Consensus scoring-based virtual screening and molecular dynamics simulation of some TNF-alpha inhibitors

Abstract

Inhibition of Tumor Necrosis Factor-alpha (TNF-alpha) represents a therapeutic approach towards the management or treatment of various inflammatory diseases like rheumatoid arthritis and cancer, but the current treatment regimen against this target in these diseases is the use of antibodies which may trigger an autoimmune response. This suggests a search for small-molecule inhibitors that could selectively inhibit the protein target. In the present study, fifty-five bioactive compounds of plant origin with already reported anti-inflammatory activities were screened for their affinity for TNF-alpha using a molecular docking strategy. We combined results from three different software packages (iGEMDOCK, MOE, & SAMSON) to come up with the best binders of the target. In addition, the resulting binders were subjected to in silico ADMET (Absorption, distribution, metabolism, excretion, and toxicity) and 100 ns molecular dynamics simulation to determine their drug-like properties and atomistic binding mechanisms respectively. Of the fifty-five evaluated bioactive compounds, Rutin, Schisantherin A, and Hesperidin performed well in the three software packages, with considerable ranking therewith. Interestingly, these compounds did not only interact with hotspot residues on TNF-alpha but also apparently balanced well on the knife-edge of pharmacokinetics and toxicity. More importantly, from the RMSD, RMSF, ROG, SASA, and hydrogen bond analysis, it was seen that Rutin, Schisantherin A, & Hesperidin exhibited stability in the active pocket of the protein. These results portend the three compounds as potent inhibitors of TNF-alpha that should be considered for further evaluation and drug development.

Keywords

• Tumor necrosis factor-alpha (TNF-α)
• Hesperidin
• Rutin
• Schisantherin A
• Molecular docking
• Virtual screening