In-silico tool for predicting and scanning rheumatoid arthritis-inducing peptides in an antigen
This study presents computational strategies for identifying RA-inducing peptides and demonstrates the advantage of combining motif-based and machine learning approaches for improved performance. The findings are valuable for evaluating the safety of proteins in probiotics, genetically modified foods, and protein-based therapeutics. To facilitate broader use, the best-performing approach has been implemented in RAIpred, a web server and standalone software tool for predicting and scanning RA-inducing peptides, available at https://webs.iiitd.edu.in/raghava/raipred/.
Authors
- Ritu Tomer (ORCID: https://orcid.org/0000-0002-6171-8660)
- Shipra Jain (ORCID: https://orcid.org/0000-0002-7045-5188)
- Gajendra P. S. Raghava (ORCID: https://orcid.org/0000-0002-8902-2876)
- Nisha Bajiya (ORCID: https://orcid.org/0000-0002-5075-5386)
- Pushpendra Singh Gahlot (ORCID: https://orcid.org/0009-0004-9868-358X)
Institutions
- Indraprastha Institute of Information Technology Delhi (IN)
Publication Details
- Journal
- Frontiers in Immunology
- Published
- 2025-09-01
- DOI
- https://doi.org/10.3389/fimmu.2025.1630863
- Citations
- 1
- Primary Topic
- vaccines and immunoinformatics approaches
- Type
- article
- Field-Weighted Citation Impact
- 0.81
Funders
- Department of Biotechnology, Ministry of Science and Technology, India
- Department of Science and Technology, Ministry of Science and Technology, India
- University Grants Commission
- Indian Institute of Technology Delhi