Skip to content
2000
image of Computational Screening of IL-1 and IL-6 Inhibitors for Rheumatoid Arthritis: 
Insights from Molecular Docking and Dynamics Analysis

Abstract

Background

Rheumatoid arthritis (RA) remains a significant therapeutic challenge due to its chronic inflammatory nature. Consequently, many patients turn to alternative therapies, such as herbal compounds and supplements, when conventional treatments prove relatively ineffective or cause adverse side effects. Some compounds are being investigated for their potential to alleviate RA symptoms or manage disease. This study aimed to evaluate the anti-inflammatory effects of selected herbal compounds targeting the Interleukin-1 (IL-1) and Interleukin-6 (IL-6) pathways, key inflammatory regulators in RA. Specifically, the study assessed the binding affinity, stability, and dynamics of IL-1 and IL-6 inhibitory compounds as potential therapeutic agents for RA.

Methods

experiments were conducted with herbal compounds to modulate IL-1 and IL-6 signaling. Computational techniques, including molecular docking, molecular dynamics (MD) simulations, Molecular Mechanics-Generalized Born Surface Area (MM-GBSA) calculations, Absorption, Distribution, Metabolism, and Excretion (ADME) analysis, toxicity predictions, and Density Functional Theory (DFT) analysis, were employed to investigate these interactions comprehensively.

Results

Neoglucobrassicin demonstrated the strongest binding affinity for IL-6 (Total score: -349.00 kJ/mol), followed by Galbelgin (-338.00 kJ/mol). For IL-1β, CID21722980 exhibited the highest binding affinity 
(-273.14 kJ/mol), with Eupaformosanin ranking second (-264.29 kJ/mol). Neoglucobrassicin formed interactions with multiple IL-6 residues, indicating a stable binding complex, while CID21722980 similarly interacted with key IL-1β residues, forming stable complexes. Both the Neoglucobrassicin-IL-6 and CID21722980-IL1β complexes demonstrated structural stability, as evidenced by Root Mean Square Deviation (RMSD) and Root Mean Square Fluctuation (RMSF) stabilizing towards the end of the 100 ns molecular dynamics (MD) simulation. MM-GBSA analysis revealed the highest binding energy for the IL-6-Neoglucobrassicin complex (-43.70 kcal/mol), while CID21722980 showed strong affinity for IL-1β (-43.29 kcal/mol), suggesting enhanced binding potential. Additionally, Density Functional Theory (DFT) analysis of the Highest Occupied Molecular Orbital (HOMO) and Lowest Unoccupied Molecular Orbital (LUMO) energies revealed electron distribution patterns in Neoglucobrassicin and CID21722980 that support their potential therapeutic applications.

Discussion

The strong binding affinities, stable molecular dynamics (MD) simulations, and favorable 
ADMET and DFT properties of Neoglucobrassicin and CID21722980 underscore their potential as anti-inflammatory agents targeting IL-6 and IL-1β. The mechanistic insights into their inhibitory effects on these targets suggest multifaceted anti-inflammatory properties, warranting further and clinical investigations.

Conclusion

Neoglucobrassicin and CID21722980 demonstrated promising binding affinities, favorable pharmacokinetic profiles, and advantageous electronic properties, positioning them as strong candidates for further exploration in anti-inflammatory therapies. These findings highlight the potential of these herbal compounds as modulators of IL-6 and IL-1β, paving the way for future drug development.

Loading

Article metrics loading...

/content/journals/cpd/10.2174/0113816128344776250222043907
2025-03-20
2025-05-21
Loading full text...

Full text loading...

References

  1. Calabresi E. Petrelli F. Bonifacio A.F. Puxeddu I. Alunno A. One year in review 2018: Pathogenesis of rheumatoid arthritis. Clin. Exp. Rheumatol. 2018 36 2 175 184 29716677
    [Google Scholar]
  2. Zhang L. Zhang Y. Pan J. Immunopathogenic mechanisms of rheumatoid arthritis and the use of anti-inflammatory drugs. Intractable Rare Dis. Res. 2021 10 3 154 164 10.5582/irdr.2021.01022 34466337
    [Google Scholar]
  3. Makaremi S. Asgarzadeh A. Kianfar H. Mohammadnia A. Asghariazar V. Safarzadeh E. The role of IL-1 family of cytokines and receptors in pathogenesis of COVID-19. Inflamm. Res. 2022 71 7-8 923 947 10.1007/s00011‑022‑01596‑w 35751653
    [Google Scholar]
  4. Yazdi A.S. Ghoreschi K. The interleukin-1 family. Adv. Exp. Med. Biol. 2016 941 21 29 10.1007/978‑94‑024‑0921‑5_2 27734407
    [Google Scholar]
  5. Pandolfi F. Franza L. Carusi V. Altamura S. Andriollo G. Nucera E. Interleukin-6 in rheumatoid arthritis. Int. J. Mol. Sci. 2020 21 15 5238 10.3390/ijms21155238 32718086
    [Google Scholar]
  6. Narazaki M. Kishimoto T. The two-faced cytokine IL-6 in host defense and diseases. Int. J. Mol. Sci. 2018 19 11 3528 10.3390/ijms19113528 30423923
    [Google Scholar]
  7. Feng W Liu H Luo T Combination of IL-6 and sIL-6R differentially regulate varying levels of RANKL-induced osteoclastogenesis through NF-κB, ERK and JNK signaling pathways. Sci. Rep. 2017 7 41411 10.1038/srep41411
    [Google Scholar]
  8. Mazurek-Mochol M. Bonsmann T. Mochol M. Poniewierska-Baran A. Pawlik A. The role of interleukin 6 in periodontitis and its complications. Int. J. Mol. Sci. 2024 25 4 2146 10.3390/ijms25042146 38396821
    [Google Scholar]
  9. Rose-John S. Jenkins B.J. Garbers C. Moll J.M. Scheller J. Targeting IL-6 trans-signalling: Past, present and future prospects. Nat. Rev. Immunol. 2023 23 10 666 681 10.1038/s41577‑023‑00856‑y 37069261
    [Google Scholar]
  10. Santos L.H.S. Ferreira R.S. Caffarena E.R. Integrating molecular docking and molecular dynamics simulations. Methods Mol. Biol. 2019 2053 13 34 10.1007/978‑1‑4939‑9752‑7_2 31452096
    [Google Scholar]
  11. Salam P. Chitta R. Sharif U. Yenisetti S. Bolin K. Molecular docking simulation analysis of the interaction of dietary flavonols with heat shock protein 90. J. Biomed. Res. 2016 30 1 67 74 10.7555/JBR.30.20130158 26423731
    [Google Scholar]
  12. Wang K. Huang Y. Wang Y. You Q. Wang L. Recent advances from computer-aided drug design to artificial intelligence drug design. RSC Med. Chem. 2024 15 3978 4000 10.1039/D4MD00522H
    [Google Scholar]
  13. Guo Z. Zhang H. Fu Y. Kuang J. Zhao B. Zhang L. Lin J. Lin S. Wu D. Xie G. Cancer-associated fibroblasts induce growth and radioresistance of breast cancer cells through paracrine IL-6. Cell Death Discov. 2023 9 1 6 10.1038/s41420‑023‑01306‑3 36635302
    [Google Scholar]
  14. Hirano T. IL-6 in inflammation, autoimmunity and cancer. Int. Immunol. 2021 33 3 127 148 10.1093/intimm/dxaa078 33337480
    [Google Scholar]
  15. Baran P. Hansen S. Waetzig G.H. Akbarzadeh M. Lamertz L. Huber H.J. Ahmadian M.R. Moll J.M. Scheller J. The balance of interleukin (IL)-6, IL-6·soluble IL-6 receptor (sIL-6R), and IL-6·sIL-6R·sgp130 complexes allows simultaneous classic and trans-signaling. J. Biol. Chem. 2018 293 18 6762 6775 10.1074/jbc.RA117.001163 29559558
    [Google Scholar]
  16. Nada H. Sivaraman A. Lu Q. Min K. Kim S. Goo J.I. Choi Y. Lee K. Perspective for discovery of small molecule IL-6 inhibitors through study of structure–activity relationships and molecular docking. J. Med. Chem. 2023 66 7 4417 4433 10.1021/acs.jmedchem.2c01957 36971365
    [Google Scholar]
  17. Alshahrani M.Y. Suliman M. Almoyad M.A.A. Wahab S. Identification of ZINC08101049 as a potential IL1β inhibitor through molecular docking and MD simulations for cancer therapeutics. J. Biomol. Struct. Dyn. 2024 19 1 12 10.1080/07391102.2024.2304669 38240096
    [Google Scholar]
  18. Harmalkar D.S. Sivaraman A. Nada H. Lee J. Kang H. Choi Y. Lee K. Natural products as IL‐6 inhibitors for inflammatory diseases: Synthetic and SAR perspective. Med. Res. Rev. 2024 44 4 1683 1726 10.1002/med.22022 38305581
    [Google Scholar]
  19. Wolf J. Rose-John S. Garbers C. Interleukin-6 and its receptors: A highly regulated and dynamic system. Cytokine 2014 70 1 11 20 10.1016/j.cyto.2014.05.024 24986424
    [Google Scholar]
  20. Kaneko N. Kurata M. Yamamoto T. Morikawa S. Masumoto J. The role of interleukin-1 in general pathology. Inflamm. Regen. 2019 39 1 12 10.1186/s41232‑019‑0101‑5 31182982
    [Google Scholar]
  21. Watanabe H. Gaide O. Pétrilli V. Martinon F. Contassot E. Roques S. Kummer J.A. Tschopp J. French L.E. Activation of the IL-1beta-processing inflammasome is involved in contact hypersensitivity. J. Invest. Dermatol. 2007 127 8 1956 1963 10.1038/sj.jid.5700819 17429439
    [Google Scholar]
  22. Tran Q.H. Nguyen Q.T. Tran T.T.N. Tran T.D. Le M.T. Trinh D.T.T. Tran V.T. Tran V.H. Thai K.M. Identification of small molecules as potential inhibitors of interleukin 6: A multi-computational investigation. Mol. Divers. 2023 27 5 2315 2330 10.1007/s11030‑022‑10558‑7 36319930
    [Google Scholar]
  23. Liu T. Chen Y. Adil M. Almehmadi M. Alshabrmi F.M. Allahyani M. Alsaiari A.A. Liu P. Khan M.R. Peng Q. In silico identification of natural product-based inhibitors targeting IL-1β/IL-1R protein–protein interface. Molecules 2023 28 13 4885 10.3390/molecules28134885 37446547
    [Google Scholar]
  24. Naqvi A.A.T. Mohammad T. Hasan G.M. Hassan M.I. Advancements in docking and molecular dynamics simulations towards ligand-receptor interactions and structure-function relationships. Curr. Top. Med. Chem. 2018 18 20 1755 1768 10.2174/1568026618666181025114157 30360721
    [Google Scholar]
  25. Gallo M.T. Grant B.J. Teodoro M.L. Melton J. Cieplak P. Phillips G.N. Jr Stec B. Novel procedure for thermal equilibration in molecular dynamics simulation. Mol. Simul. 2009 35 5 349 357 10.1080/08927020802647272 25125797
    [Google Scholar]
  26. Gupta A. Rajaram S.S. Thompson G.B. Tucker G.J. Improved computational method to generate properly equilibrated atomistic microstructures. MethodsX 2021 8 101217 10.1016/j.mex.2021.101217 34434740
    [Google Scholar]
  27. Tran Q.H. Nguyen Q.T. Vo N.Q.H. Mai T.T. Tran T.T.N. Tran T.D. Le M.T. Trinh D.T.T. Thai K.M. Structure-based 3D-pharmacophore modeling to discover novel interleukin 6 inhibitors: An in silico screening, molecular dynamics simulations and binding free energy calculations. PLoS One 2022 17 4 e0266632 10.1371/journal.pone.0266632 35385549
    [Google Scholar]
  28. Halim S.A. Jawad M. Ilyas M. Mir Z. Mirza A.A. Husnain T. In silico identification of novel IL-1β inhibitors to target protein–protein interfaces. Comput. Biol. Chem. 2015 58 158 166 10.1016/j.compbiolchem.2015.06.004 26253030
    [Google Scholar]
  29. Owoloye A.J. Ligali F.C. Enejoh O.A. Musa A.Z. Aina O. Idowu E.T. Oyebola K.M. Molecular docking, simulation and binding free energy analysis of small molecules as PfHT1 inhibitors. PLoS One 2022 17 8 e0268269 10.1371/journal.pone.0268269 36026508
    [Google Scholar]
  30. Qiu J.G. Wang L. Liu W.J. Wang J.F. Zhao E.J. Zhou F.M. Ji X.B. Wang L.H. Xia Z.K. Wang W. Lin M.C. Liu L.Z. Huang Y.X. Jiang B.H. Apigenin inhibits IL-6 transcription and suppresses esophageal carcinogenesis. Front. Pharmacol. 2019 10 1002 10.3389/fphar.2019.01002 31572184
    [Google Scholar]
  31. Lee H.H. Jung J. Moon A. Kang H. Cho H. Antitumor and anti-invasive effect of apigenin on human breast carcinoma through suppression of IL-6 expression. Int. J. Mol. Sci. 2019 20 13 3143 10.3390/ijms20133143 31252615
    [Google Scholar]
/content/journals/cpd/10.2174/0113816128344776250222043907
Loading
/content/journals/cpd/10.2174/0113816128344776250222043907
Loading

Data & Media loading...

Supplements

Supplementary material is available on the publisher's website along with the published article.

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test