Computer-aided drug screening of anti-Neobenedenia melleni drugs based on annexin B1 in farmed pearl grouper

Abstract

Monogenean capsalids of the genus Neobenedenia are widespread parasites of wild and farmed marine fish, and represent a great threat to the mariculture of grouper in China. Fishery drug development to screen and find effective compounds to control and prevent the disease is urgent needed, considering the vast production of grouper in China (294 ktons in 2025). Annexins have been discovered in Neobenedenia and other parasites, and marked differences between the parasite annexins and those of the hosts make them potentially attractive drug targets for anti-parasite therapeutics. Herein, we utilized computer-based drug discovery screens using unique Neobenedenia melleni annexin B1 and a database of 1,456,161 small molecules. The 3D structure of annexin B1 was firstly modeled by three different protein prediction tools, namely AlphaFold 3, SWISS-MODEL, and I-TASSER, of which the most accurate protein structure was used as the drug target for the following structure-based virtual screening. In vivo experimental validation of 11 compounds after molecular docking shows that abamectin (Aba) has the most effective anti-Neobenedenia bioactivity at the concentration of 0.16 mg/L as the initial screening concentration. Given its low toxicity to host grouper (24 LC50=0.254 mg/L), abamectin was chose for further investigation. A 24 h bath exposure successfully lowered the parasitic load in infected grouper, yielding an 24 h EC50 of 0.033 mg. To elucidate the anti-parasite mechanism, long-timescale molecular dynamics simulations (1000 ns) of annexin B1 and Aba was conducted, which allowed for atomic and molecular-level analysis of the essential protein motions involved in the interaction of annexin B1 and its substrate. The interaction profile between annexin B1 and abamectin was dominated by hydrophobic contacts and water bridges, involving residues TYR-210, GLU-214, GLU-244, and SER-247, which path a way for further drug optimization.