the reference drug vandetanib.

Main Results:

• Derivatives V2, V5, and G5 demonstrated superior binding affinity and resistance against wild and mutant RET proteins compared to vandetanib.
• Funnel-metadynamics simulations yielded absolute binding energy for vandetanib with wild-type RET (-5.95 ± 2.1 kcal mol⁻¹) consistent with experimental data (-8.75 kcal mol⁻¹).
• The potent derivative V2 exhibited strong binding affinity with wild-type RET (-7.2 ± 2.2 kcal mol⁻¹).

Conclusions:

• Anilinoquinazoline derivatives V2, V5, and G5 are potent inhibitors of RET-RTK, including resistant forms.
• Derivative V2 shows significant promise as a novel RET inhibitor for targeted cancer therapy.
• Computational methods accurately predict binding affinities, aiding in the development of next-generation TK inhibitors.