Structure-Based Computational Approach in Search of the Potent Molecules Targeting Phosphoglycerate Dehydrogenase (PHGDH) Enzyme for Cancer Treatment

This work aims to target phosphoglycerate dehydrogenase (PHGDH), a promising druggable target, that is overexpressed in various types of cancer. A structure-based approach was employed to identify novel inhibitors against the enzyme. A common five-feature pharmacophore model (RRHDA) was constructed using the active site co-crystalized ligands. These chemical features were responsible for showing inhibition. The generated models were subsequently subjected to the validation method using a test set, receiver-operator characteristic analysis, enrichment factor, and G & uuml;ner-Henry studies. The validated models were subjected to the screening of a dataset of natural compounds. The screened unique natural compounds (1795) were further selected for the interaction analysis and study of ligand binding affinity considering the effect of the hydrogen bonding and desolvation and hydrophobic interactions contribution to the binding. The natural compounds which exhibited good ligand binding efficiency were selected and further subjected to pharmacokinetics and pharmacodynamic study. The natural compounds which exhibited good ligand binding efficiency were selected and further subjected to pharmacokinetics and pharmacodynamic study. The finalized complexes were selected for the simulation studies and MM/PBSA-based binding free energy calculations. This study expands the possibilities for the development of shortlisted molecules as novel anti-cancer compounds.