Chinese intelligent manufacturing 'Manus' has emerged! How will AI agents improve the efficiency of biological reactions?
AI Agent is an intelligent system that can autonomously perceive the environment, process information, make decisions, and execute actions.
It combines perception, reasoning, learning, and action abilities, with the goal of simulating intelligent human or biological behavior, even surpassing human performance in specific tasks.
At present, there have been many typical cases of successfully using AI agents to improve the efficiency of biological reactions.
The most significant achievement is that the AlphaFold project of DeepMind, which focuses on protein structure prediction and drug development, has achieved high-precision prediction of protein three-dimensional structures through deep learning algorithms, reducing the originally time-consuming experiments to days or even hours.
This breakthrough has accelerated drug target recognition and molecular design, greatly improving the efficiency of new drug development. Alphafold software can predict protein folding and drug interactions, providing critical support for cancer and Alzheimer's disease treatment.
Why is AI driven culture medium design the trend of the future?
Another typical case is that on February 13, 2025, Nobel laureate David Baker's team from the University of Washington published a study in the journal Science.
They used AI to design serine hydrolases with complex active sites from scratch, and the specific steps are as follows:
1. Active site generation: By optimizing the transition state geometry structure through quantum mechanics, a geometric description of the active site of serine hydrolase is generated.
2. Protein skeleton generation: Use RF diffusion to generate protein skeletons from random noise, ensuring that they match the geometric structure of the input active site.
3. Sequence design: Use LigandMPNN to design protein sequences and optimize them using Rosetta FastRelax.
4. Filtering and screening: AlphaFold2 was used to predict the structure of the designed enzyme, and PLACER was used to generate a set of structures for each step in the reaction pathway to evaluate the degree of pre organization of active sites, significantly improving the success rate of the design.
5. Experimental verification: Screening and characterizing the function of the designed enzyme through experiments, including catalytic efficiency, crystal structure, etc.
This enzyme can accelerate a four step chemical reaction with a catalytic efficiency (kcat/Km) of up to 2.2 × 105 M-1 s-1, which is 60000 times higher than similar enzymes previously designed.
In the future, AI agents will demonstrate their abilities in the fields of biological reactions and fermentation amplification.
Firstly, in terms of fermentation monitoring, AI agents can efficiently monitor the status of experimental equipment, warn of faults, and optimize resource allocation.
Secondly, in terms of industrial fermentation control, AI agents coordinate bioreactor parameters, intelligently supplement dissolved oxygen, and improve fermentation efficiency.
Thirdly, in terms of fermentation amplification, AI agents can provide one-stop fermentation amplification solutions according to customer needs, becoming true AI experts.
Fourthly, in terms of biological response big data, AI agents can intelligently analyze, provide optimization suggestions, and provide users with decision-making basis.
Bailun Biotechnology is vigorously promoting research related to "AI Agent+Biological Reaction" and will launch testing as soon as possible!
