In Vitro and In Vivo Antileishmanial Activity of Thioridazine.

INTRODUCTION: Leishmaniasis is a neglected disease with high prevalence and incidence in tropical and subtropical areas. Existing drugs are limited due to cost, toxicity, declining efficacy and unavailability in endemic places. Drug repurposing has established as an efficient way for the discovery of drugs for a variety of diseases. PURPOSE: The objective of the present work was testing the antileishmanial activity of thioridazine, an antipsychotic agent with demonstrated effect against other intracellular pathogens. METHODS: The cytotoxicity for mouse peritoneal macrophages as well as the activity against Leishmania amazonensis, Leishmania mexicana and Leishmania major promastigotes and intracellular amastigotes, as well as in a mouse model of cutaneous leishmaniasis, were assessed. RESULTS: Thioridazine inhibited the in vitro proliferation of promastigotes (50% inhibitory concentration-IC50-values in the range of 0.73 µM to 3.8 µM against L. amazonensis, L. mexicana and L. major) and intracellular amastigotes (IC50 values of 1.27 µM to 4.4 µM for the same species). In contrast, in mouse peritoneal macrophages, the 50% cytotoxic concentration was 24.0 ± 1.89 µM. Thioridazine inhibited the growth of cutaneous lesions and reduced the number of parasites in the infected tissue of mice. The dose of thioridazine that inhibited lesion development by 50% compared to controls was 23.3 ± 3.1 mg/kg and in terms of parasite load, it was 11.1 ± 0.97 mg/kg. CONCLUSIONS: Thioridazine was effective against the promastigote and intracellular amastigote stages of three Leishmania species and in a mouse model of cutaneous leishmaniasis, supporting the potential repurposing of this drug as an antileishmanial agent.

Antileishmanial activity of 5-nitroindazole derivatives.

Background: Currently, there is no safe and effective vaccine against leishmaniasis and existing therapies are inadequate due to high toxicity, cost and decreased efficacy caused by the emergence of resistant parasite strains. Some indazole derivatives have shown in vitro and in vivo activity against Trichomonas vaginalis and Trypanosoma cruzi. On that basis, 20 indazole derivatives were tested in vitro against Leishmania amazonensis. Objective: To evaluate the in vitro activity of twenty 2-benzyl-5-nitroindazolin-3-one derivatives against L. amazonensis. Design: For the selection of promising compounds, it is necessary to evaluate the indicators for in vitro activity. For this aim, a battery of studies for antileishmanial activity and cytotoxicity were implemented. These results enabled the determination of the substituents in the indazole derivatives responsible for activity and selectivity, through the analysis of the structure-activity relationship (SAR). Methods: In vitro cytotoxicity against mouse peritoneal macrophages and growth inhibitory activity in promastigotes were evaluated for 20 compounds. Compounds that showed adequate selectivity were tested against intracellular amastigotes. The SAR from the results in promastigotes was represented using the SARANEA software. Results: Eight compounds showed selectivity index >10% and 50% inhibitory concentration <1 µM against the promastigote stage. Against intracellular amastigotes, four were as active as Amphotericin B. The best results were obtained for 2-(benzyl-2,3-dihydro-5-nitro-3-oxoindazol-1-yl) ethyl acetate, with 50% inhibitory concentration of 0.46 ± 0.01 µM against amastigotes and a selectivity index of 875. The SAR study showed the positive effect on the selectivity of the hydrophilic fragments substituted in position 1 of 2-benzyl-5- nitroindazolin-3-one, which played a key role in improving the selectivity profile of this series of compounds. Conclusion: 2-bencyl-5-nitroindazolin-3-one derivatives showed selective and potent in vitro activity, supporting further investigations on this family of compounds as potential antileishmanial hits.

Antichagasic, Leishmanicidal, and Trichomonacidal Activity of 2-Benzyl-5-nitroindazole-Derived Amines.

Three different series of new 5-nitroindazole derivatives-1-(ω-aminoalkyl)-2-benzylindazolin-3-ones (series A; ten compounds), 3-(ω-aminoalkoxy)-2-benzylindazoles (series B; four compounds) and 3-alkylamino-2-benzylindazoles (series C; five compounds)-have been synthesized and evaluated against the protozoan parasites Trypanosoma cruzi, Leishmania amazonensis, and Trichomonas vaginalis: etiological agents of Chagas disease, cutaneous leishmaniasis, and trichomoniasis, respectively. Many indazoles of series A, B, and C were efficient against T. cruzi. Some compounds in series A, after successfully passing the preliminary screening for epimastigotes, exhibited activity values against amastigotes of several T. cruzi strains that were better than or similar to those shown by the reference drug benznidazole and displayed low nonspecific toxicity against mammalian cells. On the other hand, preliminary studies against promastigotes of L. amazonensis showed high leishmanicidal activity for some derivatives of series A and C. With regard to activity against T. vaginalis, some indazoles of series B and C were rather efficient against trophozoites of a metronidazole-sensitive isolate and showed low nonspecific toxicities toward Vero cell cultures. Additionally, some of these compounds displayed similar activity against metronidazole-sensitive and resistant isolates, showing the absence of cross-resistance between these derivatives and the reference drug.

Drug repositioning for novel antitrichomonas from known antiprotozoan drugs using hierarchical screening.

AIM: Metronidazole is the most widely used drug in trichomoniasis therapy. However, the emergence of metronidazole-resistant Trichomonas vaginalis isolates calls for the search for new drugs to counter the pathogenicity of these parasites. RESULTS: Classification models for predicting the antitrichomonas activity of molecules were built. These models were employed to screen antiprotozoal drugs, from which 20 were classified as active. The in vitro experiments showed moderate to high activity for 19 of the molecules at 10 µg/ml, while 3 compounds yielded higher activity than the reference at 1 µg/ml. The 11 most active chemicals were evaluated in vivo using Naval Medical Research Institute (NMRI) mice. CONCLUSION: Benznidazole showed similar results as metronidazole, and can thus be considered as a potential candidate in antitrichomonas therapy.

The efficacy of 2-nitrovinylfuran derivatives against Leishmania in vitro and in vivo.

Despite recent advances in the treatment of some forms of leishmaniasis, the available drugs are still far from ideal due to inefficacy, parasite resistance, toxicity and cost. The wide-spectrum antimicrobial activity of 2-nitrovinylfuran compounds has been described, as has their activity against Trichomonas vaginalis and other protozoa. Thus, the aim of this study was to test the antileishmanial activities of six 2-nitrovinylfurans in vitro and in a murine model of leishmaniasis. Minimum parasiticide concentration (MPC) and 50% inhibitory concentration (IC50) values for these compounds against the promastigotes of Leishmania amazonensis, Leishmania infantum and Leishmania braziliensis were determined, as were the efficacies of two selected compounds in an experimental model of cutaneous leishmaniasis (CL) caused by L. amazonensis in BALB/c mice. All of the compounds were active against the promastigotes of the three Leishmania species tested. IC50 and MPC values were in the ranges of 0.8-4.7 µM and 1.7-32 µM, respectively. The compounds 2-bromo-5-(2-bromo-2-nitrovinyl)-furan (furvina) and 2-bromo-5-(2-methyl-2-nitrovinyl)-furan (UC245) also reduced lesion growth in vivo at a magnitude comparable to or higher than that achieved by amphotericin B treatment. The results demonstrate the potential of this class of compounds as antileishmanial agents and support the clinical testing of Dermofural(r) (a furvina-containing antifungal ointment) for the treatment of CL.

The efficacy of 2-nitrovinylfuran derivatives against Leishmania in vitro and in vivo

Despite recent advances in the treatment of some forms of leishmaniasis, the available drugs are still far from ideal due to inefficacy, parasite resistance, toxicity and cost. The wide-spectrum antimicrobial activity of 2-nitrovinylfuran compounds has been described, as has their activity against Trichomonas vaginalis and other protozoa. Thus, the aim of this study was to test the antileishmanial activities of six 2-nitrovinylfurans in vitro and in a murine model of leishmaniasis. Minimum parasiticide concentration (MPC) and 50% inhibitory concentration (IC50) values for these compounds against the promastigotes of Leishmania amazonensis, Leishmania infantum and Leishmania braziliensis were determined, as were the efficacies of two selected compounds in an experimental model of cutaneous leishmaniasis (CL) caused by L. amazonensis in BALB/c mice. All of the compounds were active against the promastigotes of the three Leishmania species tested. IC50 and MPC values were in the ranges of 0.8-4.7 µM and 1.7-32 µM, respectively. The compounds 2-bromo-5-(2-bromo-2-nitrovinyl)-furan (furvina) and 2-bromo-5-(2-methyl-2-nitrovinyl)-furan (UC245) also reduced lesion growth in vivo at a magnitude comparable to or higher than that achieved by amphotericin B treatment. The results demonstrate the potential of this class of compounds as antileishmanial agents and support the clinical testing of Dermofural(r) (a furvina-containing antifungal ointment) for the treatment of CL.

Synthesis and in vitro and in vivo biological evaluation of substituted nitroquinoxalin-2-ones and 2,3-diones as novel trichomonacidal agents.

Two series of ten novel 7-nitroquinoxalin-2-ones and ten 6-nitroquinoxaline-2,3-diones with diverse substituents at positions 1 and 4 were synthesized and evaluated against the sexually transmitted parasite Trichomonas vaginalis. Furthermore, diverse molecular and drug-likeness properties were analyzed to predict the oral bioavailability following the Lipinski's "rule of five". 7-Nitroquinoxalin-2-one derivatives displayed moderate to high in vitro activity while the efficiency of most nitroquinoxaline-2,3-diones was rather low; both kinds of compounds did not show cytotoxic effects in mammalian cells. 7-Nitro-4-(3-piperidinopropyl)quinoxalin-2-one 9 achieved the highest trichomonacidal activity (IC50 = 18.26 µM) and was subsequently assayed in vivo in a murine model of trichomonosis. A 46.13% and a 50.70% reduction of pathogenic injuries were observed in the experimental groups treated orally during 7 days with 50 mg/kg and 100 mg/kg doses. The results obtained in the biological assays against T. vaginalis indicate that compounds with ω-(dialkylamino)alkyl substituents and a keto group at positions 4 and 2 of quinoxaline ring, respectively, provide interesting structural cores to develop novel prototypes to enhance the nitroquinoxalinones activity as trichomonacidal agents with interesting ADME properties according to virtual screening analysis.

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.

Antiprotozoan lead discovery by aligning dry and wet screening: prediction, synthesis, and biological assay of novel quinoxalinones.

Protozoan parasites have been one of the most significant public health problems for centuries and several human infections caused by them have massive global impact. Most of the current drugs used to treat these illnesses have been used for decades and have many limitations such as the emergence of drug resistance, severe side-effects, low-to-medium drug efficacy, administration routes, cost, etc. These drugs have been largely neglected as models for drug development because they are majorly used in countries with limited resources and as a consequence with scarce marketing possibilities. Nowadays, there is a pressing need to identify and develop new drug-based antiprotozoan therapies. In an effort to overcome this problem, the main purpose of this study is to develop a QSARs-based ensemble classifier for antiprotozoan drug-like entities from a heterogeneous compounds collection. Here, we use some of the TOMOCOMD-CARDD molecular descriptors and linear discriminant analysis (LDA) to derive individual linear classification functions in order to discriminate between antiprotozoan and non-antiprotozoan compounds as a way to enable the computational screening of virtual combinatorial datasets and/or drugs already approved. Firstly, we construct a wide-spectrum benchmark database comprising of 680 organic chemicals with great structural variability (254 of them antiprotozoan agents and 426 to drugs having other clinical uses). This series of compounds was processed by a k-means cluster analysis in order to design training and predicting sets. In total, seven discriminant functions were obtained, by using the whole set of atom-based linear indices. All the LDA-based QSAR models show accuracies above 85% in the training set and values of Matthews correlation coefficients (C) vary from 0.70 to 0.86. The external validation set shows rather-good global classifications of around 80% (92.05% for best equation). Later, we developed a multi-agent QSAR classification system, in which the individual QSAR outputs are the inputs of the aforementioned fusion approach. Finally, the fusion model was used for the identification of a novel generation of lead-like antiprotozoan compounds by using ligand-based virtual screening of 'available' small molecules (with synthetic feasibility) in our 'in-house' library. A new molecular subsystem (quinoxalinones) was then theoretically selected as a promising lead series, and its derivatives subsequently synthesized, structurally characterized, and experimentally assayed by using in vitro screening that took into consideration a battery of five parasite-based assays. The chemicals 11(12) and 16 are the most active (hits) against apicomplexa (sporozoa) and mastigophora (flagellata) subphylum parasites, respectively. Both compounds depicted good activity in every protozoan in vitro panel and they did not show unspecific cytotoxicity on the host cells. The described technical framework seems to be a promising QSAR-classifier tool for the molecular discovery and development of novel classes of broad-antiprotozoan-spectrum drugs, which may meet the dual challenges posed by drug-resistant parasites and the rapid progression of protozoan illnesses.

Descubrimiento de nuevos antimaláricos a partir de fármacos conocidos mediante cribado in silico e in vitro / Discovery of new antimalarials from commercial drugs by in silico and in vitro screening

Existe una urgente necesidad de descubrir nuevas alternativas terapéuticas para el tratamiento de la Malaria, dado que los fármacos disponibles en la actualidad muestran una alta toxicidad así como elevados niveles de resistencia. En el presente trabajo se ha diseñado un protocolo de cribado virtual constituido por diferentes filtros computacionales con el propósito de identificar nuevos núcleos bases antimaláricos a partir de una biblioteca estructuralmente diversa. Este procedimiento retuvo 38 nuevos hit virtuales de los cuales 12 fueron evaluados experimentalmente frente a Plasmodium falciparum, mostrando 3 de ellos actividad antipalúdica y ninguno mostró citotoxicidad inespecífica. Estos compuestos pueden considerarse como nuevos compuestos líderes, dejando una puerta abierta al desarrollo de nuevos antimaláricos(AU)

Increased efforts in antimalarial drug discovery are urgently needed. This paper applies a virtual screening protocol consisting of different computational filters in order to identify new antimalarial scaffolds from a structurally diverse library. This procedure has retained 38 new virtual hit which 12 were selected for experimental evaluation against Plasmodium falciparum, 3 of them showed significant antimalarial activity. These compounds have diverse chemical structures unrelated to existing antimalarial drugs can therefore be considered as new lead compounds, which leave an open door to the development of new antimalarials(AU)

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.

HP-Lattice QSAR for dynein proteins: experimental proteomics (2D-electrophoresis, mass spectrometry) and theoretic study of a Leishmania infantum sequence.

The toxicity and inefficacy of actual organic drugs against Leishmaniosis justify research projects to find new molecular targets in Leishmania species including Leishmania infantum (L. infantum) and Leishmaniamajor (L. major), both important pathogens. In this sense, quantitative structure-activity relationship (QSAR) methods, which are very useful in Bioorganic and Medicinal Chemistry to discover small-sized drugs, may help to identify not only new drugs but also new drug targets, if we apply them to proteins. Dyneins are important proteins of these parasites governing fundamental processes such as cilia and flagella motion, nuclear migration, organization of the mitotic splinde, and chromosome separation during mitosis. However, despite the interest for them as potential drug targets, so far there has been no report whatsoever on dyneins with QSAR techniques. To the best of our knowledge, we report here the first QSAR for dynein proteins. We used as input the Spectral Moments of a Markov matrix associated to the HP-Lattice Network of the protein sequence. The data contain 411 protein sequences of different species selected by ClustalX to develop a QSAR that correctly discriminates on average between 92.75% and 92.51% of dyneins and other proteins in four different train and cross-validation datasets. We also report a combined experimental and theoretic study of a new dynein sequence in order to illustrate the utility of the model to search for potential drug targets with a practical example. First, we carried out a 2D-electrophoresis analysis of L. infantum biological samples. Next, we excised from 2D-E gels one spot of interest belonging to an unknown protein or protein fragment in the region M<20,200 and pI<4. We used MASCOT search engine to find proteins in the L. major data base with the highest similarity score to the MS of the protein isolated from L. infantum. We used the QSAR model to predict the new sequence as dynein with probability of 99.99% without relying upon alignment. In order to confirm the previous function annotation we predicted the sequences as dynein with BLAST and the omniBLAST tools (96% alignment similarity to dyneins of other species). Using this combined strategy, we have successfully identified L. infantum protein containing dynein heavy chain, and illustrated the potential use of the QSAR model as a complement to alignment tools.

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.

Non-stochastic quadratic fingerprints and LDA-based QSAR models in hit and lead generation through virtual screening: theoretical and experimental assessment of a promising method for the discovery of new antimalarial compounds.

In order to explore the ability of non-stochastic quadratic indices to encode chemical information in antimalarials, four quantitative models for the discrimination of compounds having this property were generated and statistically compared. Accuracies of 90.2% and 83.3% for the training and test sets, respectively, were observed for the best of all the models, which included non-stochastic quadratic fingerprints weighted with Pauling electronegativities. With a comparative purpose and as a second validation experiment, an exercise of virtual screening of 65 already-reported antimalarials was carried out. Finally, 17 new compounds were classified as either active/inactive ones and experimentally evaluated for their potential antimalarial properties on the ferriprotoporphyrin (FP) IX biocrystallization inhibition test (FBIT). The theoretical predictions were in agreement with the experimental results. In the assayed test compound C5 resulted more active than chloroquine. The current result illustrates the usefulness of the TOMOCOMD-CARDD strategy in rational antimalarial-drug design, at the time that it introduces a new family of organic compounds as starting point for the development of promising antimalarials.

New ligand-based approach for the discovery of antitrypanosomal compounds.

The antitrypanosomal activity of 10 already synthesized compounds was in silico predicted as well as in vitro and in vivo explored against Trypanosoma cruzi. For the computational study, an approach based on non-stochastic linear fingerprints to the identification of potential antichagasic compounds is introduced. Molecular structures of 66 organic compounds, 28 with antitrypanosomal activity and 38 having other clinical uses, were parameterized by means of the TOMOCOMD-CARDD software. A linear classification function was derived allowing the discrimination between active and inactive compounds with a confidence of 95%. As predicted, seven compounds showed antitrypanosomal activity (%AE>70) against epimastigotic forms of T. cruzi at a concentration of 100mug/mL. After an unspecific cytotoxic assay, three compounds were evaluated against amastigote forms of the parasite. An in vivo test was carried out for one of the studied compounds.

A novel non-stochastic quadratic fingerprints-based approach for the 'in silico' discovery of new antitrypanosomal compounds.

A non-stochastic quadratic fingerprints-based approach is introduced to classify and design, in a rational way, new antitrypanosomal compounds. A data set of 153 organic chemicals, 62 with antitrypanosomal activity and 91 having other clinical uses, was processed by a k-means cluster analysis to design training and predicting data sets. Afterwards, a linear classification function was derived allowing the discrimination between active and inactive compounds. The model classifies correctly more than 93% of chemicals in both training and external prediction groups. The predictability of this discriminant function was also assessed by a leave-group-out experiment, in which 10% of the compounds were removed at random at each time and their activity predicted a posteriori. In addition, a comparison with models generated using four well-known families of 2D molecular descriptors was carried out. As an experiment of virtual lead generation, the present TOMOCOMD approach was finally satisfactorily applied on the virtual evaluation of 10 already synthesized compounds. The in vitro antitrypanosomal activity of this series against epimastigotes forms of Trypanosomal cruzi was assayed. The model was able to predict correctly the behaviour of these compounds in 90% of the cases.

A linear discrimination analysis based virtual screening of trichomonacidal lead-like compounds: outcomes of in silico studies supported by experimental results.

A computational (virtual) screening test to identify potential trichomonacidals has been developed. Molecular structures of trichomonacidal and non-trichomonacidal drugs were represented using stochastic and non-stochastic atom-based quadratic indices and a linear discrimination analysis (LDA) was trained to classify molecules regarding their antiprotozoan activity. Validation tests revealed that our LDA-QSAR models recognize at least 88.24% of trichomonacidal lead-like compounds and suggest using this methodology in virtual screening protocols. These classification functions were then applied to find new lead antitrichomonal compounds. In this connection, the biological assays of eight compounds, selected by computational screening using the present models, give good results (87.50% of good classification). In general, most of the compounds showed high activity against Trichomonas vaginalis at the concentration of 100 microg/ml and low cytotoxicity to this concentration. In particular, two heterocyclic derivatives (VA7-67 and VA7-69) maintained their efficacy at 10 microg/ml with an important trichomonacidal activity (100.00% of reduction), but it is remarkable that the compound VA7-67 did not show cytotoxic effects in macrophage cultivations. This result opens a door to a virtual study considering a higher variability of the structural core already evaluated, as well as of other chemicals not included in this study.

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.

Aplicación de un método alternativo al conteo en cámara de Neubauer para determinar la concentración de Trichomonas vaginalis / Application of an alternative method to counting in Neubauer chamber to determine Trichomonas vaginalis concentrations

Se demostró que existe relación entre la concentración celular y la lectura de los parásitos en un lector de ELISA. Se determinó que la absorbancia tiene valores significativos en las longitudes de onda del rango visible y se escogió la longitud de onda mínima posible (450 nm) para garantizar un máximo de sensibilidad. Pudo comprobarse que ocurre un aumento significativo de la absorbancia (p<0,001) después de llenada la placa, que se estabiliza en el intervalo de 40 min hasta 4 h. Al aplicar 100, 150, 200 ó 300 µL por pozo de las diferentes concentraciones de células se demostró que el volumen óptimo era de 150 µL, se obtuvo un r2 = 0,9986, y resultaron altamente significativos el coeficiente de correlación (p<0,001) y la pendiente (p<0,001). En el intervalo de 5 x 104 a 1,5 x 107 células/mL se obtuvo un coeficiente de variación medio de 1,75 porciento (0,25-3,17 porciento). En estas condiciones el límite de cuantificación fue de 5,14 x 104 células/mL. Por último se demostró que hubo significación de la correlación entre el conteo en cámara de Neubauer y la densidad óptica