Computational design of metalloproteases
Researchers computationally designed novel zinc proteases from minimal catalytic motifs that efficiently and precisely hydrolyze peptide bonds, accelerating the reaction over 10^8-fold.
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The paper studies de novo computational design of zinc metalloproteases capable of hydrolyzing peptide amide bonds, a challenge because amide bonds are more stable than activated ester bonds and peptide substrates are flexible. Using a fine-tuned RoseTTAFold Diffusion 2 model for molecular interfaces, the authors generated 135 designs in a single design round and found 36% had enzymatic activity that cleaved precisely at the intended site, with the top design accelerating peptide bond hydrolysis more than 108-fold versus the uncatalyzed reaction. The authors’ main caveat is not explicitly stated in the provided text, though the results are framed around computational design and reported activity among designed candidates rather than broad applicability. This paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.
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- europepmc
- last seen: 2026-05-20T01:45:00.602351+00:00
- unpaywall
- last seen: 2026-05-26T02:00:01.498150+00:00