OpenPad AI, a data-driven investment strategy platform powered by DecentralizationAI analysis, announced that it has completed a $2 million financing round. Basics Capital led the round, with participation from Protein Capital, Spicy Capital, Green Arrow Adventures, VivaTech Ventures, Brinc, Boba Network, Avalon Wealth Club, Coin Bold, TechFarm, and others. OpenPad AI combines blockchain technology with artificial intelligence, allowing users to access investment strategies, project ratings, and real-time market insights while maintaining control over their data.

On May 7, Jinshi Data reported that the General Administration of Customs Announcement No. 52 of 2024 will allow the import of French pig-derived protein feed that meets the relevant requirements in accordance with China's relevant laws and regulations and the provisions of the General Administration of Customs of the People's Republic of China and the Ministry of Agriculture and Food Sovereignty of the French Republic on the quarantine and health requirements for the export of French pig-derived protein feed to China.

The company announced in the evening that it has recently obtained the "Medical Device Registration Certificate (In Vitro Diagnostic Reagent)" for the soluble growth stimulating expression gene 2 protein detection kit (chemiluminescent immunoassay) issued by the Zhejiang Provincial Drug Administration.

Scientists at the Protein Design Institute at the University of Washington School of Medicine used artificial intelligence software to design and create a batch of protein molecules with extraordinary binding strength, as reported by IT House on December 20. These molecules have extremely high affinity and specificity for a variety of biomarkers, including human hormones, and some have achieved the highest intensity of interaction with their targets to date. The study, led by David Baker, leverages advanced deep learning algorithms, combined with the sequence design tool ProteinMPNN, to create functional proteins more efficiently. The team named this innovative approach, "Build to Fit," to generate binding proteins using limited target information, such as individual peptide amino acid sequences. This breakthrough opens up a wealth of possibilities in the field of biotechnology, and scientists say another important advantage of designing proteins through AI is cost-effectiveness. Especially when diagnosing diseases that are difficult to detect with certain molecules, the designed protein can be used as a "replacement" for antibodies.

According to Xinzhiyuan, on November 1, Google's DeepMind announced the latest progress of AlphaFold - AlphaFold-latest. According to DeepMind's latest technical report, the next-generation AlphaFold is capable of more than just processing and predicting protein structures with greater accuracy. It can also generalize similar capabilities to other biomolecular structures such as nucleic acids, arbitrary small molecule ligands, and so on. According to DeepMind, the expanded functionality and performance of the new model can accelerate biomedical breakthroughs, opening up new possibilities for disease pathways, genomics, biorenewable materials, plant immunity, potential therapeutic targets, and drug design mechanisms.

Babbitt News, on October 10, Fujitsu and RIKEN announced that the two parties had developed an artificial intelligence drug discovery technology in January 2023, which can use generative AI to analyze electron microscope images. Three-dimensional density maps predict protein structural changes at large scales. The two parties also plan to publish a paper on this technology at MICCAI 2023, the top international conference in the field of medical image processing, today. At the same time, Fujitsu also plans to provide its protein structure change prediction technology to users as an artificial intelligence innovation component of "Fujitsu Kozuchi (code name) - Fujitsu Artificial Intelligence Platform", which allows users to quickly test advanced technologies.

According to a report by Golden 10 Data on September 29, mRNA vaccine technology and AI predicted protein technology may become the favorites to win awards this year. According to the official website of the Nobel Prize, the 2023 Nobel Prize (The Nobel Prize) will be announced one after another from October 2 to 9. Among them, the Nobel Prize in Physiology or Medicine (The Nobel Prize in Physiology or Medicine) will be announced in October. It will be announced in Sweden at 11:30 local time on the 2nd (17:30 Beijing time).

According to a report by the Associated Press on September 25, the official website of the University of Basel in Switzerland reported that scientists from the university and the Swiss Institute of Bioinformatics (SIB) used machine learning technology to identify 290 new protein families and a flower-like shape. new protein folds. A related paper was recently published in the journal Nature.

According to a report by Science and Technology Innovation Board Daily on September 22, Microsoft recently launched a general framework called EvoDiff, which is said to be able to generate "high fidelity" and "diversity" proteins based on protein sequences without the need for targets. Structural information of proteins, thus eliminating the most tedious steps. This technology has potential applications in the creation of enzymes for novel therapeutics and drug delivery methods, as well as the development of novel enzymes for industrial chemical reactions. It is understood that the core of the EvoDiff framework is a 640 million parameter model, which is trained using protein data from different species and functional categories.

According to Xinhuanet, on September 20, the 2023 World Manufacturing Conference co-sponsored by the Ministry of Industry and Information Technology, the State-owned Assets Supervision and Administration Commission of the State Council, the Chinese Academy of Engineering, the Anhui Provincial People's Government, etc. was held in Hefei. Tsinghua University Intelligent Industry Research Institute (AIR) Distinguished visiting professor Xu Jinbo showed up with NewOrigin (Chinese name "Darwin"), a self-developed large-scale AI protein production model. "Molecular Heart is working with cooperative pharmaceutical companies to solve key problems in protein vaccine stability based on the NewOrigin large model." Xu Jinbo revealed. The NewOrigin large model can help drug research and development teams quickly analyze, locate and decompose the problems of improving the effectiveness of protein vaccines into sub-problems that can be solved based on AI methods, such as using AI to design mutations to improve the stability of protein vaccines. Then, NewOrigin will conduct mutation design on the wild-type protein, and automatically call a series of methods such as language model, evolution model, structural model, and energy model to extract protein features, predict the properties of the protein vaccine mutant, and obtain the most ideal protein molecule. . In just 3 days, NewOrigin can design dozens of ideal candidate proteins.

According to the "Kechuangban Daily" report, on September 19, local time, Google DeepMind announced that its research team created AlphaMissense based on the AlphaFold methodology - by using the protein sequence database and variant structure background, it can identify disease-causing missense mutations and The causative gene is unknown. AlphaMissense successfully predicted the pathogenicity of 216 million possible single amino acid changes in 19233 standard human proteins, resulting in predictions of 71 million missense mutations. Subsequently, AlphaMissense successfully predicted 89% of missense mutations, compared with only 0.1% of mutations that have been confirmed by human experts.

According to a report by Webmaster Home on September 11, Baitu Biotech’s AIGP protein design platform released the first batch of user recruitment information for internal testing, limited to 50 users. This platform is a generative protein design platform launched based on Baitu Biotech's life science Foundation Model-xTrimo, which can support the generation and optimization of multiple types of proteins. The AIGP protein design platform does not require local deployment and can be used online instantly, and user data will be strictly encrypted and protected.

According to Jinshi News, on September 8, Tencent Health announced a large medical model and released a multi-scenario AI product matrix such as intelligent question and answer, family doctor assistant, and digital intelligent medical imaging platform. The drug discovery platform "iDrug" revealed a new Protein structure prediction algorithm framework tFold. At present, Tencent's medical large-scale models include scenario large-scale models such as copywriting generation, intelligent question and answer, medical record structuring and retrieval, imaging reports, and auxiliary diagnosis, which can be embedded in the entire medical process.

According to the "Kechuangban Daily" citing the British Financial Times, Meta disbanded its AI protein team, which launched the ESMFold project and trained large models capable of processing large amounts of biological data to predict protein structures. According to the report, this shows that Meta is abandoning purely scientific projects and turning to develop profitable artificial intelligence products to promote the commercialization of its artificial intelligence business.

According to the "Kechuangban Daily" report on August 3, scientists at the University of Pennsylvania in the United States used artificial intelligence to analyze the protein data of modern humans and human extinct relatives Neanderthals and Denisovans, and identified the latter two. Molecules made by humans that kill disease-causing bacteria and synthesized. The latest research is expected to help scientists develop new types of drugs. Relevant papers were published in the latest issue of the journal Cell Host and Microbe. Many organisms, including humans, produce peptides with antimicrobial properties, and peptides produced by extinct human relatives such as Neanderthals and Denisovans may be useful to modern bacteria, the team noted.

According to reports from the investment community, recently, Hangzhou Liwensuo Biotechnology Co., Ltd., an AI protein design company, announced that it has completed tens of millions of yuan in angel round financing. This round of financing was led by Kaitai Capital, followed by Panlin Capital and Hongshi Capital, and Zhen Fund, the lead investor of the seed round, made additional investment. The financing funds will be mainly used for the optimization and development of the AI protein design platform, and to promote the platform incubation and construction of multiple product pipelines.

According to Jinshi's news on July 21, MGI's Yang Meng team published a paper in Nature Machine Intelligence, a sub-journal of Nature, and released an algorithm model called "EvoPlay". It is reported that the algorithm draws on the way of the game of Go, and can train the agent to complete the protein evolution of specified function enhancement like an automatic driving. This breakthrough will provide new ideas in the field of protein design and be used to further optimize various tool enzymes used in gene sequencers.

According to a report from IT House on July 13, researchers at the Massachusetts Institute of Technology have developed an AI tool called FrameDiff that uses generative artificial intelligence to design new protein structures with the aim of accelerating drug development and improving gene therapy. The design of novel protein structures remains a challenge in protein engineering across biomedical and chemical applications. FrameDiff can build proteins beyond natural variants, a method that can generate protein structures that differ from existing designs, and is expected to speed up the process of protein structure generation, thereby advancing progress in drug discovery, diagnostics, and industrial applications.

According to a report by the Financial Associated Press on July 12, Professor David Baker, a pioneer in the field of artificially designed proteins, published his latest paper in Nature. The AI software RFdiffusion developed by his team can break through many previous protein design limitations and can be "customized" as needed Design proteins including high-order symmetric structures that could not be designed by AI in the past. The "Nature" press release states that this AI model can design biomolecules on demand, which may lead to the next era of transformative vaccine and drug development.

According to a report from the "Kechuangban Daily" on June 13, the AI protein design company "Yusinshuo Biology" has completed an angel round of financing of nearly 10 million yuan. The investor is Jiuhe Venture Capital. This round of funds will be used for technology research and development and market expansion. Founded in 2022, Yuxinshuo Biotech is a company focusing on new protein design. It briefly summarizes its technology and applications, that is, using AI to design biological components, and using biological components to construct genetic circuits. Strains and catalytic enzymes can undergo natural evolution to eventually generate new functional proteins.