Abstract: The prediction of ADMET properties is critical in the drug development process because they account for approximately 60% of all drug failures in clinical trials. Whereas in the past, ADME methods were used at the end of the drug development process, it is now being used in the early stages of drug development to remove molecules with bad ADME properties from the pipeline and save money on R & D costs. Many drug targets have been identified in fighting against different types of cancer. Inhibition of cell cycle is strategy used in anti-cancer research. Cyclin-dependent kinases have been identified as potential drug targets. The aim is to find a molecule that inhibits CDK, a protein that controls cell cycle progression. Many drug molecules fail during clinical trials, and ADME analysis is one of the most important steps in the process. These molecules were tested for ADME properties such as blood brain barrier, GI absorption, aqueous solubility, and skin permeability. The aim of various in-silico methods is to predict ADME from molecular structure. SwissADME is a tool that focuses on a particular property, and it is one of the most useful computational methods for determining pharmacokinetic properties of small molecules. ADME screening was carried out to know efficacy of molecules before proceeding to in-vivo or in-vitro assays.
