Recent applications of deep learning and machine intelligence on in silico drug discovery: methods, tools and databases

• Published in: Briefings in bioinformatics Vol. 20; no. 5; pp. 1878 - 1912
• Main Authors: Rifaioglu, Ahmet Sureyya, Atas, Heval, Martin, Maria Jesus, Cetin-Atalay, Rengul, Atalay, Volkan, Doğan, Tunca
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 27.09.2019; Oxford Publishing Limited (England)
• Subjects: Bioassays; Biological activity; Computer applications; Computer Simulation; Computer vision; Database Management Systems; Deep Learning; Drug development; Drug Discovery; Drug interaction; Drug screening; Drugs; Learning algorithms; Machine learning; Natural language processing; Performance prediction; Prediction models; Proteins; Review; Screening; Standard data; deep learning; compound and bioactivity databases; virtual screening; gold-standard data sets; machine learning; ligand-based VS and proteochemometric modelling; drug-target interactions

Abstract The identification of interactions between drugs/compounds and their targets is crucial for the development of new drugs. In vitro screening experiments (i.e. bioassays) are frequently used for this purpose; however, experimental approaches are insufficient to explore novel drug-target inte...