Diseño computacional de un péptido interferente para el complejo de elongación, replicación y transcripción de SARS-CoV-2
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Fecha
2023
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Idioma
es
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Universidad Andrés Bello
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Licencia CC
Licencia CC
Resumen
El año 2020 inició una pandemia a causa del virus SARS-CoV-2, el cual se replica en las células huésped gracias a su complejo de elongación, replicación y transcripción (Nsp7/Nsp8/Nsp12). Actualmente, existen muchos fármacos que han sido desarrollados in sílico (como naringenina) y otros que han llegado a las pruebas in vitro (sofosbuvir (SOF)) dando resultados positivos a la hora de inhibir RNA polimerasa RNA dependiente (RdRp o Nsp12). Si bien ha habido avances en el tema, los fármacos en estudio podrían resultar no ser tan eficientes cuando existen mutaciones del virus, esto es debido a que tanto medicamentos como vacunas se enfocan principalmente en la proteína Spike (propensa a mutaciones) o presentar alta toxicidad.
Con el fin de disminuir la actividad viral y el problema de las mutaciones, se propone, mediante el uso de herramientas computacionales como docking molecular, simulación MD y el método MM/GBSA, diseñar péptidos interferentes que se unan a sectores altamente conservados de Nsp12, los cuales serán obtenidos a partir de sitios de interacción con Nsp8 y se utilizará dicho fragmento nativo como referente para realizar mutaciones y optimizaciones con el fin de obtener un PI que tenga mejor afinidad por la proteína no estructural Nsp12. A partir del trabajo realizado se obtuvo dos fragmentos nativos de Nsp8 con 13 y 15 aminoácidos cada uno, en base a estos dos péptidos se realizaron mutaciones, las cuales generaron dos mutantes 13 MUT1 y 13 MUT2 que fueron prometedoras, especialmente 13 MUT2, la cual mediante las distintas herramientas computacionales resultó tener un ΔG total más negativo, es decir, muestra mayor afinidad que el fragmento peptídico nativo obtenido a partir de Nsp8.
Esta tesis abre la posibilidad de continuar con esta investigación, mutando fragmentos de Nsp8 con el fin de lograr el mejor péptido interferente posible para el complejo de elongación, replicación y transcripción de SARS-CoV-2 y así generar una alternativa terapéutica efectiva para evitar una nueva pandemia a partir de algún virus de la familia Coronaviridae.
In 2020, began a pandemic caused by SARS-CoV-2 virus, which replicates in hostcells thanks to its elongation, replication and transcription complex (Nsp7/Nsp8/Nsp12). Currently, there are many drugs that have been developed in silico (such as naringenin), and others that have reach in vitro trials (such as sofosbuvir (SOF)), which shows positive results in inhibiting the RNA-dependent RNA polymerase (RdRp or Nsp12). Although there have been advancements in the field, drugs under study might not be as effective when facing virus mutations. This is because both medications and vaccines mainly target the Spike protein (prone to mutations) or show high toxicity. To reduce viral activity and address the issue of mutations, it is proposed to use computational tools such as molecular docking, molecular dynamics simulation, and the MM/GBSA method, to design interfering peptides that bind to highly conserved regions of Nsp12. These regions will be obtained from interaction between Nsp12 and Nsp8, using native fragments of Nsp8 as reference for mutations and optimizations to obtain an interfering peptide with better affinity for the non-structural protein Nsp12. From this work, two native fragments of Nsp8 with 13 and 15 amino acids were obtained. Based on these two peptides, mutations were made, generating two mutants, 13 MUT1 and 13 MUT2, which showed promise. Especially 13 MUT2, which, according to various computational tools, exhibited a more negative total ΔG, indicating a higher affinity than the native peptide fragment obtained from Nsp8. This thesis opens the possibility of continuing this research, mutating Nsp8 fragments to achieve the best possible interfering peptide for the elongation, replication and transcription complex of SARS-CoV-2, thereby generating an effective therapeutic alternative to prevent a new pandemic originating from any viruses of the Coronaviridae family.
In 2020, began a pandemic caused by SARS-CoV-2 virus, which replicates in hostcells thanks to its elongation, replication and transcription complex (Nsp7/Nsp8/Nsp12). Currently, there are many drugs that have been developed in silico (such as naringenin), and others that have reach in vitro trials (such as sofosbuvir (SOF)), which shows positive results in inhibiting the RNA-dependent RNA polymerase (RdRp or Nsp12). Although there have been advancements in the field, drugs under study might not be as effective when facing virus mutations. This is because both medications and vaccines mainly target the Spike protein (prone to mutations) or show high toxicity. To reduce viral activity and address the issue of mutations, it is proposed to use computational tools such as molecular docking, molecular dynamics simulation, and the MM/GBSA method, to design interfering peptides that bind to highly conserved regions of Nsp12. These regions will be obtained from interaction between Nsp12 and Nsp8, using native fragments of Nsp8 as reference for mutations and optimizations to obtain an interfering peptide with better affinity for the non-structural protein Nsp12. From this work, two native fragments of Nsp8 with 13 and 15 amino acids were obtained. Based on these two peptides, mutations were made, generating two mutants, 13 MUT1 and 13 MUT2, which showed promise. Especially 13 MUT2, which, according to various computational tools, exhibited a more negative total ΔG, indicating a higher affinity than the native peptide fragment obtained from Nsp8. This thesis opens the possibility of continuing this research, mutating Nsp8 fragments to achieve the best possible interfering peptide for the elongation, replication and transcription complex of SARS-CoV-2, thereby generating an effective therapeutic alternative to prevent a new pandemic originating from any viruses of the Coronaviridae family.
Notas
Tesis (Licenciada en Biología)
Palabras clave
COVID-19 (Enfermedad), Investigaciones, Dinámica Molecular, Simulación por Computadores, Péptidos, Uso Terapéutico.