Organocatalytic Coordination Microenvironment Design

Descripción del proyecto

Aprovechar las interacciones entre el catalizador y el entorno para ajustar la selectividad del catalizador

La capacidad de la naturaleza para generar una gran variedad de reacciones químicas con unos medios limitados es extraordinaria. Las enzimas lo consiguen valiéndose de su entorno, en lugar de alterar sus estructuras fundamentales. Por el contrario, la organocatálisis se ha centrado principalmente en modificar las estructuras de los catalizadores, a la vez que se ajustan las condiciones de reacción para compensar. El proyecto CATACOM, financiado por el Consejo Europeo de Investigación, potenciará el estudio de las interacciones dinámicas entre los catalizadores y sus microentornos. Los investigadores utilizarán técnicas avanzadas de aprendizaje profundo y métodos organocatalíticos experimentales para desentrañar los principios que subyacen a dichas interacciones. Una mejor comprensión de esta dinámica molecular permitirá a los investigadores mejorar la eficiencia y la selectividad de los organocatalizadores.

Objetivo

An overlooked aspect in organocatalyst design relates to nature’s ability to produce a multitude of biochemical products using only a limited number of mechanisms and building blocks. Rather than relying on structural modifications of the catalytically active unit, enzymatic structures primarily vary throughout the coordination microenvironment in which the active unit is embedded. This evolutionary structural principle boosts the number of compounds and reactions that can be efficiently realized by a catalytically active structural motif. In contrast, organocatalysis research has predominantly been focused on systematically modifying catalyst structures while relying on optimization of reaction conditions to provide a suitable microenvironment. Inspired by the breadth of reactions catalyzed by non-metal dependent enzymes, CATACOM aims to boost the efficiency of organocatalysts across a broad chemical space by the a-priori design of directed interactions with their microenvironment. This interdisciplinary research proposal has a computational and experimental component focused on: (1) unravelling the molecular design principles that govern dynamic and non-covalent interactions in organocatalysis using advanced deep learning techniques, (2) showcasing the value of our approach by studying organocatalytic reactions that present ongoing challenges in both efficiency and selectivity. Akin to the remarkable understanding being generated for enzymatic microenvironments, we will construct a representation of the three-dimensional structure formed through the interactions between organocatalytic reaction components by leveraging data on chemical interactions enshrouded in large structural databases. This structural understanding will revolutionize the design of organocatalytic systems by providing strong predictive power and will garner fundamental insight on dynamic and non-covalent interactions with implication across the chemical sciences.