The impact of autophagy on cancer treatment and its corresponding responsiveness has galvanized the scientific community to develop novel inhibitors for cancer treatment. Importantly, the discovery of inhibitors that targets the early phase of autophagy was identified as a beneficial choice. Despite the number of research in recent years, screening of the DrugBank repository (9591 molecules) for the Vacuolar protein sorting 34 (VPS34) has not been reported earlier. Therefore, the present study was designed to identify potential VPS34 antagonists using integrated pharmacophore strategies. Primarily, an energy-based pharmacophore and receptor cavity-based analysis yielded five (DHRRR) and seven featured (AADDHRR) pharmacophore hypotheses respectively, which were utilized for the database screening process. The glide score, the binding free energy, pharmacokinetics and pharmacodynamics properties were examined to narrow down the screened compounds. This analysis yielded a hit molecule, DB03916 that exhibited a better docking score, higher binding affinity and better drug-like properties in contrast to the reference compound that suffers from a toxicity property. Importantly, the result was validated using a 50 ns molecular dynamics simulation study. Overall, we conclude that the identified hit molecule DB03916 is believed to serve as a prospective antagonist against VPS34 for cancer treatment.
Keywords: Free energy landscape; MM-GBSA; Molecular dynamics simulation; Principal component analysis; Vacuolar protein sorting 34.