Publications by authors named "Diego Fernando Amado Torres"
Computational discovery of novel trypanosomicidal drug-like chemicals by using bond-based non-stochastic and stochastic quadratic maps and linear discriminant analysis.
Juan Alberto Castillo-Garit Maria C Vega Miriam Rolon Yovani Marrero-Ponce Vladimir V Kouznetsov Diego Fernando Amado Torres
Eur J Pharm Sci
January 2010
Article Synopsis
- This study explores quantitative structure-activity relationship (QSAR) models to develop new antitrypanosomal drugs, using a dataset of 440 organic chemicals to identify which compounds are effective against Trypanosoma cruzi.
- The non-stochastic QSAR model demonstrates high classification accuracy (over 93-95%), while the stochastic model is slightly less effective (about 87%).
- Experimental results indicate that four compounds (FER16, FER32, FER33, FER132) display significant inhibitory effects on the parasite, with FER33 emerging as the most promising candidate for future optimization, despite none surpassing the effectiveness of the existing drug Nifurtimox.