Antimicrobial peptides (AMPs) are small molecule active peptides with broad-spectrum antimicrobial effects, which are not only resistant to acids and alkalis, tumors, and viruses, but also not easy to develop drug resistance, and have a wide range of prospects for application in the fields of pharmaceuticals, food, agriculture, and beauty care.
However, due to their short sequences, high diversity, and low similarity, the research of antimicrobial peptides still needs to resort to repeated experimental validation to a large extent. Therefore, to develop new antimicrobial peptides or improve existing ones, AI prediction mining is an effective means.
However, AI prediction and mining models for antimicrobial peptides are limited in the market, and efficient and convenient AI tools are urgently needed to realize breakthroughs. Tidetron Tao automated R&D platform covers all aspects of the synthetic biology DBTL cycle, and Striker Bio has accumulated rich R&D experience and massive data in the field of small-molecule functional peptides, which lays a solid foundation for AI prediction of active peptides.
The R&D team of Stochastic Bio integrates and optimizes advanced technologies and algorithms such as ChatGPT, AlphaFold, Progen, etc. (Comparing and Optimizing Multiple DEep Learning), gradually formed a unique algorithmic logic layer to quickly build the active peptide AI prediction and mining model TIDETRON COMDEL.
As far as antimicrobial peptides are concerned, in addition to the tens of thousands of antimicrobial peptides in the existing database, TIDETRON COMDEL has also collected more than 2,000 antimicrobial peptide data obtained by independent high-throughput screening of Striking Bio, which basically covers all the antimicrobial peptide species on the market. Advanced algorithms combined with massive data continuously optimize the model, which makes the design and prediction accuracy of antimicrobial peptides to reach the cutting-edge level of the industry and achieve a new breakthrough.
In addition, TIDETRON COMDEL is easy and fast to operate. Users only need to fill in the basic sequence information to get the probability that the sequence is an antimicrobial peptide, which greatly reduces the time and labor cost of screening.
Through the prediction of antimicrobial peptides, TIDETRON COMDEL can not only assist in guiding and screening the target substances, but also help to realize its enhancement in end-use applications.
In addition to antimicrobial peptides, immunomodulatory peptides, cell signaling peptides and other active peptides have different efficacies, but the underlying prediction logic has some similarities. tidetron comdel has already laid out the development of prediction models for more than 10 active peptides, and is exploring the infinite possibilities of AI for Synbio.
Currently TIDETRON COMDEL is just a small step for AI-enabled synthetic biology, but its generalized migration ability is expected to break through the application boundaries, and a big step will be taken in the future for predictive research in the areas of structure, activity, function, target, application, and yield.
In fact, not only protein prediction, the Tidetron Tao AI engine built by Ecotron Bio has guiding significance for the whole synthetic biology selection, enzyme design and modification, metabolic pathway design, etc., which can effectively save the labor and time cost, and drive the rapid mass production of substances.
Science and technology for good, start the future together. Relying on the synthetic biology platform for continuous innovation and taking the lead in the industry to open and share the AI antimicrobial peptide prediction and mining model, we hope to build a good ecosystem of AI-enabled synthetic biology with partners from all walks of life, and to create a green and sustainable "bio-age" together.
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