A Review of Target Identification Strategies for Drug Discovery: from Database to Machine-Based Methods

Abstract

Abstract In recent years, target identification has become more efficient than before, and it helped to discover huge amounts of drugs for various diseases. The mystery buried behind was the methods that developed in recent years utilized in the target identification. The advances and research status of database, biological assay and machine-based method in recent years for target identification would be integrated by this review. The various databases help scientists to find information about target property, chemical property or on genome level. The biological assay, such as RNAi, RNA sequencing, DNA microarray, and Gal4/UAS system, is commonly used to identify the target in recent years. The machine-based strategies, such as random forest algorithm and Support Vector Machine (SVM) algorithm, could help scientists identify the target and find compound activity more efficiently. Among the three methods mentioned above, the machine-based methods could have higher efficiency and lower cost while maintaining higher accuracy. Despite the promising properties of machine-based methods, the combination use of biological assay would still be necessary. With wider application of more efficient strategies, target identification, as well as drug discovery process, would gain more rapid development.