Drug-Target Interactions Prediction at Scale: The Komet Algorithm with the LCIdb Dataset.

ABSTRACT: Drug-target interactions (DTIs) prediction algorithms are used at various stages of the drug discovery process. In this context, specific problems such as deorphanization of a new therapeutic target or target identification of a drug candidate arising from phenotypic screens require large-scale predictions across the protein and molecule spaces. DTI prediction heavily relies on supervised learning algorithms that use known DTIs to learn associations between molecule and protein features, allowing for the prediction of new interactions based on learned patterns. The algorithms must be broadly applicable to enable reliable predictions, even in regions of the protein or molecule spaces where data may be scarce. In this paper, we address two key challenges to fulfill these goals: building larg

SUBMITTER: Guichaoua G 

PROVIDER: S-EPMC11423346 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature