In silico-driven identification of novel molluscicides effective against Biomphalaria glabrata (Say, 1818)

Abstract

Schistosomiasis control in endemic areas depends on several factors, including mass drug delivery programs and interrupting the transmission of disease by controlling the intermediate host snails in the freshwater ecosystem using molluscicides. However, the use of the gold standard molluscicide, i.e., niclosamide, has been considered problematic due to its high cost, toxicity for aquatic organisms, and the emergence of niclosamide-resistant snail populations. In this work, we report the in silico driven identification of novel naphthoquinone compounds with high molluscicidal activity against Biomphalaria glabrata. For this purpose, we developed statistically robust and validated shape-based and machine learning models using B. glabrata bioassay compounds data. Using these models, we prioritized fourteen naphthoquinone compounds for further in vivo testing against adult, newly-hatched, and embryo of B. glabrata snails. Among them, compounds 3, 5, 6, 7, and 12 were the best candidates, presenting moderate potency against adult snails (LC50: 28.98–102.24 μM) and high potency (LC50: 14.52–0.45 μM) against newly-hatched snails and embryos. To summarize, the in silico approach explored here allowed us to discover five new molluscicidal candidates for prospective field studies.