Anti-inflammatory potential of selective small compounds by targeting TNF-α & NF-kB signaling: a comprehensive molecular docking and simulation study

Abstract

Tumor necrosis factor alpha (TNF-α) is the major cause of inflammation in autoimmune diseases like rheumatoid arthritis (RA). It’s mechanisms of signal transduction through nuclear factor kappa B (NF-kB) pathway via small molecules such as metabolite crosstalk are still elusive. In this study, we have targeted TNF-α and NF-kB through metabolites of RA, to inhibit TNF-α activity and deter NF-kB signaling pathways, thereby mitigating the disease severity of RA. TNF-α and NF-kB structure was obtained from PDB database and metabolites of RA were selected from literature survey. In-silico studies were carried out by molecular docking using AutoDock Vina software and further, known TNF-α and NF-kB inhibitors were compared and revealed metabolite’s capacity to targets the respective proteins. Most suitable metabolite was then validated by MD simulation to verify its efficiency against TNF-α. Total 56 known differential metabolites of RA were docked with TNF-α and NF-kB compared to their corresponding inhibitor compounds. Four metabolites such as Chenodeoxycholic acid, 2-Hydroxyestrone, 2-Hydroxyestradiol (2-OHE2), and 16-Hydroxyestradiol were identified as a common TNF-α inhibitor’s having binding energies ranging from −8.3 to −8.6 kcal/mol, followed by docking with NF-kB. Further, 2-OHE2 was selected because of having binding energy −8.5 kcal/mol, found to inhibit inflammation and the effectiveness was validated by root mean square fluctuation, radius of gyration and molecular mechanics with generalized born and surface area solvation against TNF-α. Thus 2-OHE2, an estrogen metabolite was identified as the potential inhibitor, attenuated inflammatory activation and can be utilized as a therapeutic target to disseminate severity of RA.

Communicated by Ramaswamy H. Sarma

Keywords:

• Rheumatoid arthritis (RA)
• inflammation
• metabolites
• docking
• simulation

Acknowledgements

The authors acknowledge Council of Scientific and Industrial Research (CSIR), and Department of Science and Technology (DST), Government of India, New Delhi, India for providing financial support. Monu, Mohd Saquib and Debolina Chakraborty received fellowship support from CSIR. Prachi Agnihotri received fellowship from DST. The authors also thank CSIR-Institute of Genomics and Integrative Biology, Delhi, India for research and AcSIR for academic support.

Data sharing statement

For all original data and detail protocol, please contact Dr. Sagarika Biswas ([email protected]).

Disclosure statement

The authors declared no conflicts of interest.

Additional information

Funding

The authors would like to acknowledge the Department of Science and Technology (DST), Science & Engineering research board (SERB) New Delhi, India for financial support, [Grant no. vide Diary No. SERB/F/975/2020-2021].