Evaluation of the anti-inflammatory potential of atorvastatin targeting TNF-α, IL-6, and IL-1β using integrated in vitro and in silico approaches
Inflammation is a complex biological response driven by excessive activation of proinflammatory cytokines such as tumor necrosis factor-alpha (TNF-α), interleukin-1 beta (IL-1β), and interleukin-6 (IL-6), which play pivotal roles in chronic inflammatory diseases. Given the safety and wide clinical use of atorvastatin, this study aimed to explore its potential repurposing as an anti-inflammatory agent through the inhibition of these cytokines. Molecular docking was performed to predict the binding affinity and interaction profile of atorvastatin with TNF-α, IL-1β, and IL-6, followed by 200 ns molecular dynamics (MD) simulations, principal component analysis (PCA), and energy calculations to evaluate the stability and energetics of the complexes. Furthermore, the anti-inflammatory effects of atorvastatin (5–20 µM) were evaluated in LPS-stimulated RAW 264.7 macrophages using MTT cytotoxicity, cytokine assays (TNF-α, IL-6, IL-1β), and nitric oxide quantification. Docking study revealed strong binding affinity toward TNF-α (− 7.9 kcal/mol) through hydrogen bonding, supported by stable MD trajectories. The MM-GBSA binding energy (− 72.90 ± 4.38 kcal/mol) confirmed a favorable and stable interaction predominantly driven by hydrophobic and van der Waals forces. In -vitro study revealed, that atorvastatin showed no cytotoxicity and produced a strong dose-dependent inhibition of TNF-α, IL-6, IL-1β, and nitric oxide levels, with maximal anti-inflammatory activity observed at 20 µM. These findings suggest that atorvastatin may directly inhibit TNF-α and related cytokines, thereby modulating NF-κB–mediated inflammatory signaling. This study provides molecular-level insight supporting the repurposing of atorvastatin as a promising multi-target anti-inflammatory therapeutic.
Authors
- Sibghatullah Sangi (ORCID: https://orcid.org/0000-0003-3908-1613)
- Shankar Thapa (ORCID: https://orcid.org/0000-0003-1801-5668)
- N. Sreeharsha
- Ravi Chander Thatipelli (ORCID: https://orcid.org/0000-0001-5584-5180)
- Akinpelumi Akin-Adewumi
- Sadik Shaik
- Girish Meravanige
- Mohammed Monirul Islam
- Renukaradhya M.
- Krishna Swaroop
- Muhammad Shahzad Chohan
- K. V. Swathi Krishna
Institutions
- National Institute of Technology Warangal (IN)
- Patan Academy of Health Sciences (NP)
- Federal University of Technology (NG)
- University of Ibadan (NG)
- Kampala International University (UG)
- Gokula Krishna College of Pharmacy (IN)
- KLE Academy of Higher Education and Research (IN)
- Dar Al Uloom University (SA)
- King Faisal University (SA)
- Al-Ameen College of Pharmacy (IN)
Publication Details
- Journal
- Scientific Reports
- Published
- 2026-02-19
- DOI
- https://doi.org/10.1038/s41598-026-39082-6
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- King Faisal University