Validation of a modified fluorimetric assay for the screening of trichomonacidal drugs.

A fluorimetric microassay that uses a redox dye to determine the viability of the flagellate Trichomonas vaginalis has been optimised to provide a more sensitive method to evaluate potential trichomonacidal compounds. Resazurin has been used in recent years to test drugs against different parasites, including trichomonadid protozoa; however, the reproducibility of these resazurin-based methods in our laboratory has been limited because the flagellate culture medium spontaneously reduces the resazurin. The objective of this work was to refine the fluorimetric microassay method previously developed by other research groups to reduce the fluorescence background generated by the media and increase the sensitivity of the screening assay. The experimental conditions, time of incubation, resazurin concentration and media used in the microtitre plates were adjusted. Different drug sensitivity studies against T. vaginalis were developed using the 5-nitroimidazole reference drugs, new 5-nitroindazolinones and 5-nitroindazole synthetic derivatives. Haemocytometer count results were compared with the resazurin assay using a 10% solution of 3 mM resazurin dissolved in phosphate buffered saline with glucose (1 mg/mL). The fluorimetric assay and the haemocytometer counts resulted in similar percentages of trichomonacidal activity in all the experiments, demonstrating that the fluorimetric microtitre assay has the necessary accuracy for high-throughput screening of new drugs against T. vaginalis.

Validation of a modified fluorimetric assay for the screening of trichomonacidal drugs

A fluorimetric microassay that uses a redox dye to determine the viability of the flagellate Trichomonas vaginalis has been optimised to provide a more sensitive method to evaluate potential trichomonacidal compounds. Resazurin has been used in recent years to test drugs against different parasites, including trichomonadid protozoa; however, the reproducibility of these resazurin-based methods in our laboratory has been limited because the flagellate culture medium spontaneously reduces the resazurin. The objective of this work was to refine the fluorimetric microassay method previously developed by other research groups to reduce the fluorescence background generated by the media and increase the sensitivity of the screening assay. The experimental conditions, time of incubation, resazurin concentration and media used in the microtitre plates were adjusted. Different drug sensitivity studies against T. vaginalis were developed using the 5-nitroimidazole reference drugs, new 5-nitroindazolinones and 5-nitroindazole synthetic derivatives. Haemocytometer count results were compared with the resazurin assay using a 10% solution of 3 mM resazurin dissolved in phosphate buffered saline with glucose (1 mg/mL). The fluorimetric assay and the haemocytometer counts resulted in similar percentages of trichomonacidal activity in all the experiments, demonstrating that the fluorimetric microtitre assay has the necessary accuracy for high-throughput screening of new drugs against T. vaginalis.

Bond-based linear indices in QSAR: computational discovery of novel anti-trichomonal compounds.

Trichomonas vaginalis (Tv) is the causative agent of the most common, non-viral, sexually transmitted disease in women and men worldwide. Since 1959, metronidazole (MTZ) has been the drug of choice in the systemic treatment of trichomoniasis. However, resistance to MTZ in some patients and the great cost associated with the development of new trichomonacidals make necessary the development of computational methods that shorten the drug discovery pipeline. Toward this end, bond-based linear indices, new TOMOCOMD-CARDD molecular descriptors, and linear discriminant analysis were used to discover novel trichomonacidal chemicals. The obtained models, using non-stochastic and stochastic indices, are able to classify correctly 89.01% (87.50%) and 82.42% (84.38%) of the chemicals in the training (test) sets, respectively. These results validate the models for their use in the ligand-based virtual screening. In addition, they show large Matthews' correlation coefficients (C) of 0.78 (0.71) and 0.65 (0.65) for the training (test) sets, correspondingly. The result of predictions on the 10% full-out cross-validation test also evidences the robustness of the obtained models. Later, both models are applied to the virtual screening of 12 compounds already proved against Tv. As a result, they correctly classify 10 out of 12 (83.33%) and 9 out of 12 (75.00%) of the chemicals, respectively; which is the most important criterion for validating the models. Besides, these classification functions are applied to a library of seven chemicals in order to find novel antitrichomonal agents. These compounds are synthesized and tested for in vitro activity against Tv. As a result, experimental observations approached to theoretical predictions, since it was obtained a correct classification of 85.71% (6 out of 7) of the chemicals. Moreover, out of the seven compounds that are screened, synthesized and biologically assayed, six compounds (VA7-34, VA7-35, VA7-37, VA7-38, VA7-68, VA7-70) show pronounced cytocidal activity at the concentration of 100 mug/ml at 24 h (48 h) within the range of 98.66%-100% (99.40%-100%), while only two molecules (chemicals VA7-37 and VA7-38) show high cytocidal activity at the concentration of 10 mug/ml at 24 h (48 h): 98.38% (94.23%) and 97.59% (98.10%), correspondingly. The LDA-assisted QSAR models presented here could significantly reduce the number of synthesized and tested compounds and could increase the chance of finding new chemical entities with anti-trichomonal activity.

Predicting antitrichomonal activity: a computational screening using atom-based bilinear indices and experimental proofs.

Existing Trichomonas vaginalis therapies are out of reach for most trichomoniasis people in developing countries and, where available, they are limited by their toxicity (mainly in pregnant women) and their cost. New antitrichomonal agents are needed to combat emerging metronidazole-resistant trichomoniasis and reduce the side effects associated with currently available drugs. Toward this end, atom-based bilinear indices, a new TOMOCOMD-CARDD molecular descriptor, and linear discriminant analysis (LDA) were used to discover novel, potent, and non-toxic lead trichomonacidal chemicals. Two discriminant functions were obtained with the use of non-stochastic and stochastic atom-type bilinear indices for heteroatoms and H-bonding of heteroatoms. These atomic-level molecular descriptors were calculated using a weighting scheme that includes four atomic labels, namely atomic masses, van der Waals volumes, atomic polarizabilities, and atomic electronegativities in Pauling scale. The obtained LDA-based QSAR models, using non-stochastic and stochastic indices, were able to classify correctly 94.51% (90.63%) and 93.41% (93.75%) of the chemicals in training (test) sets, respectively. They showed large Matthews' correlation coefficients (C); 0.89 (0.79) and 0.87 (0.85), for the training (test) sets, correspondingly. The result of predictions on the 15% full-out cross-validation test also evidenced the robustness and predictive power of the obtained models. In addition, canonical regression analyses corroborated the statistical quality of these models (R(can) of 0.749 and of 0.845, correspondingly); they were also used to compute biological activity canonical scores for each compound. On the other hand, a close inspection of the molecular descriptors included in both equations showed that several of these molecular fingerprints are strongly interrelated with each other. Therefore, these models were orthogonalized using the Randic orthogonalization procedure. These classification functions were then applied to find new lead antitrichomonal agents and six compounds were selected as possible active compounds by computational screening. The designed compounds were synthesized and tested for in vitro activity against T. vaginalis. Out of the six compounds that were designed, and synthesized, three molecules (chemicals VA5-5a, VA5-5c, and VA5-12b) showed high to moderate cytocidal activity at the concentration of 10 microg/ml, other two compounds (VA5-8pre and VA5-8) showed high cytocidal and cytostatic activity at the concentration of 100 microg/ml and 10 microg/ml, correspondingly, and the remaining chemical (compound VA5-5e) was inactive at these assayed concentrations. Nonetheless, these compounds possess structural features not seen in known trichomonacidal compounds and thus can serve as excellent leads for further optimization of antitrichomonal activity. The LDA-based QSAR models presented here can be considered as a computer-assisted system that could potentially significantly reduce the number of synthesized and tested compounds and increase the chance of finding new chemical entities with antitrichomonal activity.

Synthesis and antiparasitic properties of new 4-N-benzylamino-4-hetarylbut-1-enes.

New derivatives of 4-N-benzylamino-4-hetarylbut-1-ene containing a pyridyl nucleus were synthesized from benzylamines and pyridine aldehydes. N-oxide derivatives were obtained from these homoallylamines. Study of the antiparasitic properties of obtained pyridine derivatives as well as of four related benzazepines previously described, was carried out using cytotoxicity assays against Trichomonas vaginalis and epimastigote form of Trypanosoma cruzi protozoa. Compounds showing activity against epimastigote T. cruzi were tested against the amastigote form; unspecific cytotoxicity against macrophages was also studied.

A computer-based approach to the rational discovery of new trichomonacidal drugs by atom-type linear indices.

Computational approaches are developed to design or rationally select, from structural databases, new lead trichomonacidal compounds. First, a data set of 111 compounds was split (design) into training and predicting series using hierarchical and partitional cluster analyses. Later, two discriminant functions were derived with the use of non-stochastic and stochastic atom-type linear indices. The obtained LDA (linear discrimination analysis)-based QSAR (quantitative structure-activity relationship) models, using non-stochastic and stochastic descriptors were able to classify correctly 95.56% (90.48%) and 91.11% (85.71%) of the compounds in training (test) sets, respectively. The result of predictions on the 10% full-out cross-validation test also evidenced the quality (robustness, stability and predictive power) of the obtained models. These models were orthogonalized using the Randic orthogonalization procedure. Afterwards, a simulation experiment of virtual screening was conducted to test the possibilities of the classification models developed here in detecting antitrichomonal chemicals of diverse chemical structures. In this sense, the 100.00% and 77.77% of the screened compounds were detected by the LDA-based QSAR models (Eq. 13 and Eq. 14, correspondingly) as trichomonacidal. Finally, new lead trichomonacidals were discovered by prediction of their antirichomonal activity with obtained models. The most of tested chemicals exhibit the predicted antitrichomonal effect in the performed ligand-based virtual screening, yielding an accuracy of the 90.48% (19/21). These results support a role for TOMOCOMD-CARDD descriptors in the biosilico discovery of new compounds.