Artificial intelligence makes enzyme engineering easy

We revealed that the redox cofactor preference of malic enzymes can be strikingly converted by applying phylogenetic analysis to machine learning, without experimental screening. This method can predict mutation positions and candidate amino acids that affect substrate specificity, which is challenging to infer solely from the crystal structures. Machine learning uses the structurally homologous but functionally distinct enzymes' amino acid sequences as input datasets to efficiently navigate toward the target function, and potentially provide new fundamental insights into enzyme–substrate specificity. Osaka, Japan – You can't expect a pharmaceutical scientist to switch labs to the facilities available in a television studio and expect the same research output. Enzymes behave exactly the same.