Abstract:
:Chagas disease is endemic to 21 Latin American countries and is a great public health problem in that region. Current chemotherapy remains unsatisfactory; consequently the need to search for new drugs persists. Here we present a new approach to identify novel compounds with potential anti-chagasic action. A large dataset of 584 compounds, obtained from the Drugs for Neglected Diseases initiative, was selected to develop the computational model. Dragon software was used to calculate the molecular descriptors and WEKA software to obtain the classification tree. The best model shows accuracy greater than 93.4% for the training set; the tree was also validated using a 10-fold cross-validation procedure and through a test set, achieving accuracy values over 90.5% and 92.2%, correspondingly. The values of sensitivity and specificity were around 90% in all series; also the false alarm rate values were under 10.5% for all sets. In addition, a simulated ligand-based virtual screening for several compounds recently reported as promising anti-chagasic agents was carried out, yielding good agreement between predictions and experimental results. Finally, the present work constitutes an example of how this rational computer-based method can help reduce the cost and increase the rate in which novel compounds are developed against Chagas disease.
journal_name
SAR QSAR Environ Resjournal_title
SAR and QSAR in environmental researchauthors
Castillo-Garit JA,Barigye SJ,Pham-The H,Pérez-Doñate V,Torrens F,Pérez-Giménez Fdoi
10.1080/1062936X.2020.1863857subject
Has Abstractpub_date
2021-01-01 00:00:00pages
71-83issue
1eissn
1062-936Xissn
1029-046Xjournal_volume
32pub_type
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