Targeting tribbles homolog 3 (TRIB3) protein against type 2 diabetes for the identification of potential inhibitors by in silico screening

Tribbles homolog 3 (TRIB3) protein is inhibiting the insulin signaling by directly binding to the Akt/PKB leading to insulin resistance in the pancreas causing type 2 diabetes mellitus. Hence, TRIB3 protein is considered as a possible drug target for the new lead identification against type 2 diabetes. In the present study, the homology model of TRIB3 protein was generated to explore its biochemical function and molecular interactions in the new lead identification. The energy minimization of TRIB3 protein was carried out and evaluated by validation protocols for structure reliability. The druggable binding site of TRIB3 protein was identified for the virtual screening and molecular docking studies. The Asinex-fragments library of 22634 small molecules was docked at TRIB3 active site using the Glide module to identify new chemical entities. A total of 9 molecules were identified as final hits from virtual screening and their potency was ranked using Glide score, Glide energies, and residues interactions. The 6 prioritized lead molecules were further optimized using AutoDock, Prime MM/GBSA, and percentage of human oral absorption for the identification of potential leads. The molecules L2, L5, and L6 are identified as lead inhibitors and are showing consistent interactions with key residues Glu194 and Lys196 of TRIB3 protein. The identified potential leads were analyzed by ADME properties for their drug likeness and HergIC50 values are predicted for the prevention of preclinical failures. The present work sheds light on the identification of the best lead molecules against TRIB3 protein and offers a route to design as novel potential drug candidates for T2DM. [Display omitted] •The present work is aimed to identify the potential leads against TRIB3 protein for type 2 diabetes using in silico models.•The homology model of TRIB3 protein was built and its binding site was identified for docking studies.•Virtual screening was carried out using the Asinex bio-design library of small molecules.•AutoDock and Prime MM/GBSA, and ADME approaches were also used to optimize the lead molecules.•L2, L5, and L6 leads were identified as final potential inhibitors against TRIB3 for type 2 diabetes mellitus.