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Tácticas de optimización multiobjetivo basadas en datos para reacciones asimétricas catalíticas utilizando ligandos

Jordan J Dotson¹, Lucy van Dijk¹, Jacob C Timmerman²

¹Department of Chemistry, University of Utah, Salt Lake City, Utah 84112, United States.

Journal of the American Chemical Society

|December 27, 2022

Resumen

Este estudio introduce un enfoque de aprendizaje automático para optimizar los catalizadores con ligandos quirales de bisfosfina. El método mejoró con éxito múltiples objetivos de reacción, como rendimiento y selectividad, en síntesis farmacéutica.

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Área de la Ciencia:

Catálisis
Química orgánica
Química computacional

Sus antecedentes:

La optimización simultánea de múltiples objetivos de reacción (rendimiento, enantioselectividad, regioselectividad) en la catálisis es un desafío.
Los ligandos de bisfosfina quiral juegan un papel crucial en el control de la selectividad en la síntesis asimétrica.

Objetivo del estudio:

Desarrollar y demostrar un flujo de trabajo de aprendizaje automático para la optimización multiobjetivo de reacciones catalíticas utilizando ligandos quirales de bisfosfina.
Mejorar el rendimiento, la enantioselectividad y la regioselectividad en reacciones secuenciales para la síntesis de ingredientes farmacéuticos activos.

Principales métodos:

Construcción de una base de datos derivada de la teoría funcional de la densidad de más de 550 ligandos de bisfosfina.
Desarrollo de una técnica de mapeo químico de diseño.
Aplicación de métodos de clasificación para identificar catalizadores activos y regresión lineal para modelar la selectividad de las reacciones.

Principales resultados:

Predicción y validación experimental de nuevos ligandos con un rendimiento significativamente mejorado en todos los objetivos de reacción.
Se ha demostrado la optimización exitosa de dos reacciones secuenciales en síntesis asimétrica.
Identificó una estrategia generalizable para la optimización del catalizador controlada por ligandos de bisfosfina.

Conclusiones:

El flujo de trabajo de aprendizaje automático proporciona una estrategia efectiva para la optimización de múltiples objetivos en la catálisis.
Este enfoque puede implementarse fácilmente para reacciones en las que los ligandos de bisfosfina dictan el rendimiento.
Los hallazgos avanzan en el desarrollo de vías de síntesis asimétricas eficientes.