Peroxisome Proliferator-Activated Receptor Gamma encoded by PPARG gene is also known as type II nuclear receptor in humans plays a significant role in regulating the glucose metabolism, adipocyte differentiation and serves as a lipid sensor. This has been implicated in the pathology of various diseases like obesity, diabetes, atherosclerosis, and cancer. In search of drugs that uses PPAR gamma as a therapeutic target for its inhibition: Insilico CADD approaches has been widely used in this aspect to understand the intrinsic molecular aspects and their interaction with the chemicals. In-silico based virtual screening helps in identification of optimum molecule among the large dataset to elucidate the effects on a particular target through binding interaction and can be used for further experimentations. In the present study, two PPAR gamma/antagonists GW9662 and T0070907 were selected for this study as they serves as potent therapeutics to minimize the effects of PPAR gamma in chronic diseases. A set of structural analogs of GW9662 and T0070907 were screened from ZINC public database. Ligand based screening is followed by 80% similarity search, Lipinski filter, Pharmacophore based and toxicity based screening. Structure based virtual screening follows the output and final molecular docking using iGemdock and Autodock explained the binding affinity and pharmacological interactions. The results between the GW9662, T0070907 and screened structural analogs show better binding affinity with respect to the former one with similar pharmacological interactions