In Silico Discovery of mTOR Inhibitors as Potential Therapeutics for Feline Hypertrophic Cardiomyopathy.

CONTEXT: Feline Hypertrophic Cardiomyopathy (HCM) is a significant health issue, with a current prevalence of 14.7% in cats. The mammalian target of rapamycin (mTOR) is an atypical serine/threonine protein kinase system that also participates in the control of structural and functional remodeling of the heart in relation to haemodynamic stress and non-hemodynamic stimuli. Here, we sought to discover candidate feline-specific inhibitors of mTOR for the treatment of HCM using an integrated computational pipeline combining homology modeling, virtual screening, and molecular dynamics simulations. Using this pipeline, we screened the DrugBank database and identified 17 candidate compounds that bind significantly better than rapamycin, serving as a control mTOR inhibitor. Both molecular dynamics (MD) simulation and MM/PBSA calculations indicated that the screened compound, dihydro-alpha-ergocryptine, exhibited a higher binding affinity and stability with feline mTOR compared to rapamycin. Moreover, ADMET analysis further demonstrated that the compound had good drug-like properties.
METHODS: Homologous models of feline mTOR were built using publicly available software MODELLER (version 10.5) and the SWISS-MODEL webserver. Homologous templates were used to predict the active binding sites. Structure-based virtual screening of high-affinity small molecule compounds from the DrugBank database was carried out using AutoDock Vina (version 1.2.0). Molecular dynamics (MD) simulations were performed using the GROMACS software version 2021.4. The CHARMM36 all-atom force field parameterised the protein, and the ligand's parameters were taken from the GAFF force field. The simulations were equilibrated under NVT and NPT conditions. During trajectory analysis (RMSD, RMSF, radius of gyration, SASA and hydrogen bonding), the complex stability was evaluated to identify the best potential mTOR inhibitor candidates using OriginPro (version 2024).