Experimental models in Chagas disease: a review of the methodologies applied for screening compounds against Trypanosoma cruzi.

One of the main problems of Chagas disease (CD), the parasitic infection caused by Trypanosoma cruzi, is the lack of a completely satisfactory treatment, which is currently based on two old nitroheterocyclic drugs (i.e., nifurtimox and benznidazole) that show important limitations for treating patients. In this context, many laboratories look for alternative therapies potentially applicable to the treatment, and therefore, research in CD chemotherapy works in the design of experimental protocols for detecting molecules with activity against T. cruzi. Phenotypic assays are considered the most valuable strategy for screening these antiparasitic compounds. Among them, in vitro experiments are the first step to test potential anti-T. cruzi drugs directly on the different parasite forms (i.e., epimastigotes, trypomastigotes, and amastigotes) and to detect cytotoxicity. Once the putative trypanocidal drug has been identified in vitro, it must be moved to in vivo models of T. cruzi infection, to explore (i) acute toxicity, (ii) efficacy during the acute infection, and (iii) efficacy in the chronic disease. Moreover, in silico approaches for predicting activity have emerged as a supporting tool for drug screening procedures. Accordingly, this work reviews those in vitro, in vivo, and in silico methods that have been routinely applied during the last decades, aiming to discover trypanocidal compounds that contribute to developing more effective CD treatments.

Bond-based bilinear indices for computational discovery of novel trypanosomicidal drug-like compounds through virtual screening.

Two-dimensional bond-based bilinear indices and linear discriminant analysis are used in this report to perform a quantitative structure-activity relationship study to identify new trypanosomicidal compounds. A data set of 440 organic chemicals, 143 with antitrypanosomal activity and 297 having other clinical uses, is used to develop the theoretical models. Two discriminant models, computed using bond-based bilinear indices, are developed and both show accuracies higher than 86% for training and test sets. The stochastic model correctly indentifies nine out of eleven compounds of a set of organic chemicals obtained from our synthetic collaborators. The in vitro antitrypanosomal activity of this set against epimastigote forms of Trypanosoma cruzi is assayed. Both models show a good agreement between theoretical predictions and experimental results. Three compounds showed IC50 values for epimastigote elimination (AE) lower than 50 µM, while for the benznidazole the IC50 = 54.7 µM which was used as reference compound. The value of IC50 for cytotoxicity of these compounds is at least 5 times greater than their value of IC50 for AE. Finally, we can say that, the present algorithm constitutes a step forward in the search for efficient ways of discovering new antitrypanosomal compounds.

A sequential procedure for rapid and accurate identification of putative trichomonacidal agents.

In the current report, a sequential step-wise methodology based on in silico, in vitro and in vivo experimental procedures for the prompt detection of potential trichomonacidal drugs is proposed. A combinatorial of 12 QSAR (Quantitative Structure-Activity Relationship) models based on Linear Discrimination Analysis (LDA) are suggested for the rational identification of new trichomonacidal drugs from virtual screening of in house chemical libraries and drug databases. Subsequently, compounds selected as potential anti-trichomonas are screened in vitro against Trichomonas vaginalis. Finally, molecules with specific trichomonacidal activity are evaluated in vivo. Herein, different molecules were exposed to the proposed methodology. Firstly, the agents were virtually screened and two of the eight molecules (G-1 and dimetridazole) were classified as trichomonacidals by the 12 models. Subsequently both drugs were proved in vitro and in vivo following the workflow procedure. Although a remarkable in vitro activity was observed in both cases, dimetridazole achieved higher MIC100 activity than metronidazole against the resistant isolate. Furthermore, the in vivo models showed a remarkable reduction of lesions of more than 55% in both compounds. These observations support the current flowchart screening and suggest the use of dimetridazole as a promising drug-like scaffold for novel therapeutic alternatives against T. vaginalis resistant infections.

In vitro phenotypic screening of 7-chloro-4-amino(oxy)quinoline derivatives as putative anti-Trypanosoma cruzi agents.

In this study, a series of 22 pre-synthesized 7-chloro-4-amino(oxy)quinoline derivatives was assayed in vitro as potential antichagasic agents. A primary screening against Trypanosoma cruzi epimastigotes and a non-specific cytotoxicity assay on murine fibroblasts were simultaneously performed, resulting quinolines 3, 7 and 12 with great selectivity (SI) on the extracellular parasite (SI7, SI3, SI12 and SIBZ >9.44). Therefore, the activity of these derivatives was evaluated on intracellular amastigotes, achieving derivative 7 the best SI (SI=12.73). These results, supported by the in silico prediction of a good oral bioavailability and a suitable risk profile, propose the 4-amino-7-chloroquinoline scaffold as a potential template for designing trypanocidal prototypes.

New antitrichomonal drug-like chemicals selected by bond (edge)-based TOMOCOMD-CARDD descriptors.

Bond-based quadratic indices, new TOMOCOMD-CARDD molecular descriptors, and linear discriminant analysis (LDA) were used to discover novel lead trichomonacidals. The obtained LDA-based quantitative structure-activity relationships (QSAR) models, using nonstochastic and stochastic indices, were able to classify correctly 87.91% (87.50%) and 89.01% (84.38%) of the chemicals in training (test) sets, respectively. They showed large Matthews correlation coefficients of 0.75 (0.71) and 0.78 (0.65) for the training (test) sets, correspondingly. Later, both models were applied to the virtual screening of 21 chemicals to find new lead antitrichomonal agents. Predictions agreed with experimental results to a great extent because a correct classification for both models of 95.24% (20 of 21) of the chemicals was obtained. Of the 21 compounds that were screened and synthesized, 2 molecules (chemicals G-1, UC-245) showed high to moderate cytocidal activity at the concentration of 10 microg/ml, another 2 compounds (G-0 and CRIS-148) showed high cytocidal activity only at the concentration of 100 microg/ml, and the remaining chemicals (from CRIS-105 to CRIS-153, except CRIS-148) were inactive at these assayed concentrations. Finally, the best candidate, G-1 (cytocidal activity of 100% at 10 microg/ml) was in vivo assayed in ovariectomized Wistar rats achieving promising results as a trichomonacidal drug-like compound.