Identification of potential Aurora kinase-C protein inhibitors: an amalgamation of energy minimization, virtual screening, prime MMGBSA and AutoDock.

Genomic instability is a trademark of cancer evolution, there is still a wide necessity to discover safe and effective anti-cancer drugs. Aurora kinase-C protein is a member of the Aurora kinase family involved in regulating mitosis phases of the cell cycle. Aurora kinase-C protein has an aberrant expression at spindle assembly checkpoint leading to human cervical cancer and colorectal cancer. Knowledge of 3D structure of the protein is vital for identify possible inhibitors. In the present study, 3D structure prediction of Aurora kinase-C protein is taken up by using comparative homology modeling techniques and minimized by NAMD-VMD Software. The quality of modeled protein was validated using ProSA and Ramachandran plot. Probable binding site in protein was identified from SiteMap and molecular docking based virtual screening was carried out using Asinex database to identify lead molecules. The obtained lead molecules were further optimized using PrimeMM-GBSA and AutoDock. ADME properties of the leads were calculated to ascertain the drug-like properties at lead molecules.Communicated by Ramaswamy H. Sarma.

Structure-based identification of potential novel inhibitors targeting FAM3B (PANDER) causing type 2 diabetes mellitus through virtual screening.

Type 2 diabetes mellitus is a metabolic disorder that requires potent therapeutic approaches. The FAM3B is a cytokine-like protein also referred to as PANcreatic-DERrived factor (PANDER) which mainly exists in pancreatic islets. In the process of identifying potential inhibitors with the aid of structure-based method PANDER protein is identified as a novel therapeutic target against type 2 diabetes mellitus as it involved in the development of type 2 diabetes by negatively regulating the pancreatic ß-cell function and insulin sensitivity in the liver. In the present study, the 3d model of target protein FAM3B was generated by homology modeling technique using the MODELLER9.9 program. The assessment of the structural stability of the 3d model was established by energy minimization technique. The structural quality was evaluated with standard validating protocols. Binding regions of the target protein has been determined by literature and SiteMap tool. In the current study of research, the FAM3B model was subjected to molecular screening with the Asinex-elite database of 14849 output molecules using the Glide virtual screening module in the Schrodinger suite. The final XP descriptor output of 14 molecules was analyzed and prioritized based on molecular interactions at the FAM3B active site. The docking score, binding free energies (Prime MM/GBSA) and bioavailability were undertaken into the consideration to identify lead inhibitors. The identified lead compounds were checked for ADME properties all falling within the permeable ranges. The analysis of results gave the insight to develop the novel therapeutic strategies against type 2 diabetes mellitus.