虚拟筛选
药品
精密医学
计算生物学
基因组
计算机科学
基因组信息
数据科学
药物发现
人工智能
药物开发
生物信息学
生物
基因
遗传学
药理学
作者
Takeshi Fujiwara,Mayumi Kamada,Yasushi Okuno
出处
期刊:RSC drug discovery series
日期:2020-01-01
卷期号:45 (4): 593-596
被引量:23
标识
DOI:10.1039/9781788016841
摘要
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.
科研通智能强力驱动
Strongly Powered by AbleSci AI