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Computer-Assisted Discovery of Compounds With Schistosomicidal Activity
- Source :
- Bioinformatics and Biology Insights, Vol 18 (2024)
- Publication Year :
- 2024
- Publisher :
- SAGE Publishing, 2024.
-
Abstract
- Schistosomiasis, otherwise known as bilharzia or snail fever, is a disease that usually affects poor people and people exposed to poor sanitation. The disease affects over 200 million people worldwide annually. Schistosomiasis has been treated using a single drug, praziquantel, since the 1970s and this is resulting in schistosomes becoming resistant. Therefore, there is an urgent need to develop new antischistosoma drugs and vaccines. This study focuses on identifying potential antischistosomal compounds from the plant Salvia fruticosa . We virtually screened a library of 163 S fruticosa compounds by docking against Schistosoma mansoni sulfotransferase ( Sm SULT) using the PyRx software. Docking scores ranged from −4.7 to −9.3 kcal/mol. Compounds with binding affinity of −7.6 or stronger were subjected to drug-likeness assessments using the DataWarrior software. We also employed the PAINS removal tool to filter off false-positive results. Twelve compounds passed the drug-likeness screen, and these were subjected to in silico toxicity predictions to determine their mutagenic, tumorigenic and reproductive potential. Seven compounds were predicted to be nontoxic. After considering the toxicity analysis results and drug scores of the compounds, we identified rosmarinic acid and hispidulin as qualifying for further evaluation as potential drugs against schistosomiasis. Free energy calculations using the fastDRH webserver and molecular dynamics simulations using CABS-flex showed that the receptor-ligand complexes for the 2 lead compounds are stable under physiological conditions. We recommend that rosmarinic acid and hispidulin be used as hit compounds for the development of potential antischistosomal drugs.
- Subjects :
- Biology (General)
QH301-705.5
Subjects
Details
- Language :
- English
- ISSN :
- 11779322
- Volume :
- 18
- Database :
- Directory of Open Access Journals
- Journal :
- Bioinformatics and Biology Insights
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.f7828551255b4525a514364001ad1826
- Document Type :
- article
- Full Text :
- https://doi.org/10.1177/11779322241240651