Biocatalysis is important in the discovery, development, and manufacture of pharmaceuticals. However, the identification of enzymes for target transformations of interest requires major screening efforts. Here, we report a structure-based computational workflow to prioritize protein sequences by a score based on predicted activities on substrates, thereby reducing a resource-intensive laboratory-based biocatalyst screening. We selected imine reductases (IREDs) as a class of biocatalysts to illustrate the application of the computational workflow termed IREDFisher. Validation by using published data showed that IREDFisher can retrieve the best enzymes and increase the hit rate by identifying the top 20 ranked sequences. The power of IREDFisher is confirmed by computationally screening 1400 sequences for chosen reductive amination reactions with different levels of complexity. Highly active IREDs were identified by only testing 20 samples in vitro. Our speed test shows that it only takes 90 min to rank 85 sequences from user input and 30 min for the established IREDFisher database containing 591 IRED sequences. IREDFisher is available as a user-friendly web interface (https://enzymeevolver.com/IREDFisher). IREDFisher enables the rapid discovery of IREDs for applications in synthesis and directed evolution studies, with minimal time and resource expenditure. Future use of the workflow with other enzyme families could be implemented following the modification of the workflow scoring function.
Yuqi Yu is a computational structural biologist in antibody discovery based at AstraZeneca in the UK. She earned her Ph.D. in computer-aided drug design from the prestigious Shanghai Institute of Materia Medica in China. Following her doctoral studies, Yuqi embarked on her first postdoctoral research at KU Leuven, where she focused on investigating the structure-activity relationship of small molecules for pancreatic cancer. Her scientific journey then took her to the University of Manchester for her second postdoctoral position under the mentorship of Professor Nigel Scrutton and Nicholas Turner. During this time, she applied computational tools to conduct in silico enzyme screening and engineering, specifically in the realm of imine reductases. Yuqi developed an automated structure-based in silico workflow, IREDFisher, designed for pre-screening enzymes in chiral amine synthesis. Then Yuqi joined AstraZeneca in Cambridge as a senior scientist. In her current role, she is actively involved in predicting antibody affinity using state-of-the-art structure-based machine learning and deep learning approaches.
