Machine Learning for Discovery of GSK3β Inhibitors.

ABSTRACT: Alzheimer's disease (AD) is the most common cause of dementia, affecting approximately 35 million people worldwide. The current treatment options for people with AD consist of drugs designed to slow the rate of decline in memory and cognition, but these treatments are not curative, and patients eventually suffer complete cognitive injury. With the substantial amounts of published data on targets for this disease, we proposed that machine learning software could be used to find novel small-molecule treatments that can supplement the AD drugs currently on the market. In order to do this, we used publicly available data in ChEMBL to build and validate Bayesian machine learning models for AD target proteins. The first AD target that we have addressed with this method is the serine-threonine ki

SUBMITTER: Vignaux PA 

PROVIDER: S-EPMC7581251 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature