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Updated: Feb 22, 2026

A Protocol for Computer-Based Protein Structure and Function Prediction

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

SwinSite: Predicción de sitios de unión de ligandos de proteínas basada en estructura 3D utilizando un modelo

Dongwoo Kim¹, Juyong Lee^1,2,3

¹College of Pharmacy, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Republic of Korea.

Journal of chemical information and modeling

|February 20, 2026

Resumen

SwinSite, un marco novedoso de aprendizaje profundo, predice con precisión los sitios de unión de ligandos utilizando un enfoque híbrido de CNN 3D y transformador de visión. Este método mejora el descubrimiento de fármacos basado en la estructura al mejorar la identificación de los bolsillos de unión cruciales.

Sus antecedentes:

La identificación precisa de los sitios de unión de ligandos de proteínas es fundamental para el descubrimiento de fármacos basado en la estructura.
Los métodos computacionales existentes, incluidos los CNN y GNN, tienen limitaciones para predecir eficazmente los sitios de unión.

Conclusiones:

SwinSite representa un avance significativo en los enfoques computacionales para identificar sitios de unión de ligandos de proteínas.
La arquitectura híbrida del marco ofrece una precisión y confiabilidad mejoradas para las canalizaciones de descubrimiento de fármacos basadas en la estructura.
SwinSite tiene el potencial de acelerar la identificación de candidatos a fármacos al predecir con mayor precisión las interacciones de unión.

Palabras clave:

aprendizaje profundo predicción de sitios de unión descubrimiento de fármacos CNN 3D transformador de visión biología estructural bioinformática

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