{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T18:02:30Z","timestamp":1792000950608,"version":"4.4.0"},"reference-count":52,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2025,12,12]],"date-time":"2025-12-12T00:00:00Z","timestamp":1765497600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["CIMB"],"abstract":"<jats:p>Background: Rheumatoid arthritis (RA) is a systemic chronic inflammatory autoimmune disease causing progressive joint destruction, resulting in significant morbidity and increased mortality. Despite advances in treatment, current pharmacological options, including NSAIDs, DMARDs, and biological agents, have limitations in tissue repair and can lead to severe side effects. Objectives: This study aims to explore drug repurposing as a viable approach to identify novel therapeutic agents for RA by utilizing existing FDA-approved drugs. Methods: We applied an integrated computational strategy that uniquely combines network pharmacology with molecular docking and dynamics simulations. The process began with the construction of a protein\u2013protein interaction (PPI) network from 2723 RA-associated genes, which identified five central targets: TNF-\u03b1, IL-6, IL-1\u03b2, STAT3, and AKT1. We then built protein\u2013drug interaction (PDI) networks by screening 2637 FDA-approved drugs against these targets. Critically, the top candidates from this network analysis were not just docked but were further validated using 100 ns molecular dynamics simulations to thoroughly evaluate binding affinity, complex stability, and interaction dynamics. Results: This multi-tiered computational workflow identified Rifampicin, Telmisartan, Danazol, and Pimozide as the most promising repurposing candidates. They demonstrated strong binding affinities and, importantly, formed stable complexes with TNF-\u03b1, IL-6, IL-1\u03b2, and STAT3, respectively, in dynamic simulations. The key innovation of this study is this sequential funnel approach, which integrates large-scale network data with atomic-level simulation to prioritize high-confidence drug candidates for RA. Conclusions: In conclusion, this study highlights the potential of repurposing FDA-approved drugs to target key proteins involved in RA, offering a cost-effective and time-efficient strategy to discover new therapies.<\/jats:p>","DOI":"10.3390\/cimb47121039","type":"journal-article","created":{"date-parts":[[2025,12,12]],"date-time":"2025-12-12T12:52:31Z","timestamp":1765543951000},"page":"1039","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Advancing Drug Repurposing for Rheumatoid Arthritis: Integrating Protein\u2013Protein Interaction, Molecular Docking, and Dynamics Simulations for Targeted Therapeutic Approaches"],"prefix":"10.3390","volume":"47","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2696-4193","authenticated-orcid":false,"given":"Krishna Swaroop","family":"Akey","sequence":"first","affiliation":[{"name":"Department of Pharmaceutical Chemistry, Shri Vile Parle Kelavani Mandal\u2019s College of Pharmacy, Shirpur 425421, MH,  India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9162-5553","authenticated-orcid":false,"given":"Bharat Kumar Reddy","family":"Sanapalli","sequence":"additional","affiliation":[{"name":"Department of Pharmacology, School of Pharmacy & Technology Management, SVKM\u2019s Narsee Monjee Institute of Management Studies (NMIMS) Deemed-to-be-University, Jadcherla 509301, TS,  India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7286-0128","authenticated-orcid":false,"given":"Dilep Kumar","family":"Sigalapalli","sequence":"additional","affiliation":[{"name":"Department of Biochemistry, University of Washington, Seattle, WA 98195, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7532-9578","authenticated-orcid":false,"given":"Ramya","family":"Tokala","sequence":"additional","affiliation":[{"name":"Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02129, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8298-1161","authenticated-orcid":false,"given":"Vidyasrilekha","family":"Sanapalli","sequence":"additional","affiliation":[{"name":"Department of Pharmaceutical Chemistry, School of Pharmacy & Technology Management, SVKM\u2019s Narsee Monjee Institute of Management Studies (NMIMS) Deemed-to-be-University, Jadcherla 509301, TS,  India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,12,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"e070856","DOI":"10.1136\/bmj-2022-070856","article-title":"Therapeutic Advances in Rheumatoid Arthritis","volume":"384","author":"Brown","year":"2024","journal-title":"Br. Med. 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