EQS-News: Sino Biological's Cell-Free Protein Synthesis Supports Tencent AI for Life Sciences Lab's Protein Design Study Published in Nature Communications
Source: EQS|
Bridging AI Protein Design and Experimental Validation Artificial intelligence has significantly accelerated protein amino acid sequence design, however, translating these computational designs into functional proteins remains a key challenge in protein engineering. Protein activity, stability, folding, and expression are influenced by complex structural and biochemical factors, often leading to discrepancies between in silico predictions and experimental outcomes. To address this gap, the study introduced an Ontology Reinforcement Iteration (ORI) framework, integrating protein ontology with reinforcement learning from wet-lab feedback. Experimental data, including protein expression levels and functional activity, were continuously fed back into the model enabling iterative optimization of protein sequences and improved design accuracy. Cell-Free Protein Synthesis Accelerates the The researchers subsequently utilized Sino Biological’s XPressMAX™ Cell-Free Protein Synthesis Kit to enable rapid protein expression and functional screening. Protein-coding sequences cloned into the kit’s expression vector and added to the proprietary cell-free reaction system supported rapid design–build–test cycles. Using this workflow, the team engineered a lysozyme with over 100-fold higher activity than the natural enzyme, developed a thermostable chitinase retaining activity at 85°C, and successfully expressed bifunctional enzymes with improved performance compared with naturally occurring multifunctional enzymes. XPressMAX™Cell-Free Protein Synthesis Kit Key features include:
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| Language: | English |
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| ISIN: | CNE100004Q23 |
| EQS News ID: | 2335390 |
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2335390 28.05.2026 CET/CEST