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Pruebas virtuales aceleradas por GPU y simulaciones de dinámica molecular para la identificación de nuevos

Nathaly Vasquez-Martínez¹, Jonathan Trapala², Laura I Álvarez-Añorve¹

¹Departamento de Bioquímica, Facultad de Medicina, Universidad Nacional Autónoma de México, Ciudad de México 04510, México.

|February 9, 2026

Resumen

Métodos computacionales novedosos identificaron nuevos inhibidores de la dipeptidil peptidasa 4 (DPP-4) para la diabetes tipo 2. Los compuestos EPZ005687, OSU-03012 y bemcentinib muestran una alta eficacia y una mejor absorción celular en comparación con los medicamentos existentes.

Área de la Ciencia:

Química computacional y descubrimiento de medicamentos.
Farmacología y química medicinal.
Bioquímica y biología molecular.

Sus antecedentes:

La inhibición de la dipeptidil peptidasa 4 (DPP-4) es una estrategia clave para el manejo de la diabetes mellitus tipo 2 (DMT2).
Los inhibidores DPP-4 existentes pueden causar efectos adversos, lo que hace necesaria la búsqueda de alternativas más seguras.
Los enfoques computacionales ofrecen una vía prometedora para acelerar el descubrimiento de nuevos agentes terapéuticos.

Objetivo del estudio:

Identificar inhibidores novedosos, selectivos y más seguros de DPP-4 utilizando una tubería computacional integrada.
Para evaluar la afinidad de unión, la estabilidad y la permeabilidad celular de posibles fármacos candidatos.
Para demostrar la efectividad de un flujo de trabajo computacional para el descubrimiento de fármacos.

Principales métodos:

Aceleración de acoplamiento molecular por GPU de 30.699 compuestos contra el sitio activo DPP-4.
Simulaciones de dinámica molecular (100 ns) para evaluar la estabilidad de los complejos proteína-ligando.
Cálculos MM-GBSA para la afinidad de unión y muestreo general/MD para el análisis de la permeabilidad de la membrana.

Principales resultados:

Se identificaron EPZ005687, OSU-03012 y bemcentinib como candidatos prometedores para el inhibidor de la DPP-4.
Estos compuestos demostraron una afinidad de unión superior e interacciones favorables en comparación con la alogliptina.
EPZ005687, OSU-03012 y bemcentinib exhibieron una mayor permeabilidad celular sobre la alogliptina.

Conclusiones:

La estrategia computacional integrada acelera efectivamente el descubrimiento de agentes antidiabéticos potenciales.
EPZ005687, OSU-03012 y bemcentinib son candidatos prometedores para el desarrollo de tratamientos más seguros y efectivos para la DM2.
El filtrado riguroso de las bases de datos públicas combinado con el análisis computacional es crucial para identificar pistas viables de drogas.

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