Leveraging large language models for literature-driven prioritization of protein binding pockets
The developed benchmark dataset and methodology are freely available at the GitHub repository (https://github.com/receptor-ai/LLM-benchmark-dataset) and Zenodo (DOI: 10.5281/zenodo.15798647).
Authors
- Zakhar Ostrovsky (ORCID: https://orcid.org/0009-0003-4644-3587)
- Vladyslav Husak
- Roman Stratiichuk (ORCID: https://orcid.org/0009-0001-6632-7642)
- Ihor Koleiev (ORCID: https://orcid.org/0009-0001-4620-3175)
- Taras Voitsitskyi
- Наталія Анатоліївна Шевчук
- Volodymyr G. Bdzhola (ORCID: https://orcid.org/0000-0003-0315-450X)
- Sergiy A. Starosyla (ORCID: https://orcid.org/0000-0002-5103-0635)
- Алан Нафієв (ORCID: https://orcid.org/0009-0004-8604-377X)
- Semen Yesylevskyy (ORCID: https://orcid.org/0000-0002-6748-8931)
- Mykola Melnychenko
Institutions
- National Academy of Sciences of Ukraine (UA)
- Taras Shevchenko National University of Kyiv (UA)
- University of Trento (IT)
- Web Science Trust (GB)
- National Confidential Enquiry into Patient Outcome and Death (GB)
- Institute of Organic Chemistry (PL)
- London Borough of Hackney (GB)
- Czech Academy of Sciences, Institute of Organic Chemistry and Biochemistry (CZ)
- Institute of Molecular Biology and Genetics (UA)
- Palacký University Olomouc (CZ)
- Institute of Physics (UA)
Publication Details
- Journal
- Bioinformatics
- Published
- 2025-08-01
- DOI
- https://doi.org/10.1093/bioinformatics/btaf449
- Citations
- 1
- Primary Topic
- Biomedical Text Mining and Ontologies
- Type
- article
- Field-Weighted Citation Impact
- 0.81
Funders
- European Commission