Schistosomiasis Drug Development: A Computational Approach

Abstract

Schistosomiasis continues to be a significant global health concern, affecting millions of individuals worldwide. The limitations associated with the existing treatment, Praziquantel, highlight the urgent need for novel schistosomicides. The development of a structure-based drug with high efficacy offers a potential solution to the challenges posed by current treatments. Given the capital and time-intensive nature of traditional inhibitor identification methods, computational techniques have gained prominence as valuable tools in drug discovery. This study employed a comprehensive computational approach to identify potential drug candidates, laying the groundwork for future wet-lab experimentation. In this research, in silico molecular docking analysis assessed the binding affinity of various compounds to the Schistosoma japonicum tegument protein 4 (SGTP4). To facilitate this analysis, homology modeling generated a reliable 3D structure of SGTP4. This rigorous approach, encompassing homology modeling and subsequent validation, ensured the reliability and high quality of the SGTP4 protein model, providing a solid foundation for subsequent molecular docking and drug discovery investigations. The ligands examined included Praziquantel , Licochalcone, P96, Licarin, and Harmonine. Ligand preparations were conducted using LigPrep within the Schrodinger Maestro suite, and pharmacokinetic parameters were evaluated using the QikProp tool within the Schrodinger-2019-4 software suite. Subsequently, AutoDockTools version 4 facilitated the docking analysis of the prepared ligands. The docking results furnished valuable insights into the binding affinities and potential inhibitory activities of the assessed compounds against SGTP4. PZQ, Licochalcone, and P96 exhibited robust binding affinities and inhibitory potentials, characterized by their lower binding energies and Ki values. Licarin demonstrated moderate activity, whereas Harmonine exhibited comparatively weaker binding and inhibition. The amalgamated results of docking analysis and ADMET simulations establish a foundation for the selection of lead compounds for further experimental evaluation in the quest for effective anti-schistosomal drugs. Among the evaluated compounds, Licochalcone and Licarin emerge as promising candidates, characterized by favorable molecular properties, drug-like attributes, and bioavailability. While PZQ retains its importance as a reference, its limitations underscore the necessity of exploring alternative compounds. Furthermore, P96 exhibits potential, particularly with structural modifications, warranting further investigation. This study underscores the significance of computational methodologies in the initial stages of drug discovery. Nonetheless, it is essential to stress that wet-lab experimentation remains an indispensable step in drug development. The computational insights presented herein offer a compelling rationale for the wet-lab validation of the identified candidates. Such experiments can elucidate the mechanisms of action, evaluate safety profiles, and confirm efficacy against schistosomes. Therefore, we advocate for the integration of wet-lab experiments to complement computational approaches, presenting a synergistic strategy poised to address the deficiencies of PZQ and effectively combat schistosomiasis.