De novo computational design using RFD2-MI with explicit modeling of the catalytic water molecule enables creation of zinc metalloproteases that achieve >10^8-fold rate acceleration over uncatalyzed peptide bond hydrolysis with 36% success rate, exhibit emergent substrate specificity through two-sided design, and can be reprogrammed to cleave disease-relevant human proteins including aggregation-prone TDP-43.

Although significant progress has been made in creating de novo metalloenzymes that hydrolyze activated esters, the energetically demanding cleavage of amide bonds has remained a major challenge for enzyme design: amide bonds are significantly more stable than ester bonds, the amine leaving groups in proteins are not activated, and peptide substrates are flexible making them difficult to bind precisely. Here, we report the de novo design of zinc proteases from minimal catalytic motifs using a fine-tuned version of RoseTTAFold Diffusion 2, called RoseTTAFold Diffusion 2 for Molecular Interfaces, optimized for both enzyme and protein-protein interaction design. In a single one-shot design round of 135 designs, 36% of the designs had activity and cleaved precisely at the intended site. The most active design accelerated peptide bond hydrolysis more than 10-fold over the uncatalyzed reaction. These results demonstrated that de novo enzyme design has advanced well beyond model reactions with activated substrates, and open the door to design of proficient metallohydrolases for medicine and bioremediation.