Litcius/Paper detail

Artificial Intelligence in Drug Discovery

Takeshi Fujiwara, Mayumi Kamada, Yasushi Okuno

2020RSC drug discovery/RSC drug discovery series23 citationsDOI

Abstract

According to the increase of data generated from analytical instruments, application of artificial intelligence(AI)technology in medical field is indispensable. In particular, practical application of AI technology is strongly required in "genomic medicine" and "genomic drug discovery" that conduct medical practice and novel drug development based on individual genomic information. In our laboratory, we have been developing a database to integrate genome data and clinical information obtained by clinical genome analysis and a computational support system for clinical interpretation of variants using AI. In addition, with the aim of creating new therapeutic targets in genomic drug discovery, we have been also working on the development of a binding affinity prediction system for mutated proteins and drugs by molecular dynamics simulation using supercomputer "Kei". We also have tackled for problems in a drug virtual screening. Our developed AI technology has successfully generated virtual compound library, and deep learning method has enabled us to predict interaction between compound and target protein.

Topics & Concepts

Drug discoveryComputer scienceVirtual screeningComputational biologyGenomePrecision medicineDrug developmentArtificial intelligenceData scienceGenomic informationDrugBioinformaticsBiologyGeneGeneticsPharmacologyGenetics, Bioinformatics, and Biomedical ResearchComputational Drug Discovery MethodsBioinformatics and Genomic Networks