An Effective Computational Strategy for UGTs Catalytic Function Prediction

The GT-B type glycosyltransferases
play a crucial post-modification
role in synthesizing natural products, such as triterpenoid and steroidal
saponins, renowned for their diverse pharmacological activities. Despite
phylogenetic analysis aiding in enzyme family classification, distinguishing
substrate specificity between triterpenoid and steroidal saponins,
with their highly similar cyclic scaffolds, remains a formidable challenge.
Our studies unveil the potential transport tunnels for the glycosyl
donor and acceptor in PpUGT73CR1, by molecular dynamics simulations.
This revelation leads to a plausible substrate transport mechanism,
highlighting the regulatory role of the N-terminal domain (NTD) in
glycosyl acceptor binding and transport. Inspired by these structural
and mechanistic insights, we further analyze the binding pockets of
44 plant-derived UGTs known to glycosylate triterpenes and sterols.
Notably, sterol UGTs are found to harbor aromatic and hydrophobic
residues with polar residues typically present at the bottom of the
active pocket. Drawing inspiration from the substrate binding and
product release mechanism revealed through structure-based molecular
modeling, we devised a fast sequence-based method for classifying
UGTs using the pre-trained ESM2 protein model. This method involved
extracting the NTD features of UGTs and performing PCA clustering
analysis, enabling accurate identification of enzyme function, and
even differentiation of substrate specificity/promiscuity between
structurally similar triterpenoid and steroidal substrates, which
is further validated by experiments. This work not only deepens our
understanding of substrate binding mechanisms but also provides an
effective computational protocol for predicting the catalytic function
of unknown UGTs.