MULGA, a unified multi-view graph autoencoder-based approach for identifying drug-protein interaction and drug repositioning.

ABSTRACT:

Motivation

Identifying drug-protein interactions (DPIs) is a critical step in drug repositioning, which allows reuse of approved drugs that may be effective for treating a different disease and thereby alleviates the challenges of new drug development. Despite the fact that a great variety of computational approaches for DPI prediction have been proposed, key challenges, such as extendable and unbiased similarity calculation, heterogeneous information utilization, and reliable negative sample selection, remain to be addressed.

Results

To address these issues, we propose a novel, unified multi-view graph autoencoder framework, termed MULGA, for both DPI and drug repositioning predictions. MULGA is featured by: (i) a multi-view learning technique to effectively learn authentic

SUBMITTER: Ma J 

PROVIDER: S-EPMC10518077 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature