Análisis y elaboración de un modelo in silico para 2 proteasas romboides (AtRBL10 Y AtRBL13) de Arabidopsis thaliana para el estudio de la relación entre secuencia y función
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Fecha
2022
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es
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Universidad Andrés Bello
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Licencia CC
Licencia CC
Resumen
Las proteasas romboides son la familia más grande de enzimas que hidrolizan enlaces
peptídicos, dentro del entorno hidrófobo de la membrana celular. Si bien hace menos de
3 décadas fueron descubiertas y clasificadas como serina proteasas, ya se consideran
como una de las proteasas intramembranas mejor comprendidas. Transformando a los
bastos miembros de la familia, repartidos por todos los reinos de la vida, en potenciales
reguladores de procesos complejos dentro de la célula; por lo que no es de sorprender
que en organismo sésiles como las plantas, sean los que presenten más homólogos
romboides, dando indicios de que esta superfamilia de enzimas, pudiese haber
diversificado sus funciones en las células vegetales, conservando por lo menos la
disposición espacial que debe adoptar para adaptarse a las distintas membranas
celulares. Por lo que el conocer a cabalidad su estructura, siempre se ha tomado como
objetivo clave para conocer el rol fisiológico y que puede ser pieza clave para el
entendimiento de la proteólisis intramembrana regulada (RIP) y de cuanto está
involucrada en la regulación homeostática de los organismos vegetales. En ausencia de
estructuras tridimensionales experimentales, hay varios ejemplos donde la predicción
computarizada ha generado grandes contribuciones en la predicción de nueva funciones
proteicas, por lo que, un enfoque adecuado para comparar la funcionalidad de proteínas
pertenecientes a la misma familia; como es el caso de las 2 romboides de la planta
modelo A thaliana, AtRBL10 y AtRBL13.
Gracias a los grandes avances en el desarrollo de la inteligencia artificial (IA) se han
generado herramientas computacionales que han permitido manejar cantidades de
información nunca vistas, generando predicciones cada vez más cercanas a las
obtenidas experimentalmente, dándole mucho más valor y peso a los ensayos in silico.
La anotación por homología ha sido uno de los métodos más utilizados para la anotación
funcional de péptidos, especialmente de enzimas, donde se ha logrado la inferencia de
nuevas familias de enzimas, gracias a la comparación en la composición de su
secuencia con respecto de una de función conocida. Este método se basa en la
suposición de que las proteínas con secuencias similares tendrán funciones similares.
La anotación homológica es especialmente útil para estudiar la relación secuencia función de proteínas con pocos antecedentes disponibles o como el caso de las
romboides, superfamilias recientemente descubiertas, que difieren bastante de las ya
caracterizadas e inclusive entre ellas mismas.
Se logra corroborar que mediante las nacientes herramientas biotecnologicas, labores
que anteriormente, se obtenía mucha ambigüedad entre las predicciones obtenidas,
como determinar el número de segmentos transmembrana (TMD) o la relación
conservada en la secuencia aminoacídica de grupos con centenares de proteínas; ya
se encuentran más democratizadas para su libre acceso, incluso para usuarios sin una
mayor experiencia o conocimientos informáticos. Para esto fue necesario, la generación
y depuración de un red de similitud de secuencia, esto con el objetivo de interrogar estas
dos enzimas, abordando el desafío de vincular la información funcional descrita hasta la
fecha, con la secuencia y las similitudes estructurales obtenidas, utilizando un redes de
similitud de proteínas que permita dicha inspección pero desde una visión a gran escala
de la familia, con un énfasis especial en los homólogos vegetales, pensando en dilucidar
nuevas funciones aún no exploradas en plantas, para este tipo de enzimas
Rhomboid proteases are the largest family of enzymes that hydrolyse peptide bonds within the hydrophobic environment of the cell membrane. Although they were discovered and classified as serine proteases less than 3 decades ago, they are already considered one of the best understood intramembrane proteases. Transforming the numerous members of the family, spread throughout all kingdoms of life, into potential regulators of complex processes within the cell; it is therefore not surprising that in sessile organisms such as plants, they are the ones with the most rhomboid homologues, giving indications that this superfamily of enzymes may have diversified their functions in plant cells, conserving at least the spatial arrangement that must be adopted to adapt to the different cell membranes. Therefore, a thorough understanding of its structure has always been a key objective for understanding its physiological role and may be a key to understanding regulated intramembrane proteolysis (RIP) and how it is involved in the homeostatic regulation of plant organisms. In the absence of experimental three-dimensional structures, there are several examples where computational prediction has generated great contributions in the prediction of new protein functions, thus, a suitable approach to compare the functionality of proteins belonging to the same family; such is the case of the 2 rhomboids of the model plant A.thaliana, AtRBL10 and AtRBL13. Thanks to the great advances in the development of artificial intelligence (AI), computational tools have been generated that have made it possible to handle unprecedented amounts of information, generating predictions that are increasingly closer to those obtained experimentally, giving much more value and weight to in silico assays. Homology annotation has been one of the most widely used methods for the functional annotation of peptides, especially enzymes, where the inference of new families of enzymes has been achieved, thanks to the comparison in the composition of their sequence with respect to one of known function. This method is based on the assumption that proteins with similar sequences will have similar functions. Homology annotation is especially useful for studying the sequence-function relationship of proteins with little available history or, as in the case of the rhomboids, recently discovered superfamilies, which differ significantly from those already characterised and even from each other. Here it was determined that, by means of this type of cutting-edge tools, work that in the past, there was much ambiguity between the predictions obtained, such as determining the number of transmembrane segments (TMD) or the conserved relationship in the amino acid sequence of groups with hundreds of proteins, is now more democratised for free access, even for users without greater experience or computer knowledge. For this, it was necessary to generate and debug a sequence similarity network, with the aim of interrogating these two enzymes, addressing the challenge of linking the functional information described to date with the sequence and structural similarities obtained, using a protein similarity network that allows such inspection but from a large-scale view of the family, with a special emphasis on plant counterparts, thinking of elucidating new functions not yet explored in plants of this type of enzyme.
Rhomboid proteases are the largest family of enzymes that hydrolyse peptide bonds within the hydrophobic environment of the cell membrane. Although they were discovered and classified as serine proteases less than 3 decades ago, they are already considered one of the best understood intramembrane proteases. Transforming the numerous members of the family, spread throughout all kingdoms of life, into potential regulators of complex processes within the cell; it is therefore not surprising that in sessile organisms such as plants, they are the ones with the most rhomboid homologues, giving indications that this superfamily of enzymes may have diversified their functions in plant cells, conserving at least the spatial arrangement that must be adopted to adapt to the different cell membranes. Therefore, a thorough understanding of its structure has always been a key objective for understanding its physiological role and may be a key to understanding regulated intramembrane proteolysis (RIP) and how it is involved in the homeostatic regulation of plant organisms. In the absence of experimental three-dimensional structures, there are several examples where computational prediction has generated great contributions in the prediction of new protein functions, thus, a suitable approach to compare the functionality of proteins belonging to the same family; such is the case of the 2 rhomboids of the model plant A.thaliana, AtRBL10 and AtRBL13. Thanks to the great advances in the development of artificial intelligence (AI), computational tools have been generated that have made it possible to handle unprecedented amounts of information, generating predictions that are increasingly closer to those obtained experimentally, giving much more value and weight to in silico assays. Homology annotation has been one of the most widely used methods for the functional annotation of peptides, especially enzymes, where the inference of new families of enzymes has been achieved, thanks to the comparison in the composition of their sequence with respect to one of known function. This method is based on the assumption that proteins with similar sequences will have similar functions. Homology annotation is especially useful for studying the sequence-function relationship of proteins with little available history or, as in the case of the rhomboids, recently discovered superfamilies, which differ significantly from those already characterised and even from each other. Here it was determined that, by means of this type of cutting-edge tools, work that in the past, there was much ambiguity between the predictions obtained, such as determining the number of transmembrane segments (TMD) or the conserved relationship in the amino acid sequence of groups with hundreds of proteins, is now more democratised for free access, even for users without greater experience or computer knowledge. For this, it was necessary to generate and debug a sequence similarity network, with the aim of interrogating these two enzymes, addressing the challenge of linking the functional information described to date with the sequence and structural similarities obtained, using a protein similarity network that allows such inspection but from a large-scale view of the family, with a special emphasis on plant counterparts, thinking of elucidating new functions not yet explored in plants of this type of enzyme.
Notas
Tesis (Ingeniero en Biotecnología)
Palabras clave
Proteínas, Análisis, Modelo, Arabidopsis Thaliana, Red de Similitud de Secuencia (SSN), Enzimología genómica, Modelado de Proteínas, Proteasas de Escisión Intramembrana (I-CLiP)