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<p>In humans, rheumatoid arthritis (RA) is a deadly autoimmune disease that affects bone health. Although the specific etiology of RA is unknown, scientific evidence suggests that smoking, genetic abnormalities, and environmental factors may all contribute to the disease’s progression. We employed protein–protein interaction (PPI) networking analysis to identify a possible therapeutic target for RA. The lead-like molecule for the selected target was then found via virtual screening in the Indian medicinal plants phytochemistry and therapeutics database. Molecular dynamics has confirmed the stability of drug target-lead-like molecule complexes. The networking analysis identifies TNF-α as a potential therapeutic target for RA. TNF-α expression was verified using in vitro studies. Cassamedine was identified as a possible lead molecule among 17,967 chemicals in the Indian Medicinal Plants Phytochemistry and Therapeutics database using virtual screening experiments. The molecular docking results of the lead compound interaction with TNF-α were clarified by the quantum mechanism (QM) technique, namely, density functional theory (DFT). The stability of the lead-like compound with TNF-α was confirmed using 200&#xa0;ns of molecular dynamics simulations. Energy calculations using molecular mechanics Poisson–Boltzmann surface area (MMPBSA) confirm the free energy between TNF-α and lead-like molecules.</p>

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PPI networking, in-vitro expression analysis, virtual screening, DFT, and molecular dynamics for identifying natural TNF-α inhibitors for rheumatoid arthritis

  • 期刊论文

  • 发表日期：

    2025年4月19日

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  • Yogaswaran Velmurugan,
  • Nandhini Chakkarapani,
  • Sathan Raj Natarajan,
  • Selvaraj Jayaraman,
  • Hemamalini Madhukar,
  • Rajakannan Venkatachalam

摘要

In humans, rheumatoid arthritis (RA) is a deadly autoimmune disease that affects bone health. Although the specific etiology of RA is unknown, scientific evidence suggests that smoking, genetic abnormalities, and environmental factors may all contribute to the disease’s progression. We employed protein–protein interaction (PPI) networking analysis to identify a possible therapeutic target for RA. The lead-like molecule for the selected target was then found via virtual screening in the Indian medicinal plants phytochemistry and therapeutics database. Molecular dynamics has confirmed the stability of drug target-lead-like molecule complexes. The networking analysis identifies TNF-α as a potential therapeutic target for RA. TNF-α expression was verified using in vitro studies. Cassamedine was identified as a possible lead molecule among 17,967 chemicals in the Indian Medicinal Plants Phytochemistry and Therapeutics database using virtual screening experiments. The molecular docking results of the lead compound interaction with TNF-α were clarified by the quantum mechanism (QM) technique, namely, density functional theory (DFT). The stability of the lead-like compound with TNF-α was confirmed using 200 ns of molecular dynamics simulations. Energy calculations using molecular mechanics Poisson–Boltzmann surface area (MMPBSA) confirm the free energy between TNF-α and lead-like molecules.