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Cited by 4Computational Drug Discovery MethodsProtein Degradation and InhibitorsMachine Learning in Materials Science

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A precise comparison of molecular target prediction methods

Open access
He, Tiantian, Caba, Klaudia, Ballester, Pedro J.·2025·Digital Discovery
DOI 10.1039/d5dd00199d

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Abstract

We compared seven target prediction methods using annotated target–compound interaction and FDA-approved drugs. MolTarPred, using Morgan fingerprints and Tanimoto scores, outperforms others in precision, recall, and MCC for drug repurposing.

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Metadata

Authors
He, T., Caba, K., & Ballester, P. J.
Affiliations
Imperial College London (GB)
Corresponding author
Ballester, Pedro J.
ORCID
Ballester, Pedro J.
Venue
Digital Discovery
Publisher
Royal Society of Chemistry (RSC)
Published
2025
Volume
4
Issue
9
Pages
2548-2558
ISSN
2635-098X (ISSN-L)
DOI
10.1039/d5dd00199d
OpenAlex
W4412885762
Cited by
4
References
2
Citations by year
2026: 2 · 2025: 2
FWCI
2.08
Type
journal article
Language
en
Open access
Licence
Locations
  • Digital Discovery (publishedVersion, cc-by)
  • ChemRxiv (acceptedVersion, cc-by-nc)
Funders
  • Royal Society (Royal Society Wolfson Fellowship)
  • Wolfson Foundation (Royal Society Wolfson Fellowship)
Topics
  • Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Degradation and Inhibitors
  • Physical Sciences › Materials Science › Materials Chemistry › Machine Learning in Materials Science
Keywords
molecular target prediction, drug repurposing, Morgan fingerprints, Tanimoto similarity, method comparison, FDA-approved drugs

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