Estudio in silico para el reposicionamiento de fármacos del cuadro básico de medicamentos de Cuba como inhibidores de la enzima Mpro del SARS-CoV-2
Fecha
2021
Autores
Torrado Pernía, Román
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Editor
Universidad Central ‘‘Marta Abreu’’ de Las Villas. Facultad de Química y Farmacia. Departamento de Farmacia
Resumen
La Covid-19 es una enfermedad emergente producida por el virus SARS-CoV-2 que ha causado la muerte de millos de personas a nivel mundial. Nuestro país no está exento de este problema por lo que realiza grandes esfuerzos para la búsqueda de agentes terapéuticos efectivos contra este virus. La enzima viral Mpro se ha convertido en una diana importante para el desarrollo de nuevos antivirales. Esta desempeña un papel esencial en el proceso de maduración de otras proteínas no estructurales y promueve la biosíntesis del virus convirtiendo sus inhibidores en potenciales fármacos para el control de la infección. En este estudio se desarrolló un modelo QSAR de Regresión Lineal Múltipleusando el software QSARIns y los descriptores moleculares tridimensionales implementados en el DRAGON para modelar la actividad inhibitoria de la Mpro del SARS-CoV-2. El modelo muestra un R2 de 0,61 y parámetros adecuados para el ajuste del mismo. Este fue validado extensamente según los principios regulatorios de la OECD, mediante validación interna y externa mostrando adecuada estabilidad (Q2LOO=0,52) y predictibilidad (R2ext=0,54)así como bajos valores de y-aleatoria (R2Y-scr=0,06 y Q2Y-scr=-0,09)por lo que no es producto de una correlación casual. Además, se determinó su dominio de aplicación para garantizar la fiabilidad de las predicciones. El modelo fue usado para cribar 444 compuestos del Cuadro Básico de Medicamentos de Cuba de los cuales se reportan 11 como más prometedores en el tratamiento de Covid-19. Dentro de ellos se incluyen compuestos antineoplásicos que no deben usarse en pacientes que no padecen enfermedades oncológicas, antiagregante plaquetario, así como antimicrobianos que pueden tener una acción dual beneficiosa para el tratamiento de la enfermedad. Por esta razón las herramientas propuestas son útiles para la identificación rápida y económica de potenciales candidatos a fármacos contra la Mpro del SARS-CoV-2.
Palabras clave: Covid-19, proteasa Mpro, SARS-CoV-2, QSAR, Cribado virtual, Cuadro Básico de Medicamentos de Cuba.
Covid-19 is an emerging disease caused by the SARS-CoV-2 virus that has caused the death of millions of people worldwide. Our country is not exempt from this problem, which is why it makes great efforts to search for effective therapeutic agents against this virus. The viral enzyme Mpro has become an important target for the development of new antivirals. This plays an essential role in the maturation process of other non-structural proteins and promotes the biosynthesis of the virus, converting its inhibitors into potential drugs for the control of infection. In this study, a Multiple Linear Regression QSAR model was developed using the QSARIns software and the three-dimensional molecular descriptors implemented in DRAGON to model the Mproinhibitory activity of SARS-CoV-2. The model shows an R2 of 0.61 and adequate parameters for its fit. This was extensively validated according to OECD regulatory principles, through internal and external validation showing adequate stability (Q2LOO=0.5 and predictability (R2ext=0.54) as well as low y-random values (R2Y-scr=0 ,06 and Q2Y-scr=-0.09) so it is not chance correlation. In addition, its applicability domain was determined to guarantee the reliability of the predictions. The model was used to screening 444 compounds from the Basic Medication Chart of Cuba, of which 11 are reported as the most promising in the treatment of Covid-19. These include antineoplastic compounds that should not be used in patients who do not suffer from oncological diseases, antiplatelet agents, as well as antimicrobials that can have a dual beneficial action for the treatment of the disease. For this reason, the proposed tools are useful for the rapid and inexpensive identification of potential drug candidates against Mpro of SARS-CoV-2. Key words: Covid-19, Mproprotease, SARS-CoV-2, QSAR, Virtual screening, Basic Medication Chart of Cuba.
Covid-19 is an emerging disease caused by the SARS-CoV-2 virus that has caused the death of millions of people worldwide. Our country is not exempt from this problem, which is why it makes great efforts to search for effective therapeutic agents against this virus. The viral enzyme Mpro has become an important target for the development of new antivirals. This plays an essential role in the maturation process of other non-structural proteins and promotes the biosynthesis of the virus, converting its inhibitors into potential drugs for the control of infection. In this study, a Multiple Linear Regression QSAR model was developed using the QSARIns software and the three-dimensional molecular descriptors implemented in DRAGON to model the Mproinhibitory activity of SARS-CoV-2. The model shows an R2 of 0.61 and adequate parameters for its fit. This was extensively validated according to OECD regulatory principles, through internal and external validation showing adequate stability (Q2LOO=0.5 and predictability (R2ext=0.54) as well as low y-random values (R2Y-scr=0 ,06 and Q2Y-scr=-0.09) so it is not chance correlation. In addition, its applicability domain was determined to guarantee the reliability of the predictions. The model was used to screening 444 compounds from the Basic Medication Chart of Cuba, of which 11 are reported as the most promising in the treatment of Covid-19. These include antineoplastic compounds that should not be used in patients who do not suffer from oncological diseases, antiplatelet agents, as well as antimicrobials that can have a dual beneficial action for the treatment of the disease. For this reason, the proposed tools are useful for the rapid and inexpensive identification of potential drug candidates against Mpro of SARS-CoV-2. Key words: Covid-19, Mproprotease, SARS-CoV-2, QSAR, Virtual screening, Basic Medication Chart of Cuba.
Descripción
Palabras clave
COVID-19, Virus SARS-CoV-2, Modelo QSAR, Tamizaje Masivo, Cuadro Básico de Medicamentos de Cuba