The aim of this study is to find a potential inhibitor for all of SARS CoV 2 resolved proteins. To achieve this, I extracted all of the binding sites of these resolve structures, then used a pocket similarity approach to find potential inhibitors from approved drugs followed by docking of these drugs as a confirmation step. Many of the in silico repurposing studies use docking methods [3] , and if the author have access to more computational power a Molecular Dynamic will follow to conform his results [7] , but if you think about it this is not quite a drug repurposing method, because what a docking algorithm really answers is what is the best conformation of this drug that fit into this protein? and in many cases, this drug happens to be a complex compound with many atoms and rotatable bonds that gave the compound enormous number of conformations and the probability of one of these confirmations to have a good fit is therefore higher. The significance of pocket similarity is that similar pocket will have similar conformational changes after ligand binding. This ensures the same effect of the drug on the predicted similar pocket. Up to the author's knowledge, this is the first study that uses pocket similarity to identify potential drugs for COVID 19, but it has been done before on Tuberculosis(not exactly the same method) .