Kinome-Wide Virtual Screening by Multi-Task Deep Learning.

ABSTRACT: Deep learning is a machine learning technique to model high-level abstractions in data by utilizing a graph composed of multiple processing layers that experience various linear and non-linear transformations. This technique has been shown to perform well for applications in drug discovery, utilizing structural features of small molecules to predict activity. Here, we report a large-scale study to predict the activity of small molecules across the human kinome-a major family of drug targets, particularly in anti-cancer agents. While small-molecule kinase inhibitors exhibit impressive clinical efficacy in several different diseases, resistance often arises through adaptive kinome reprogramming or subpopulation diversity. Polypharmacology and combination therapies offer potential therapeutic

SUBMITTER: Hu J 

PROVIDER: S-EPMC10932040 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature