In the past two decades, synthetic biology has made breakthroughs in the construction of biocircuits, the standardization of biological elements and the development of various genomic/metabolic engineering tools and approaches. Its rapid development is changing the industrial layout of biotechnology industry. At present, synthetic biotechnology has been widely used in many fields such as natural product synthesis, medicine, energy and industry. Pharmaceutical demands have also driven its development, including the application of in vitro catalytic technology in the green manufacturing of chiral pharmaceutical chemicals and the integration of heterologous pathways into designer cells to efficiently produce medicines and so on. Synthetic biology, with its more economical and environmentally friendly features, will subvert some traditional pharmaceutical manufacturing methods. This article reviews the applications of synthetic biology in the green manufacturing of chiral pharmaceutical chemicals and the biological manufacturing of natural plant products.

Traditional Chinese medicine, primarily based on medicinal plants, has been used for thousands of years in China and has made significant contributions to the health and proliferation of the Chinese nations. The bioactive compounds are the pharmaceutical basis for Chinese medicine. The identification of the composition of active components in Chinese medicine and the establishment of their green, low-cost manufacturing technoogies would play key roles in the promotion of the modernization of Chinese medicine. The recent development of synthetic biology not only provides new avenues for the green, low-cost and large-scale production of bioactive components of Chinese medicine but also offers technical support and necessary compounds for clarifying the composition of active components and their pharmacological mechanisms. This article reviews the development and application of synthetic biology in the production of bioactive components of Chinese medicine, such as artemisinin, ginsenosides and icaritin, and the potential roles of synthetic biology in promoting the modernization of Chinese medicine.

Proteins, the intricate “molecular machines” that orchestrate life’s processes, hold immense potential for therapeutic applications. However, the designing and engineering of these proteins towards desired properties and functions remain a formidable challenge due to the complex interplay between the amino acid sequence, the three dimensional structure, and biological function. Artificial intelligence (AI) has been making transformative strides in various fields and its combination with protein engineering techniques offers a powerful toolkit in generating novel proteins for synthetic biology and therapeutics development. In this review, we will discuss the advancements and applications of AI in protein modeling and design and highlight the challenges and outlook of its applications.

The research progress in the biosynthesis of ursodeoxycholic acid with hydroxysteroid dehydrogenase as the core element in recent years is reviewed, and the challenges and future research directions for further development of this technology are proposeed, aiming to provide reference for the ursodeoxycholic acid biosynthesis.

Protein drugs have the advantages of strong targeting, clear mechanism of action and fewer adverse reactions, so they have great application prospects in clinic. The stability of protein is one of the most important properties of protein drugs, which is crucial for drugs’ efficacy, safety and stability. In recent years, protein engineering assisted by artificial intelligence (AI) has been developed into an efficient strategy for protein molecular design, and has been widely used in protein stability prediction, drug design and antibody optimization. In this paper, we introduce several major methods of AI-assisted protein stability optimization, discuss their advantages and disadvantages and their applications in protein drug design and optimization. We also discuss the challenges and prospects of AI in protein stability design. We hope this paper will provide new ideas for researchers to develop more stable and efficient protein drugs.