A programmatic tool (hosted, maintained and supported at the GitHub repository workflow-for-coronavirus) was used to screen the PubChem compound library for compounds with a good ML-based predicted activity against the papain-like protease from SARS-CoV2 virus. Due to the dynamic real-time approach of the workflow, at the instant we ran the program, data availability of PubChem provided us with experimental activity data of 111 compounds reported to be active against any of the domains of nsp3. The tool retrieved molecular descriptors (Molecular Weight, Heavy Atom Count, XLOGP, Complexity, Hydrogen bond Acceptor Count, MonoisotopicMass, RotatableBondCount and Topological Surface Area) for these compounds and then implemented an AutoQSAR algorithm for drug lead generation.