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Synthetic biology is an interdisciplinary science that involves using principles from disciplines such as engineering, molecular biology, cell biology, and systems biology. It involves remodeling existing organisms from nature or constructing completely new synthetic organisms for applications such as protein or enzyme production, bioremediation, value-added macromolecule production, and the addition of desirable traits to crops, to name a few.
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An important concept in studying metabolism and energy is that of chemical equilibrium. Most chemical reactions are reversible. They can proceed in both directions, releasing energy into their environment in one direction, and absorbing it from the environment in the other direction. The same is true for the chemical reactions involved in cell metabolism, such as the breaking down and building up of proteins into and from individual amino acids, respectively. Reactants within a closed system...
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Microorganisms rely on proteins as an essential carbon and energy source, particularly in environments with limited polysaccharides or lipids. However, proteins are too large to cross the plasma membrane unaided, necessitating enzymatic degradation. Microbes secrete extracellular proteases and peptidases that hydrolyze proteins into peptides, which can then be transported across the membrane. Once inside the cell, intracellular proteases degrade these peptides into free amino acids, which...
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以人工智能为动力,用于蛋白质工程和代谢工程的生物基础设施.

Junyu Chen1, Nilmani Singh2, Jingxia Lu3

  • 1Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL 61801, United States; Carl R. Woese Institute for Genomic Biology, University of Illinois Urbana-Champaign, Urbana, IL 61801, United States; DOE Center for Advanced Bioenergy and Bioproducts Innovation, University of Illinois Urbana-Champaign, Urbana, IL 61801, United States.

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合成生物学利用人工智能 (AI) 和自动化生物工厂来加速蛋白质和代谢工程. 这种转变使得自主实验成为可能,推动了合成生物学领域的创新.

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科学领域:

  • 合成生物学 合成生物学
  • 人工智能的人工智能是人工智能.
  • 生物基础公司 (Biofoundries)

背景情况:

  • 合成生物学正在迅速发展.
  • 人工智能 (AI) 和自动化生物基础设施的整合是关键的发展.
  • 这种融合改变了传统的实验方法.

研究的目的:

  • 审查人工智能和生物基础集成在合成生物学方面的最新进展.
  • 为了突出对蛋白质和代谢工程的影响.
  • 强调加速科学发现的潜力.

主要方法:

  • 审查人工智能驱动的生物基础设施的工作流程的发展.
  • 对生物应用的AI模型的分析.
  • 检查人工智能和生物基础设施之间的整合策略.

主要成果:

  • 人工智能和生物基础加速了设计-构建-测试-学习循环.
  • 自动化将工程从手动实验转移到自动实验.
  • 在自动化蛋白质和代谢工程方面取得了重大进展.

结论:

  • 由人工智能驱动的生物基础设施正在彻底改变合成生物学.
  • 自主实验提高了效率和速度.
  • 这种整合有望加速创新和发现.