TNF-α inhibitory potential of bioactive compounds from Caesalpinia sappan L.: A virtual screening study

Abstract

   Background: Tumor necrosis factor alpha (TNF-α) is a multifunctional proinflammatory cytokine that plays a crucial role in many pathological conditions such as inflammation, autoimmune diseases, and cancer. There is a large body of evidence that Caesalpinia sappan L. extract inhibits the TNF-α signaling pathway. Nevertheless, no studies evaluating the TNF-α inhibitory capacity of bioactive metabolites in C. sappan have been reported to date, and the mechanism of this process remains unclear. This study assessed the in silico binding ability of bioactive compounds in C. sappan with TNF-α through molecular docking simulation.
   Methods: The secondary metabolite structures reported from C. sappan were retrieved from the PubChem database. A model of molecular docking simulation was constructed based on the crystal structure of TNF-α and the small molecule SPD304 with the PDB ID 2AZ5 (rcsb.org/structure/2AZ5). A high throughput docking campaign was conducted by using Autodock Vina with a simple bash script. The optimal docking pose of each compound was visually analyzed using BIOVIA Discovery Studio Visualizer.
   Results: Most of the compounds in C. sappan showed good in silico binding ability to TNF-α. The fifteen metabolites were recognized as potential TNF-α inhibitors with better binding energy than the reference ligand SPD304. Neoprotosappanin was discovered as the best potential structure with a binding energy of -10.06 kcal/mol and meaningful in silico interactions with TNF-α.
   Conclusions: Bioactive compounds from sappanwood may have the potential to inhibit TNF-α. The most promising compounds should be further evaluated by molecular dynamics simulations and predicted pharmacokinetic and toxicological properties before performing in vitro assays.
   Background: Tumor necrosis factor alpha (TNF-α) is a multifunctional proinflammatory cytokine that plays a crucial role in many pathological conditions such as inflammation, autoimmune diseases, and cancer. There is a large body of evidence that Caesalpinia sappan L. extract inhibits the TNF-α signaling pathway. Nevertheless, no studies evaluating the TNF-α inhibitory capacity of bioactive metabolites in C. sappan have been reported to date, and the mechanism of this process remains unclear. This study assessed the in silico binding ability of bioactive compounds in C. sappan with TNF-α through molecular docking simulation.
   Methods: The secondary metabolite structures reported from C. sappan were retrieved from the PubChem database. A model of molecular docking simulation was constructed based on the crystal structure of TNF-α and the small molecule SPD304 with the PDB ID 2AZ5 (rcsb.org/structure/2AZ5). A high throughput docking campaign was conducted by using Autodock Vina with a simple bash script. The optimal docking pose of each compound was visually analyzed using BIOVIA Discovery Studio Visualizer.
   Results: Most of the compounds in C. sappan showed good in silico binding ability to TNF-α. The fifteen metabolites were recognized as potential TNF-α inhibitors with better binding energy than the reference ligand SPD304. Neoprotosappanin was discovered as the best potential structure with a binding energy of -10.06 kcal/mol and meaningful in silico interactions with TNF-α.
   Conclusions: Bioactive compounds from sappanwood may have the potential to inhibit TNF-α. The most promising compounds should be further evaluated by molecular dynamics simulations and predicted pharmacokinetic and toxicological properties before performing in vitro assays.

DOI: 10.59715/pntjmp.5.2.19