Modelación de la actividad antimalárica de compuestos orgánicos frente al parásito protozoario Plasmodium falciparum
Fecha
2016-06-25
Autores
Acosta González, Adilen Isabel
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Editor
Universidad Central “Marta Abreu” de Las Villas. Facultad de Química Farmacia. Departamento de Licenciatura en Química
Resumen
La caracterización estructural de las sustancias es uno de los campos de mayor interés dentro de las ciencias químicas. El objetivo fundamental de este trabajo consiste en desarrollar regresiones sobre un conjunto químico estructuralmente diverso, conocido como Malaria Box, para encontrar relaciones lineales que correlacionen las estructuras moleculares con sus actividades correspondientes. En este estudio se modeló la actividad antimalárica (expresada como el EC50) de 317 entidades químicas, frente al parásito Plasmodium falciparum. Las estructuras químicas fueron codificadas usando índices de derivada discreta de grafos moleculares. Estos fueron calculados utilizando el módulo DIVATI del software TOMOCOMD-CARDD. Posteriormente, para seleccionar los descriptores con mayor variabilidad, fue utilizado el software IMMAN, que permite desarrollar análisis de variabilidad basado en el cálculo de la entropía de Shannon. Los modelos de regresión lineal múltiple (RLM) fueron encontrados en el software MobyDigs, este último usa algoritmo genético para la selección de parámetros. El modelo de RLM obtenido luego de eliminar 60 estructuras outliers demostró mejor ajuste y predictibilidad que el obtenido en un inicio sin la exclusión de las mismas.
Structural characterization of the substances is one of the areas of greatest interest in the chemical sciences. The fundamental objective of this work consists in developing regressions of one dataset whit high chemist diversity, known as Malaria Box, to find linear relations between the molecular structures and their corresponding activities. In this study was modeling the antimalarial activity (expressed like the EC50) of 317 chemical entities, in front of the parasite Plasmodium falciparum. Chemical structures were encoded using indexes of discreet derivative of molecular graphs. These were calculated using the module DIVATI of the software TOMOCOMD CARDD. At a later time, in order to select the descriptors with bigger variability, was used the software IMMAN, that it allows developing analysis of variability based on the calculation of the Shannon entropy. The best MLR equations were found with MObyDigs software. These programs obtain the optimum parameters using genetic algorithm. Last to separate 60 molecular structures of data set, the model show better statistic values and mildly robustness.
Structural characterization of the substances is one of the areas of greatest interest in the chemical sciences. The fundamental objective of this work consists in developing regressions of one dataset whit high chemist diversity, known as Malaria Box, to find linear relations between the molecular structures and their corresponding activities. In this study was modeling the antimalarial activity (expressed like the EC50) of 317 chemical entities, in front of the parasite Plasmodium falciparum. Chemical structures were encoded using indexes of discreet derivative of molecular graphs. These were calculated using the module DIVATI of the software TOMOCOMD CARDD. At a later time, in order to select the descriptors with bigger variability, was used the software IMMAN, that it allows developing analysis of variability based on the calculation of the Shannon entropy. The best MLR equations were found with MObyDigs software. These programs obtain the optimum parameters using genetic algorithm. Last to separate 60 molecular structures of data set, the model show better statistic values and mildly robustness.
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Palabras clave
Malaria, Plasmodium falciparum