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Applying Cheminformatics to Develop a Structure Searchable Database of Analytical Methods

Applying Cheminformatics to Develop a Structure Searchable Database of Analytical Methods

Published on: June 6, 2025

ATDB: a uni-database platform for animal toxins.

Quan-Yuan He¹, Quan-Ze He, Xing-Can Deng

¹The Key Laboratory of Protein Chemistry and Developmental Biology of Ministry of Education, College of Life Sciences, Hunan Normal University, Changsha 410081, P. R. China.

Nucleic Acids Research

|October 16, 2007

Summary

A new Animal Toxin Database (ATDB) standardizes venom toxin data. This resource, with over 3235 toxins and a novel Toxin Ontology, facilitates research and data sharing in toxicology.

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Area of Science:

Biochemistry
Pharmacology
Zoology

Background:

Venomous animals utilize diverse toxins for predation and defense, offering significant research value.
Toxinomics research has identified numerous novel toxins, but data management is fragmented.
Existing toxin databases lack comprehensive data access and consistent functional classification.

Purpose of the Study:

To develop a centralized, standardized database for animal toxins.
To create a novel ontology for consistent toxin annotation and classification.
To provide a user-friendly platform for accessing and querying toxin data.

Main Methods:

Compiled over 3235 animal toxins from UniProtKB/Swiss-Prot, TrEMBL, and literature.
Developed a new Toxin Ontology with 745 terms across four spaces.
Manually assigned over 8423 Toxin Ontology terms to 2132 toxins by biologists.

Main Results:

Established the Animal Toxin Database (ATDB) with extensive toxin data.
Implemented a standardized annotation system using the Toxin Ontology.
Created a web interface for efficient data querying and access.

Conclusions:

The ATDB provides a valuable, standardized resource for the scientific community.
The Toxin Ontology facilitates consistent data description and comparison.
The ATDB and its interface promote advancements in toxin research and drug discovery.