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[Protein engineering: from directed evolution to computational design].

Ge Qu1, Tong Zhu2, Yingying Jiang1

  • 1Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China.

Sheng Wu Gong Cheng Xue Bao = Chinese Journal of Biotechnology
|November 1, 2019
PubMed
Summary
This summary is machine-generated.

Computer-assisted protein design, including directed evolution and computational methods, is revolutionizing protein engineering. Artificial intelligence is further enhancing these techniques for novel enzyme development and improved protein functions.

Keywords:
artificial intelligencecomputational designenergy functionprotein engineeringsimulation of structure

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Area of Science:

  • Biochemistry
  • Protein Engineering
  • Computational Biology

Background:

  • Directed evolution is a leading strategy for protein design.
  • Computer-assisted protein design has advanced significantly due to increased computing power and algorithms.
  • Machine learning and AI are emerging as powerful tools in computational protein engineering.

Purpose of the Study:

  • To review the progress and applications of computer-assisted protein design.
  • To discuss current trends and future outlooks in the field of protein engineering.

Main Methods:

  • Construction of mutant libraries and high-throughput screening for directed evolution.
  • Protein structure simulation and energy function calculations for computational design.
  • Application of machine learning and artificial intelligence in protein engineering.

Main Results:

  • Computational design can modify enzyme substrate specificity and thermostability.
  • De novo design of artificial enzymes with desired functions is achievable.
  • Remarkable applications have arisen from AI integration in computational protein engineering.

Conclusions:

  • Computer-assisted protein design is a powerful and rapidly developing field.
  • The integration of AI promises further breakthroughs in protein engineering.
  • Future developments will likely focus on advanced computational and AI-driven approaches for novel protein functionalities.