Sequence and taxonomic feature evaluation facilitated the discovery of alcohol oxidases.

ABSTRACT: Recent advancements in data technology offer immense opportunities for the discovery and development of new enzymes for the green synthesis of chemicals. Current protein databases predominantly prioritize overall sequence matches. The multi-scale features underpinning catalytic mechanisms and processes, which are scattered across various data sources, have not been sufficiently integrated to be effectively utilized in enzyme mining. In this study, we developed a sequence- and taxonomic-feature evaluation driven workflow to discover enzymes that can be expressed in E. coli and catalyze chemical reactions in vitro, using alcohol oxidase (AOX) for demonstration, which catalyzes the conversion of methanol to formaldehyde. A dataset of 21 reported AOXs was used to construct sequen

SUBMITTER: Han Y 

PROVIDER: S-EPMC12083922 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature