Computer-aided discovery of novel SmDHODH inhibitors for schistosomiasis therapy: Ligand-based drug design, molecular docking, molecular dynamic simulations, drug-likeness, and ADMET studies.

Schistosomiasis, also known as bilharzia or snail fever, is a tropical parasitic disease resulting from flatworms of the Schistosoma genus. This often overlooked disease has significant impacts in affected regions, causing enduring morbidity, hindering child development, reducing productivity, and creating economic burdens. Praziquantel (PZQ) is currently the only treatment option for schistosomiasis. Given the potential rise of drug resistance and the limited treatment choices available, there is a need to develop more effective inhibitors for this neglected tropical disease (NTD). In view of this, quantitative structure-activity relationship studies (QSAR), molecular docking, molecular dynamics simulations, drug-likeness, and ADMET predictions were applied to 31 inhibitors of Schistosoma mansoni Dihydroorotate dehydrogenase (SmDHODH). The designed QSAR model demonstrated robust statistical parameters including an R² of 0.911, R²_adj of 0.890, Q²cv of 0.686, R²_pred of 0.807, and cR²p of 0.825, confirming its robustness. Compound 26, identified as the most active derivative, emerged as a lead candidate for new potential inhibitors through ligand-based drug design. Subsequently, 12 novel compounds (26A-26L) were designed with enhanced inhibition activity and binding affinity. Molecular docking studies revealed strong and stable interactions, including hydrogen bonding and hydrophobic interactions, between the designed compounds and the target receptor. Molecular dynamics simulations over 100 nanoseconds and MM-PBSA free binding energy (ΔG_bind) calculations validated the stability of the two best-designed molecules (26A and 26L). Furthermore, drug-likeness and ADMET prediction analyses affirmed the potential of these designed compounds, suggesting their promise as innovative agents for treating schistosomiasis. Author summary: In an innovative effort to combat schistosomiasis, we have employed a computational drug innovation approach to design a potential treatment options. Schistosomiasis, a parasitic disease affecting millions worldwide, has been a persistent global health challenge. The study, nestled within the broader realm of life sciences, sought to identify a more effective drug using computational methods that analyze highly effective derivatives targeting SmDHODH. This pioneering approach not only accelerates the drug discovery process but also offers a promising avenue for developing targeted treatments. By harnessing computational power, we systematically explored chemical databases to pinpoint compounds with the potential to combat schistosomiasis. The findings hold significant implications for both scientists and non-scientists, as they represent a step forward in addressing a major public health concern. For scientists, this work exemplifies the integration of in silico techniques in drug development, while non-scientists can appreciate the tangible impact on improving global health and the well-being of communities affected by schistosomiasis. This research underscores the power of interdisciplinary efforts in advancing our ability to tackle complex health challenges. [ABSTRACT FROM AUTHOR]