Artículos - Centro de Bioactivos Químicos (CBQ)

URI permanente para esta colección

En esta colección están depositados los artículos científicos publicados por personal afiliado al Centro de Bioactivos Químicos (CBQ).


Envíos recientes

Mostrando 1 - 5 de 5
  • ÍtemAcceso Abierto
    Ligand-based discovery of novel trypanosomicidal drug-like compounds: In silico identification and experimental support
    (2011) Castillo Garit, Juan Alberto; Vega, Maria Celeste; Rolón, Miriam; Marrero Ponce, Yovani; Gómez Barrio, Alicia; Escario, José A.; Alvarez Bello, Alfredo; Montero Torres, Alina; Torrens, Francisco; Pérez Giménez, Facundo; Arán, Vicente J.; Abad, Concepción; Universidad Central "Marta Abreu" de Las Villas. Centro de Bioactivos Químicos; Universidad de Valencia; Centro para el Desarrollo de la Investigación Científica. Fundación Moisés Bertoni/Díaz Gill Medicina Laboratorial. Paraguay; Instituto de Química Médica, CSIC. Madrid; Universidad Central "Marta Abreu" de Las Villas. Facultad de Química y Farmacia. Departamento de Farmacia
    Two-dimensional bond-based linear indices and linear discriminant analysis are used in this report to perform a quantitative structureeactivity relationship study to identify new trypanosomicidal compounds. A database with 143 anti-trypanosomal and 297 compounds having other clinical uses, are utilized to develop the theoretical models. The best discriminant models computed using bond-based linear indices provides accuracies greater than 90 for both training and test sets. Our models identify as anti-trypanosomals five out of nine compounds of a set of already-synthesized substances. The in vitro anti-trypanosomal activity of this set against epimastigote forms of Trypanosoma cruzi is assayed. Both models show a perfect agreement between theoretical predictions and experimental results. The compounds identified as active ones show more than 98% of anti-epimastigote elimination (AE) at a concentration of 100 mg/mL. Besides, three compounds show more than 70% of AE at a concentration of 10 mg/mL. Finally, compounds with the best “activity against epimastigote forms/unspecific cytotoxicity” ratio are evaluated using an amastigote susceptibility assay. It should be noticed that, compound Va7-71 exhibit a 100% of intracellular amastigote elimination and shows similar activity when compared to a standard trypanosomicidal as nifurtimox. Finally, we can emphasize that, the present algorithm constitutes a step forward in the search for efficient ways of discovering new anti-trypanosomal compounds
  • ÍtemAcceso Abierto
    New antitrichomonal drug-like chemicals selected by bond (edge)-based TOMOCOMD-CARDD descriptors
    (2008) Meneses Marcel, Alfredo; Rivera Borroto, Oscar Miguel; Marrero Ponce, Yovani; Montero Torres, Alina; Machado Tugores, Yanetsy; Escario, José Antonio; Gómez Barrio, Alicia; Montero Pereira, David; Nogal Ruiz, Juan José; Kouznetsov, Vladimir V.; Ochoa Puentes, Christian; Bohórquez, Arnaold R.; Grau Ábalo, Ricardo del Corazón; Torrens, Francisco; Ibarra Velarde, Froylán; Arán, Vicente J.; Universidad Central "Marta Abreu" de Las Villas. Facultad de Química y Farmacia. Departamento de Farmacia; Universidad Complutense de Madrid. Facultad de Farmacia; Universidad Central "Marta Abreu" de Las Villas. Facultad de Matemática Física y Computación. Centro de Estudios Informáticos; Instituto de Ciencias Moleculares. Universidad de Valencia; Universidad Industrial de Santander, Bucaramanga, Colombia .Laboratorio de Química Orgánica y Biomolecular; Universidad Nacional Autónoma de México
    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 mg/ml, another 2 compounds (G-0 and CRIS-148) showed high cytocidal activity only at the concentration of 100 mg/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 mg/ml) was in vivo assayed in ovariectomized Wistar rats achieving promising results as a trichomonacidal drug-like compound. (Journal of Biomolecular Screening 2008:785-794).
  • ÍtemAcceso Abierto
    A linear discrimination analysis based virtual screening of trichomonacidal lead-like compounds: outcomes of in silico studies supported by experimental results
    (2005) Meneses Marcel, Alfredo; Marrero Ponce, Yovani; Machado Tugores, Yanetsy; Montero Torres, Alina; Montero Pereira, David; Escario, José Antonio; Nogal Ruiz, Juan José; Ochoa, Carmen; Arán, Vicente J.; Martínez Fernández, Antonio R.; García Sánchez, Rory N.; Universidad Central "Marta Abreu" de Las Villas. Centro de Bioactivos Químicos; Universidad Central "Marta Abreu" de Las Villas. Facultad de Química y Farmacia. Departamento de Farmacia; Instituto de Química Médica, CSIC. Madrid; Universidad Nacional de la Amazonía Peruana. Laboratorio de Investigación de Productos Naturales Antiparasitarios de la Amazonía
    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 lg/ml and low cytotoxicity to this concentration. In particular, two heterocyclic derivatives (VA7-67 and VA7-69) maintained their efficacy at 10 lg/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
  • ÍtemAcceso Abierto
    A novel non-stochastic quadratic fingerprints-based approach for the “in silico” discovery of new antitrypanosomal compounds
    (2005) Montero Torres, Alina; Vega, María Celeste; Marrero Ponce, Yovani; Rolóm, Miriam; Gómez Barrio, Alicia; Escario, José Antonio; Arán, Vicente J.; Martinez Fernández, Antonio R.; Meneses Marcel, Alfredo; Universidad Central "Marta Abreu" de Las Villas. Centro de Bioactivos Químicos; Universidad Complutense de Madrid. Facultad de Farmacia; Universidad Central "Marta Abreu" de Las Villas. Facultad de Química y Farmacia. Departamento de Farmacia; Instituto de Química Médica, CSIC. Madrid
    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 in order 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 a posteriori predicted. Also 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 ten already synthesized compounds. The in vitro antitrypanosomal activity of this series against epimastigotes forms of T. cruzi was assayed. The model was able to predict correctly the behaviour of these compounds in 90% of the cases.
  • ÍtemAcceso Abierto
    A Computer-Based Approach to the rational discovery of new trichomonacidal drugs by atom-type linear indices
    (2005) Marrero Ponce, Yovani; Machado Tugores, Yanetsy; Pereira, David M.; Barrio, Alicia G.; Nogal Ruiz, Juan J.; Montero Torres, Alina; Meneses Marcel, Alfredo; Torrens, Francisco; Martinez Fernández, Antonio R.; Garcia Sánchez, Rory; Escario, José A.; Aran, Vicente J.; Ochoa, Carmen; Universidad Central "Marta Abreu" de Las Villas. Facultad de Química y Farmacia. Departamento de Farmacia; Universidad Central "Marta Abreu" de Las Villas. Centro de Bioactivos Químicos
    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.
Los Artículos depositados en esta colección son Propiedad Patrimonial de la Universidad Central "Marta Abreu" de Las Villas, o la misma ha obtenido las autorizaciones requeridas para ejecutar el depósito de estos materiales en el Repositorio Digital.