Computational docking is used for optimizing known drugs and for defining new binders by simulating their
binding mode and affinity. AutoDock tools have been widely cited as necessary tools in structure-based drug
design. These methods are rapid enough to declare virtual screening of ligand libraries. We selected a target
involved in transferases enzyme class and provided a fully reproducible docking protocol. This paper will show
how docking techniques would be an important asset to identify new ligands interactions with transferases. We
used Non-3D structures of chosen transferases and built models for the proteins in trying to find putative
compounds against them. Five proteins have structural data available in uniprot with varying degrees of structural
coverage. Using homology-based methods; structural coverage of these proteins and built models for them through
Swiss model. Designed ligands are tested by Autodock vina to study the interacting sites with the proteins. We
have predicted putative drug like molecules using molecular docking that could bind to transferases. The stability
of a few of our top docked protein-inhibitor complexes was evaluated based on molecular docking simulations.
Our proposed inhibitors should potentially bind to enzyme proteins and hinder their function.