Horst Lechner

This paper introduces Riff-Diff, a machine learning and atomistic modeling method for designing enzymes with high catalytic activity and stereoselectivity, demonstrating its effectiveness for two chemical reactions.

The paper designs and characterizes a thermostable α-helical barrel protein with tunable active-site positioning, showing improved catalytic efficiency.

The paper describes an artificial cofactor using designed streptavidin to catalyze the Baylis-Hillman reaction with increased activity.