In silico Investigation of Immulina Glycosidic Residues as Immunostimulants by Targeting Penaeus monodon Shrimp Toll-Receptor 9

Abstract

White Feces Syndrome (WFS) is a disease that causes serious problems in the shrimp aquaculture industry and is highly linked to two bacterial species, namely, Enterocytozoon hepatopenaei (EHP) and Gram-negative Vibrio species. Due to the emergence of new diseases in shrimps and their unclear etiology, such as WFS, there is a need for the development of new therapeutic strategies that can improve the immunity of shrimps. Thus, in this study, we determined glycosidic compounds which can serve as immunostimulants that have high affinity towards P. monodon shrimp TLR9 to induce the NF-κB signaling pathway and strengthen shrimp immunity against viral and bacterial diseases. The glycosidic compounds were obtained from the Immulina polysaccharide. The protein structure was acquired through homology modeling using mouse TLR3 (SMTL ID: 7c77.1) as a template using the SWISS-MODEL webserver. Based on the docking studies, N-acetyl-glucosamine (ca. -6.99 kcal/mol), 2,3-methylfucose (ca. -6.78 kcal/mol), and 2-methyl glycose (ca. -6.66 kcal/mol) were the top-scoring compounds which have high binding affinity towards the target protein. By visualizing the ligand-protein interactions, we learned that ASN512 was the common binding residue among most of the top-scoring compounds and plays a crucial role in ligand-protein binding. Based on the MD studies, all compounds showed low RMSD values, except N-acetyl-glucosamine, indicating good ligand binding to the target protein. In the MMPBSA studies, we found that 2,3-methylfucose had the lowest average binding energy (ca. -41.507 ± 88.52); hence, this glycosidic compound shows the highest affinity towards shrimp TLR9. To conclude, all three top-scoring compounds have highly favorable agonistic binding towards P. monodon TLR9 given their low average binding energy values. To further affirm our conclusions, we recommend the use of in vivo and in vitro tests, as well as longer MD studies for more accurate simulations.