Enzyme Discovery: Enzyme Selection and Pathway Design

High-throughput prediction of enzyme promiscuity based on substrate-product pairs

The screening of enzymes for catalyzing specific substrate-product pairs is often constrained in the realms of metabolic engineering and synthetic biology. Existing tools based on substrate and reaction similarity predominantly rely on prior knowledge, demonstrating limited extrapolative capabilities and an inability to incorporate custom candidate-enzyme libraries. Addressing these limitations, we have developed the Substrate-product Pair-based Enzyme Promiscuity Prediction (SPEPP) model. This innovative approach utilizes transfer learning and transformer architecture to predict enzyme promiscuity, thereby elucidating the intricate interplay between enzymes and substrate-product pairs. SPEPP exhibited robust predictive ability, eliminating the need for prior knowledge of reactions and allowing users to define their own candidate-enzyme libraries. It can be seamlessly integrated into various applications, including metabolic engineering, de novo pathway design, and hazardous material degradation. To better assist metabolic engineers in designing and refining biochemical pathways, particularly those without programming skills, we also designed EnzyPick, an easy-to-use web server for enzyme screening based on SPEPP. EnzyPick is accessible at http://www.biosynther.com/enzypick/.

Cell-Free Biosynthesis System: Methodology and Perspective of in Vitro Efficient Platform for Pyruvate Biosynthesis and Transformation

The modification of intracellular metabolic pathways by metabolic engineering has generated many engineered strains with relatively high yields of various target products in the past few decades. However, the unpredictable accumulation of toxic products, the cell membrane barrier, and competition between the carbon flux of cell growth and product synthesis have severely retarded progress toward the industrial-scale production of many essential chemicals. On the basis of an in-depth understanding of intracellular metabolic pathways, scientists intend to explore more sustainable methods and construct a cell-free biosynthesis system in vitro. In this review, the synthesis and application of pyruvate as a platform compound is used as an example to introduce cell-free biosynthesis systems. We systematically summarize a proposed methodology workflow of cell-free biosynthesis systems, including pathway design, enzyme mining, enzyme modification, multienzyme assembly, and pathway optimization. Some new methods, such as machine learning, are also mentioned in this review.