RESUMO
The aims of the present study were to establish an adequate excystment method for metacercariae of Paramphistomum spp. and to compare the in vitro survival of paramphistomids in three different culture media. In a preliminary study, 31 different assays were performed solely with the purpose of obtaining the best percentage of metacercariae excystment. Once the best excystment method was selected, 21 further assays using 100 metacercariae/assay were carried out to determine the average percentage of excystment. For the in vitro culture of paramphistomids, the Hedon-Fleig, Rohrbacher, and RPMI-1640 culture media were compared by using 24-well immunoplates containing newly excysted flukes or 50-ml capacity tissue-culture flasks for adult paramphistomids. Results indicated an average of 69.0% excystment, the best culture medium to support the survival of immature and adult stages of the trematode being Hedon-Fleig and Rohrbacher, respectively. The best percentage of survival obtained was on day 4 (80%), with some immature and adult trematodes remaining alive until days 10 and 11, respectively.
Assuntos
Paramphistomatidae/citologia , Paramphistomatidae/fisiologia , Animais , Meios de Cultura , Estágios do Ciclo de Vida , Fatores de TempoRESUMO
Helminth infections are a medical problem in the world nowadays. In this paper a novel atom-level chemical descriptor has been applied to estimate the anthelmintic activity. Total and local linear indices and linear discriminant analysis were used to obtain a quantitative model that discriminates between anthelmintic and non-anthelmintic drug-like compounds. The discriminant model has an accuracy of 90.11% in the training set, with a high Matthews' correlation coefficient (MCC=0.80). To assess the robustness and predictive power of the obtained model, internal (leave-n-out) and external validation process was performed. The QSAR model correctly classified 88.55% of compounds in this external prediction set, yielding a MCC of 0.77. Another LDA model was carried out to outline some conclusions about the possible modes of action of anthelmintic drugs. It has an accuracy of 93.50% in the training set, and 80.00% in the external prediction set. After that, the developed model was used in the virtual--in silico--screening and several compounds from the Merck Index, Negwer's Handbook and Goodman and Gilman were identified by the model as anthelmintic. Finally, the experimental assay of an organic chemical (a furylethylene derivative) by an in vivo test permits us to carry out an assessment of the model. An accuracy of 100% with the theoretical predictions was observed. These results suggest that the proposed method will be a good tool for studying the biological properties of drug candidates during the early state of the drug-development process.
Assuntos
Anti-Helmínticos/química , Desenho de Fármacos , Anti-Helmínticos/classificação , Modelos QuímicosRESUMO
In this work, the TOMOCOMD-CARDD approach has been applied to estimate the anthelmintic activity. Total and local (both atom and atom-type) quadratic indices and linear discriminant analysis were used to obtain a quantitative model that discriminates between anthelmintic and non-anthelmintic drug-like compounds. The obtained model correctly classified 90.37% of compounds in the training set. External validation processes to assess the robustness and predictive power of the obtained model were carried out. The QSAR model correctly classified 88.18% of compounds in this external prediction set. A second model was performed to outline some conclusions about the possible modes of action of anthelmintic drugs. This model permits the correct classification of 94.52% of compounds in the training set, and 80.00% of good global classification in the external prediction set. After that, the developed model was used in virtual in silico screening and several compounds from the Merck Index, Negwer's handbook and Goodman and Gilman were identified by models as anthelmintic. Finally, the experimental assay of one organic chemical (G-1) by an in vivo test coincides fairly well (100%) with model predictions. These results suggest that the proposed method will be a good tool for studying the biological properties of drug candidates during the early state of the drug-development process.