Structure-Based Identification of Natural Compounds as Potential RET-Kinase Inhibitors for Therapeutic Targeting of Neurodegenerative Diseases

Abstract

Background: Tyrosine-protein kinase receptor Ret (RET), a proto-oncogene, is considered as an attractive drug target for cancer and neurodegenerative diseases, including Alzheimer's disease (AD).

Objective: We aimed to identify potential inhibitors of RET kinase among natural compounds present in the ZINC database.

Methods: A multistep structure-based virtual screening approach was used to identify potential RET kinase inhibitors based on their binding affinities, docking scores, and interactions with the biologically important residues of RET kinase. To further validate the potential of these compounds as therapeutic leads, molecular dynamics (MD) simulations for 100 ns were carried out and subsequently evaluated the stability, conformational changes, and interaction mechanism of RET in-complex with the elucidated compounds.

Results: Two natural compounds, ZINC02092851 and ZINC02726682, demonstrated high affinity, specificity for the ATP-binding pocket of RET and drug-likeness properties. The MD simulation outputs indicated that the binding of both compounds stabilizes the RET structure and leads to fewer conformational changes.

Conclusions: The findings suggest that ZINC02092851 and ZINC02726682 may be potential inhibitors for RET, offering valuable leads for drug development against RET-associated diseases. Our study provides a promising avenue for developing new therapeutic strategies against complex diseases, including AD. Identifying natural compounds with high affinity and specificity for RET provides a valuable starting point for developing novel drugs that could help combat these debilitating diseases.

Keywords: Alzheimer’s disease; computer-aided drug design; molecular dynamics simulations; natural compounds; proto-oncogene tyrosine-protein kinase receptor Ret; virtual screening.