Identification of pan-kinase-family inhibitors using graph convolutional networks to reveal family-sensitive pre-moieties.

ABSTRACT:

Background

Human protein kinases, the key players in phosphoryl signal transduction, have been actively investigated as drug targets for complex diseases such as cancer, immune disorders, and Alzheimer's disease, with more than 60 successful drugs developed in the past 30 years. However, many of these single-kinase inhibitors show low efficacy and drug resistance has become an issue. Owing to the occurrence of highly conserved catalytic sites and shared signaling pathways within a kinase family, multi-target kinase inhibitors have attracted attention.

Results

To design and identify such pan-kinase family inhibitors (PKFIs), we proposed PKFI sets for eight families using 200,000 experimental bioactivity data points and applied a graph convolutional network (GCN) to build clas

SUBMITTER: Lin XY 

PROVIDER: S-EPMC9214975 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature