SOURCE-LINKED INTELLIGENCE

Organocatalytic Coordination Microenvironment Design

CORDIS · observation · Publication date unknown

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. organocatalysis, machine learning, non-covalent interactions, dynamic covalent interactions

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recordType

award

status

SIGNED

region

EU

value

2999998

unit

EUR