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Published on: June 21, 2018
An Integrated Text Mining Approach for Discovering Pharmacological Effects, Drug Combinations, and Repurposing
Nadezhda Yu Biziukova1, Polina I Savosina1, Dmitry S Druzhilovskiy1
1Institute of Biomedical Chemistry, 10, Pogodinskaya Street, 119121 Moscow, Russia.
This study introduces a text-mining framework to automatically extract and structure data on small-molecule drug activities from biomedical literature. It reveals new therapeutic uses and mechanisms for angiotensin-converting enzyme (ACE) inhibitors, aiding drug repurposing.
Area of Science:
- Biomedical Informatics
- Pharmacology
- Computational Biology
Background:
- Biomedical literature contains vast data on small-molecule therapeutics, but systematic knowledge extraction is challenging.
- Integrating information on drug effects, mechanisms, and repurposing potential requires advanced methods.
Purpose of the Study:
- To develop an integrated text-mining framework for automated extraction and structured representation of biological activities of low-molecular-weight compounds.
- To exemplify the framework using angiotensin-converting enzyme (ACE) inhibitors.
Main Methods:
- Assembled a corpus of over 20,000 PubMed titles/abstracts on ACE inhibitors.
- Utilized named entity recognition (NER) for chemical compounds, proteins/genes, and diseases.
- Employed rule-based sentence-level association extraction and normalized entities via PubChem, UniProt, and Human Disease Ontology.
Main Results:
- Extracted approximately 22,000 unique, normalized associations (drug-target, drug-disease, drug-drug).
- Confirmed known therapeutic effects and drug combinations.
- Identified underexplored activities of ACE inhibitors (e.g., antineoplastic, antifibrotic, neuropsychiatric) and novel mechanistic links.
Conclusions:
- Automated literature mining can significantly advance systematic knowledge integration in pharmacology.
- The framework supports data-driven hypothesis generation for drug repurposing and safety evaluation.
- Highlights the potential of ACE inhibitors beyond cardiovascular applications.
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