Sequence-Based Protein-Protein Interaction Prediction and Its Applications in Drug Discovery.

ABSTRACT: Aberrant protein-protein interactions (PPIs) underpin a plethora of human diseases, and disruption of these harmful interactions constitute a compelling treatment avenue. Advances in computational approaches to PPI prediction have closely followed progress in deep learning and natural language processing. In this review, we outline the state-of-the-art methods for sequence-based PPI prediction and explore their impact on target identification and drug discovery. We begin with an overview of commonly used training data sources and techniques used to curate these data to enhance the quality of the training set. Subsequently, we survey various PPI predictor types, including traditional similarity-based approaches, and deep learning-based approaches with a particular emphasis on transformer ar

SUBMITTER: Charih F 

PROVIDER: S-EPMC12468386 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature