Identificación in silico de nuevos compuestos inhibidores de la Neprilisina para el tratamiento de patologías cardiovasculares
Fecha
2019
Autores
Alcántara Cárdenas, Adriana
Título de la revista
ISSN de la revista
Título del volumen
Editor
Universidad Central ``Marta Abreu`` de Las Villas. Facultad de Química y Farmacia. Departamento de Licenciatura en Ciencias Farmacéuticas
Resumen
La Neprilisina (NEP, EC:3.4.24.11) es una proteína de membrana considerada el prototipo de la familia de metalopeptidasa de zinc M13. Los inhibidores de esta enzima constituyen dianas terapéuticas para enfermedades cardiovasculares. A pesar de las alternativas existentes para el tratamiento de dichas patologías, la calidad de vida y el pronóstico de los pacientes siguen siendo precarios, por lo que se requiere el descubrimiento de nuevos fármacos con esta finalidad. En este sentido, los métodos in silico juegan un papel fundamental puesto que son una alternativa a los métodos tradicionales de “prueba y error” para la obtención de nuevas entidades moleculares. Teniendo en cuenta que la principal motivación de este trabajo es proponer modelos teóricos para la identificación de nuevos compuestos inhibidores de la Neprilisina a través de un sistema de cribado virtual, se desarrollaron modelos QSAR-ADL y QSAR-MLP con una precisión superior al 80%. Previamente se estableció un umbral para la inhibición de la NEP empleando el método de regresión piecewise (pIC50=6,855) y a partir de este valor se conformaron dos clases de compuestos (inhibidores potentes e inhibidores pobres/moderados). Los modelos desarrollados se emplearon para el cribado virtual de compuestos, estableciendo como reglas: que sean predichos como activos por ambos modelos, que estén dentro del dominio de aplicación y que posean propiedades tipo fármaco para administración oral. Siguiendo esta estrategia fueron identificados 50 compuestos potenciales inhibidores de la Neprilisina, concluyendo que las herramientas computacionales propuestas constituyen una metodología eficiente para la identificación de nuevos fármacos inhibidores de esta enzima.
Neprilysin (NEP, EC: 3.4.24.11) is a membrane protein considered the prototype of the M13 zinc metallopeptidase family. Inhibitors of this enzyme constitute therapeutic targets for cardiovascular diseases. Despite the existing alternatives for the treatment of these pathologies, the quality of life and the prognosis of patients remain precarious, which the discovery of new drugs for this purpose is required. In this sense, in silico methods play a fundamental role since they are an alternative to the traditional methods of 'proof and error' to obtain new molecular entities. Bearing in mind that the main motivation of this work is to propose theoretical models for the identification of new compounds inhibitors of Neprilysin through a virtual screening system, QSAR-LDA and QSAR-MLP models were developed with an accuracy of more than 80%. Previously, a breakpoint for the inhibition of NEP was established using the piecewise regression method (pIC50 = 6,855) and from this value two classes of compounds (potent inhibitors and poor/moderate inhibitors) are formed. The developed models were used for the virtual screening of compounds, establishing as rules: be predicted as active by both models, be within the applicability domain and possess drug-like properties for oral administration. Following this strategy, 50 potential Neprilysin inhibitors compounds were identified, concluding that the proposed computational tools constitute an efficient methodology for the identification of new inhibitory drugs of this enzyme.
Neprilysin (NEP, EC: 3.4.24.11) is a membrane protein considered the prototype of the M13 zinc metallopeptidase family. Inhibitors of this enzyme constitute therapeutic targets for cardiovascular diseases. Despite the existing alternatives for the treatment of these pathologies, the quality of life and the prognosis of patients remain precarious, which the discovery of new drugs for this purpose is required. In this sense, in silico methods play a fundamental role since they are an alternative to the traditional methods of 'proof and error' to obtain new molecular entities. Bearing in mind that the main motivation of this work is to propose theoretical models for the identification of new compounds inhibitors of Neprilysin through a virtual screening system, QSAR-LDA and QSAR-MLP models were developed with an accuracy of more than 80%. Previously, a breakpoint for the inhibition of NEP was established using the piecewise regression method (pIC50 = 6,855) and from this value two classes of compounds (potent inhibitors and poor/moderate inhibitors) are formed. The developed models were used for the virtual screening of compounds, establishing as rules: be predicted as active by both models, be within the applicability domain and possess drug-like properties for oral administration. Following this strategy, 50 potential Neprilysin inhibitors compounds were identified, concluding that the proposed computational tools constitute an efficient methodology for the identification of new inhibitory drugs of this enzyme.
Descripción
Palabras clave
Plantas Medicinales, Farmacología, Enzima Neprilisina, Fitofármacos, Patologías Cardiovasculares, Descriptores Moleculares, Modelos QSAR, Sistema de Cribado irtual