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Author Spotlight: Optimizing Apoplast Protein Extraction for Efficient Recovery of Recombinant Proteins from Plant Cells
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Artificial intelligence-driven systems engineering for next-generation plant-derived biopharmaceuticals.

Subramanian Parthiban1, Thandarvalli Vijeesh1, Thashanamoorthi Gayathri1

  • 1Plant Genetic Engineering Laboratory, Department of Biotechnology, Bharathiar University, Coimbatore, India.

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Plant molecular pharming uses plants to produce biopharmaceuticals. Artificial intelligence (AI) and synthetic biology can overcome challenges like protein instability and improve yield for therapeutic applications.

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Area of Science:

  • Biotechnology
  • Plant Sciences
  • Bioengineering

Background:

  • Recombinant biopharmaceuticals are crucial for vaccines, diagnostics, and therapeutics.
  • Plant molecular pharming offers scalable, cost-effective production with reduced contamination risks.
  • Challenges in plant-based production include non-human post-translational modifications and protein instability.

Purpose of the Study:

  • To review the integration of artificial intelligence (AI) and synthetic biology in plant molecular pharming.
  • To explore AI-driven strategies for overcoming limitations in plant-based recombinant protein production.
  • To highlight AI's role in optimizing protein properties and host engineering for enhanced biopharmaceutical manufacturing.

Main Methods:

  • Review of AI algorithms (neural networks, support vector machines, etc.) for protein engineering.
  • Application of synthetic biology tools for plant-based glycan engineering.
  • Integration of systems engineering approaches with AI for protein and host optimization.

Main Results:

  • AI can predict and validate protein structures, optimizing properties like thermostability and antibody affinity.
  • AI-driven glycan engineering enhances protein folding, stability, and catalytic activity.
  • Combined AI and synthetic biology approaches significantly improve yield and stability of plant-produced biopharmaceuticals.

Conclusions:

  • AI and synthetic biology are vital for advancing plant molecular pharming.
  • These technologies offer solutions to current limitations, enabling efficient production of complex biopharmaceuticals.
  • Optimized plant-based production systems are essential for meeting the growing demand in the therapeutics market.