Artificial intelligence for drug discovery: Resources, methods, and applications.

ABSTRACT: Conventional wet laboratory testing, validations, and synthetic procedures are costly and time-consuming for drug discovery. Advancements in artificial intelligence (AI) techniques have revolutionized their applications to drug discovery. Combined with accessible data resources, AI techniques are changing the landscape of drug discovery. In the past decades, a series of AI-based models have been developed for various steps of drug discovery. These models have been used as complements of conventional experiments and have accelerated the drug discovery process. In this review, we first introduced the widely used data resources in drug discovery, such as ChEMBL and DrugBank, followed by the molecular representation schemes that convert data into computer-readable formats. Meanwhile, we summar

SUBMITTER: Chen W 

PROVIDER: S-EPMC10009646 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature