ArticleJournal of integrative plant biology2026
AlkaPlorer: A database-driven explorer for natural alkaloids and derivatives.
Article in Journal of integrative plant biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- AlkaPlorer: A database-driven explorer for natural alkaloids and derivatives.Journal of integrative plant biology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.