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Updated: Mar 21, 2026

Identification and Classification of Position-specific GABAA Receptor Subunit Missense Variants for Their Role In Hippocampal Pyramidal Neurons
Published on: June 6, 2025
PHA synthase variant design using a conditional variational autoencoder
Tuula Tenkanen1, Anna Ylinen1, Paula Jouhten2
1VTT Technical Research Centre of Finland Ltd., Espoo, Finland.
Abstract:
Polyhydroxyalkanoate (PHA) synthases are a group of complex, dimeric enzymes which catalyze polymerization of R-hydroxyacids into PHAs. PHA properties depend on their monomer composition but enzymes found in nature have limited specificities to certain R-hydroxyacids only. In this study, a conditional variational autoencoder was used for the first time to design novel PHA synthases. The model was trained with native protein sequences obtained from Uniprot and was used for the creation of approximately 10 000 new PHA synthase enzymes. Out of these, 16 sequences were selected for in vivo validation. The selection criteria included the presence of conserved residues such as catalytic amino acids and amino acids in the dimer interface and structural features like the number of [Formula: see text]-helices in the N-terminal part of the enzyme. Two of the 16 novel PHA synthases that had substantial numbers of amino acid substitutions (87 and 98) with respect to the most similar native enzymes were confirmed active and produced poly(hydroxybutyrate) (PHB) when expressed in yeast S. cerevisiae. The results show the power of AI based methods to create active variants of highly complex dimer enzymes.
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