Identify potential drug candidates within a high-quality compound search space.

ABSTRACT: The identification of potential effective drug candidates is a fundamental step in new drug discovery, with profound implications for pharmaceutical research and the healthcare sector. While many computational methods have been developed for such predictions and have yielded promising results, two challenges persist: (i) The cold start problem of new drugs, which increases the difficulty of prediction due to lack of historical data or prior knowledge. (ii) The vastness of the compound search space for potential drug candidates. In this study, we present a promising method that not only enhances the accuracy of identifying potential novel drug candidates but also refines the search space. Drawing inspiration from solutions to the cold start problem in recommender systems, we apply 'learning

SUBMITTER: Ru X 

PROVIDER: S-EPMC11758506 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature