Design of Synthetic Biomolecular Condensates for Metabolic Engineering
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Design of Synthetic Biomolecular Condensates for Metabolic Engineering

Biometabolic engineering has great potential for the sustainable supply of a variety of valuable products, including fine chemicals, fuels, pharmaceuticals, and materials. However, manufacturing efficient cell factories for biosynthesis is challenging. Based on building blocks and genetic tools, CD BioSciences offers comprehensive services to design and construct synthetic biomolecular condensates with responsive properties and on-demand functions in bacteria and eukaryotic cells. These synthetic compartments act as microbial cell factories to produce complex chemicals. Synthetic biomolecular condensates offer unique advantages in metabolic engineering in that they aggregate or exclude specific metabolic enzymes within the cell and are unlikely to adversely affect cellular function and are not regulated by endogenous mechanisms.

Fig. 1. Synthetic condensates for metabolic engineering.Fig. 1. Synthetic condensates for metabolic engineering. (Qian Z G, et al., 2022)

Customized Services

CD BioSciences is a leading company focused on biological research and innovation, offering comprehensive services to design synthetic biomolecular condensates for metabolic engineering applications. Our solutions improve the biosynthesis of metabolites of interest with precision and efficiency, leading to the sustainable production of valuable compounds. With our extensive expertise and state-of-the-art technology, we offer tailored solutions to meet the diverse needs of our clients.

By combining advanced technologies, computational modeling, and in-depth knowledge of cellular metabolism, we aim to enhance the biosynthesis of a wide range of valuable products. Our synthetic biomolecular condensates are widely used in the following areas of metabolic engineering:

  • Improving Enzymatic Reaction Rates
    We offer custom-designed synthetic biomolecular condensates that accelerate enzymatic reactions by lowering the scaffold-dependent substrate Mie constant (Km), further optimizing metabolic fluxes and increasing the yield of desired compounds.
  • Reaction Pathway Optimization
    The complexity of metabolic pathways often has multiple branches. CD BioSciences utilizes synthetic biomolecular condensates for the post-translational compartmentalization of pathway enzymes. This strategy allows dynamic regulation of enzyme clusters, enabling precise control of metabolic fluxes.
  • Mitigating Cytotoxicity
    We can encapsulate enzymes with toxic intermediates in synthetic biomolecule condensates. This strategy prevents their excessive accumulation and minimizes cytotoxicity, helping to produce valuable compounds in a safe and efficient manner.

With comprehensive services and a team of highly skilled experts, CD BioSciences is committed to revolutionizing the production of valuable compounds from fine chemicals to pharmaceuticals through the application of synthetic condensates. Our innovative approach harnesses the power of anabolic organelles and post-translational compartmentalization, enabling improved enzymatic rates, pathway optimization, and toxicity mitigation.

CD BioSciences plays a key role in advancing sustainable and efficient biosynthesis. Our commitment to innovation, scientific excellence, and customer satisfaction makes us an ideal partner for organizations seeking to harness the potential of synthetic biomolecular condensates for metabolic engineering applications. Contact us today to embark on a transformative journey to optimize the production of valuable compounds through the design of synthetic biomolecular condensates.

Reference

  1. Qian Z G, Huang S C, Xia X X. (2022) Synthetic protein condensates for cellular and metabolic engineering[J]. Nature Chemical Biology, 1-11.
For research use only, not intended for any clinical use.
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CD BioSciences is a company conducting biomolecular condensates targeted innovative drugs. We integrate the latest advances in physics, chemistry, biology, and machine learning to address some of the most fundamental challenges in health and disease today.

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