SynProtX: a large-scale proteomics-based deep learning model for predicting synergistic anticancer drug combinations.

ABSTRACT:

Motivation

Drug combination therapy plays a pivotal role in addressing the molecular heterogeneity of cancer, improving treatment efficacy, minimizing resistance, and reducing toxicity. Deep learning approaches have significantly advanced drug combination discovery by addressing the limitations of conventional laboratory experiments, which are time-consuming and costly. While most existing models rely on the molecular structure of drugs and gene expression data, incorporating protein-level expression provides a more accurate representation of cellular behavior and drug responses. In this study, we introduce SynProtX, an enhanced deep learning model that explicitly integrates large-scale proteomics with deep neural networks (DNNs) and the molecular structure of drugs with graph neur

SUBMITTER: Boonyarit B 

PROVIDER: S-EPMC12343095 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature