Schematic representation of Kcat’s Technology used to derive variants to achieve kg level substrate conversion with desired regioselectivity, stereospecificity, and enantiomeric excess. A system of Micrometer size with higher enzyme and substrate concentrations at varying pH, temperature, cofactor, co-substrate, and solvent conditions is simulated for microseconds.
Information Capturing Technologies:
A 7th Dimensional Grid made of Quantum beads that captures information across the reaction system
Cryptic Interactions & Cryptic Pockets
Induced Substrate diffusion path and thermodynamics based product exit path
De novo active site design using Suspended probes and fluid models
FMO-DFT based long-range QM/MM simulation to identify transition states
Deep Learning uses convolution neural networks constructed from a database of enzymes & mutations to derive enzyme variants to achieve kg level substrate conversion
Enzyme Control Flux Analysis technology with Deep Learning using convolution neural networks