Insilico methods are the leading-edge potential tools for assessing ADME properties. These Machine learning methods have ability in allocating diverse structures and complex mechanisms, are appropriate for prediction of biological activity and therapeutic potency. Insilico is simply; Latin- in silicon (i.e. Performed using computer simulation). These newer Insilico approaches has led to easier and broader discovery of new drug , which in turn affect the success and time for carrying out Clinical trials. The In silico techniques like molecular docking, QSAR, Virtual High throughput screening, Pharmacophore, Fragment based screening are explained in this review. Efforts have been directed at broadening of application scopes and improvement of predictive performance of these methods. Here the progresses and performances as well as challenges of scrutinizing Insilico method by molecular docking of Tea leaves extracted as anti-malarial (Gallocatecin) in correlation with PLANTS® software has been illustrated as a case study.