Exploring kinase family inhibitors and their moiety preferences using deep SHapley additive exPlanations.

ABSTRACT:

Background

While it has been known that human protein kinases mediate most signal transductions in cells and their dysfunction can result in inflammatory diseases and cancers, it remains a challenge to find effective kinase inhibitor as drugs for these diseases. One major challenge is the compensatory upregulation of related kinases following some critical kinase inhibition. To circumvent the compensatory effect, it is desirable to have inhibitors that inhibit all the kinases belonging to the same family, instead of targeting only a few kinases. However, finding inhibitors that target a whole kinase family is laborious and time consuming in wet lab.

Results

In this paper, we present a computational approach taking advantage of interpretable deep learning models to address th

SUBMITTER: Fan YW 

PROVIDER: S-EPMC9208089 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature