Abstract: Alkaloids, renowned for their pivotal physiological roles in plant defense and chemical medium, constitute a structurally diverse class of bioactive natural products with substantial therapeutic potential in modern drug development. There is currently no dedicated alkaloid database, highlighting an urgent need for such a resource. Here, we present AlkaPlorer (https://alkaplorer.qmclab.com/), the first systematic alkaloid database, which has compiled over 130,000 alkaloids from 12,250 species, with reported activity against 6,583 biological targets. AlkaPlorer not only integrates comprehensive experimentally validated data and computationally predicted properties for each alkaloid, but also establishes standardized notation and associations among various data elements, forming a correlative-type dataset. Extensive chemoinformatic analyses on structural scaffolds, biosynthetic precursors, physicochemical properties, and phylogenetic distributions across plant taxa are performed based on AlkaPlorer, providing new insights into the chemical diversity, structural evolution, and biosynthetic regularity of plant alkaloids. AlkaPlorer enables easy access and efficient retrieval and provides a foundational resource for AI-driven applications in plant metabolism and alkaloid research.

Key words: AI‐driven applications, alkaloids, chemical space, natural products, phytochemistry