Collector

Collector extracts compound series annotated with experimental bioactivity data to generate datasets for quantitative structure-activity relationship (QSAR) modeling.


Key Features:

  • Data extraction from OPS: Uses the Open Pharmacological Space (OPS) ontologies from the Open PHACTS Discovery platform to expand target queries using all known synonyms and retrieve compounds annotated with bioactivity data from multiple sources.
  • Filtering and summarization: Filters results to retain drug-like compounds and summarizes multiple bioactivity measurements to assign a single value per compound suitable for QSAR modeling.
  • Local storage and traceability: Facilitates local storage of extracted datasets to preserve traceability and auditability of source annotations.
  • Applied use in research: Has been used to develop models for toxicity endpoints within the eTOX project.

Scientific Applications:

  • QSAR modeling: Provides compound–bioactivity datasets formatted for quantitative structure-activity relationship (QSAR) model development.
  • Property prediction and lead optimization: Supplies annotated bioactivity data to support prediction of compound properties and lead optimization efforts.
  • Toxicity modeling (eTOX): Enables development of toxicity endpoint models as demonstrated in the eTOX project.

Methodology:

Accepts a valid biological target name, employs OPS ontologies to expand the search using synonyms, extracts bioactivity annotations from multiple sources, applies filtering for drug-like compounds, summarizes bioactivities to a single value per compound, and stores the resulting dataset locally for traceability.

Topics

Details

License:
GPL-3.0
Maturity:
Mature
Cost:
Free of charge
Tool Type:
api, desktop application, web application
Operating Systems:
Linux, Windows, Mac
Programming Languages:
Java
Added:
7/7/2019
Last Updated:
11/24/2024

Operations

Publications

López-Massaguer O, Sanz F, Pastor M. An automated tool for obtaining QSAR-ready series of compounds using semantic web technologies. Bioinformatics. 2017;34(1):131-133. doi:10.1093/bioinformatics/btx566. PMID:28968713.

Documentation

Downloads

Links