Computational Design of Novel Candidate Drug Molecules for Schistosomiasis

Abstract

Schistosomiasis is a parasitic disease that leads to chronic ill-health. Infection is acquired from infested freshwater containing the larval forms (cercariae) of blood flukes, known as schistosomes. The three main species of the parasite that infect humans are Schistosoma haematobium, S.japonicum, and S.mansoni. Schistosomiasis affects at least 230 million people worldwide. The infection is prevalent in tropical and sub-tropical areas, in poor communities without potable water and adequate sanitation. The disease is considered as one of the Neglected Tropical Diseases and so far praziquantel is the only drug used for treatment. Should the parasites develop resistance to praziquantel, treatment would be problematic.  This study incorporated a computational approach to design novel compounds with unprecedented potential as candidate drug compounds for the disease. The Schistosoma mansoni fatty acid binding protein was selected as a suitable drug target for its crucial role in the dependence of the parasite on its host for fatty acids. Screening for potential lead compounds was done using molecular docking software.  Identified lead compounds were analyzed and optimized in silico for their ADMET properties then re-evaluated for suitability of their binding energies. Eight novel compounds with good predicted ADMET properties were designed and found to interact with the S.mansoni fatty acid binding protein with favorable binding energy, showing potential to inhibit this protein. This study opens up new possibilities in antischistosomal drug inquiry and potentiates efficacy studies of such compounds against schistosomiasis.

Keywords: computational design, antischistosomal drug inquiry, binding energy, lead optimization, ADMET properties