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TiRNA: un método de grano grueso con efectos de temperatura e iones para el plegamiento y la predicción de la

Xunxun Wang¹, Zouchenyu Zhou¹, Shixiong Yu¹

¹Department of Physics and Key Laboratory of Artificial Micro & Nano-structures of Ministry of Education, School of Physics and Technology, Wuhan University, Wuhan 430072, China.

Nucleic acids research

|January 14, 2026

Resumen

Desarrollamos TiRNA, un nuevo método para predecir estructuras y estabilidad del ARN en soluciones. TiRNA predice con precisión el plegamiento y la estabilidad térmica del ARN a partir de secuencias o estructuras secundarias, superando a los métodos existentes.

Sus antecedentes:

Las moléculas de ARN realizan funciones biológicas vitales, incluida la regulación génica y la catálisis.
La estructura y la estabilidad del ARN son cruciales para la función, pero son sensibles a las condiciones iónicas.
La predicción de las estructuras y la estabilidad del ARN en soluciones iónicas sigue siendo un desafío importante.

Conclusiones:

TiRNA ofrece un enfoque robusto y preciso para simular el plegamiento del ARN y predecir estructuras 3D y estabilidad térmica en soluciones iónicas.
La capacidad del método para utilizar la secuencia o la estructura secundaria como entrada mejora su versatilidad.
TiRNA representa un avance significativo en las herramientas computacionales para la investigación de la estructura y la función del ARN.

Palabras clave:

ARN plegamiento de ARN predicción de estructura de ARN estabilidad térmica del ARN simulación de ARN método de grano grueso efectos iónicos efectos de temperatura biología computacional bioquímica

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