In-silico studies for the development of novel RET inhibitors for cancer treatment

Abstract

The RET (Rearranged during transfection) is a viable target for thyroid cancer and non-small cell lung cancer. For RET inhibition, a variety of heterocyclic fused ring systems have been evaluated. In this context, pyrrolo [2, 3-d] pyrimidine analogues have been proven to be a potential inhibitor of the target in the treatment of various cancers. In the present study, we have taken an initiative to model a data set of compounds from the literature and performed in-silico studies. As essential features required for the activity, the pharmacophore modeling generated a five-point pharmacophore hypothesis (DDRRR). The AB-QSAR wizard was utilized for 3D-QSAR analysis and generated significant parameters for the high predictive ability of the model (Q2 = 0.9093, R2 = 0.9621) with minimum errors (SD = 0.3043, RMSE =0.18). The virtual screening studies have been performed through the ZINC database using DDRRR_1 as a template and developed 4800 drug like molecules. These molecules further proceeded through different docking methodologies and screened four hit compounds: ZINC00198134, ZINC32124485, ZINC11856422 and ZINC41121323 showed the best docked poses with docking scores. The ADME parameters showed an excellent pharmacokinetic profile for the selected compounds that may be used further for optimization. The study results may be useful to the researchers for the development of novel RET inhibitors with improved therapeutic efficacy towards cancer treatment.