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Explorando la simetría como una vía para el diseño computacional de grandes dominios de proteínas

Carie Fortenberry¹, Elizabeth Anne Bowman, Will Proffitt

¹Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37235, United States.

Journal of the American Chemical Society

|October 8, 2011

Resumen

Los investigadores diseñaron computacionalmente una proteína simétrica (FLR) que adopta un superdoblamiento de barril TIM. Esta proteína diseñada, cuando se divide, forma fácilmente un homodímero estable, avanzando los principios de diseño de la proteína.

Área de la Ciencia:

Biología estructural Biología estructural.
Diseño computacional del diseño de proteínas.
La bioquímica es la bioquímica.

Sus antecedentes:

Las proteínas simétricas y homodiméricas son abundantes en la naturaleza debido a su favorabilidad energética.
Se propone que los superpliegues simétricos hayan evolucionado a partir de la duplicación de genes y la fusión de homodímeros simétricos.

Objetivo del estudio:

Para diseñar computacionalmente una variante de proteína perfectamente simétrica y su homodímero utilizando el software ROSETTA.
Investigar los principios de la estabilidad de las proteínas y la construcción in silico de los dominios de proteínas.

Principales métodos:

Utilizado el software de diseño de proteínas ROSETTA para ingeniería computacional.
Se empleó cristalografía para verificar la simetría de la proteína en detalle atómico.
Investigó el comportamiento de dimerización de la proteína diseñada.

Principales resultados:

Se ha diseñado con éxito una proteína monomérica soluble (FLR) que adopta un superplegado simétrico (βα) 8 de barril TIM.
FLR exhibe una doble simetría en la disposición de la estructura secundaria, la secuencia y el detalle atómico.
La proteína diseñada se dimeriza fácilmente al dividirse, formando el homodímero simétrico deseado.

Conclusiones:

El diseño computacional de FLR demuestra el progreso en la comprensión de los principios de estabilidad de las proteínas.
Presenta una estrategia viable para la construcción in silico de dominios de proteínas más grandes a partir de unidades más pequeñas.
Destaca el potencial de los métodos computacionales en el diseño de proteínas de novo.

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