Improving Drug Discovery Process by Identifying Frequent Toxic Substructures in Chemical Compounds - A Graph Mining Approach
چکیده
Discovery of drug using computer modeling is one of the major challenges in contemporary medicine. Developing new therapeutic drugs is an expensive and time consuming process. Toxicity, caused by substructures that are carcinogenic in nature, is one of the important aspects that need to be explored during drug discovery. The use of in silico methods at an early stage of drug discovery can greatly reduce the time to test the drugs in laboratories. Identifying frequent substructures related to carcinogenic toxicity from a database of chemical compounds can be of great help in reducing the search space during drug discovery process. Graph mining algorithms can be used in order to identify substructures that occur frequently in a given compound database.