Background and Aim: Cancer is a complex collection of dynamic genome mutation which appears in the body with broad changes in the cell surface and tissue. The goal is to attain new methods that with less expense of time and money are able to design more efficient drugs with fewer side effects.

Materials and Methods: Today, the number of small molecules discovered in the treatment of cancer grew considerably because of the availability of strong drug design technologies. With having an access to the human genome project and making a target of genes responsible for cancer using computational modeling, identification and treatment of cancer is possible with less expense of time and cost. Several key parameters that are not attainable in experiments can be computed in four levels of atomic, molecular, microscopic and macroscopic.

Results: Computational modeling in drug design is a valuable measure in the targeted discovery and production of new anticancer drugs. QSAR, docking, and molecular dynamics simulation are among these methods.