Core Viewpoint - David Baker's team has developed a groundbreaking AI protein design model, RFdiffusion, which allows for the precise control of protein-protein interactions, potentially revolutionizing fields such as cancer treatment and immune regulation [2][3]. Group 1: Research Breakthroughs - The new design method enables precise timing of cytokine signaling, allowing for "remote control" of protein interactions with second-level accuracy [3]. - The research focuses on designing the "excited state" of proteins, which influences the kinetics of protein-protein interactions, rather than just their stable states [7]. - A special "hinge protein" was designed to change conformation in response to external signaling molecules, facilitating rapid dissociation of protein complexes [10]. Group 2: Performance Metrics - The new design method achieves up to a 5700-fold increase in dissociation rates, allowing protein complexes that previously took hours to dissociate to do so in seconds [12]. - Structural analysis confirmed that the designed proteins closely matched theoretical predictions, with a maximum deviation of only 1.3Å [12]. Group 3: Applications - The technology has potential applications in developing rapid biosensors, such as a SARS-CoV-2 sensor with a response time of just 30 seconds, which is 70 times faster than previous sensors [14]. - It can create dynamic control circuits at the protein level, enabling efficient signal transmission and amplification [15]. - The method allows for the rapid shutdown of highly active splitting enzyme systems, providing new tools for metabolic engineering [16]. Group 4: Immunology Insights - The research has significant implications for controlling the interleukin-2 (IL-2) signaling pathway, which is crucial for immune response, allowing for rapid on/off switching of IL-2 analogs [18]. - Different durations of IL-2 stimulation were found to have distinct biological effects, with short stimulation providing anti-apoptotic protection while prolonged stimulation activated metabolic changes and cell division [19][20]. Group 5: Paradigm Shift in Protein Design - This research represents a paradigm shift in protein design, moving from static structure design to dynamic kinetic control, with broad applicability across various protein interactions [22]. - The technology not only serves as a powerful tool for basic biological research but also opens new avenues for therapeutic applications, potentially leading to more precise and controllable biotherapies [22].

Company Overview - Wuxi Tushen Zhihuo Artificial Intelligence Technology Co., Ltd. (Tushen Zhihuo) completed a multi-million RMB angel round financing, with participation from Shanghai Angel Association and continued investment from existing shareholder Chengmei Capital [1][3] - Founded in December 2023, Tushen Zhihuo focuses on AI-driven protein design in the biotechnology sector, leveraging advanced AI technology for high-value protein and related product development [2][3] - The company is led by Wang Yuguang, an associate professor at Shanghai Jiao Tong University, with a strong background in AI, applied mathematics, and synthetic biology [2][3] Technology and Innovation - Tushen Zhihuo has developed a scientific intelligence platform for the biopharmaceutical field, enabling automated antibody design and protein expression testing [2][3] - The company has achieved significant advancements in industrial applications, such as improving the affinity of rabbit monoclonal antibodies beyond that of leading European pharmaceutical companies and enhancing enzyme activity by 380% and 800% for specific enzymes [3] Funding and Investment - Tushen Zhihuo has completed four rounds of financing within two years, indicating strong investor confidence and interest in the AI protein design sector [3][5] - Chengmei Capital has been a consistent investor, recognizing the potential of AI technology across various industries and the team's solid technical background [3][5] Industry Landscape - The global protein design market is rapidly evolving, with a focus on the application of AI in drug development, industrial enzyme catalysis, and biomanufacturing [4][5] - Approximately 30 AI protein-related companies are based in China, while 25 are located overseas, with most technologies originating from academic institutions [5][6] - Chinese companies emphasize practical applications and industrial efficiency in AI protein design, contrasting with overseas firms that focus on foundational breakthroughs [6] Challenges and Future Outlook - The AI protein design sector faces challenges such as data quality, model interpretability, and high costs of wet lab validation, which are critical for transitioning from research to commercial applications [6]

Core Viewpoint - The article discusses the breakthrough technology BindCraft, which allows for the one-shot design of functional protein binders with a success rate of 10%-100%, significantly improving the efficiency of protein design compared to traditional methods [2][3][5]. Summary by Sections BindCraft Technology - BindCraft is an open-source, automated platform for de novo design of protein binders, achieving high-affinity binders without the need for high-throughput screening or experimental optimization [3][5]. - The technology leverages AlphaFold2's weights to generate protein binders with nanomolar affinity, even in the absence of known binding sites [3][5]. Applications and Results - The research team successfully designed binders targeting challenging targets such as cell surface receptors, common allergens, de novo proteins, and multi-domain nucleases like CRISPR-Cas9 [3][7]. - Specific applications include: 1. Designing antibody drugs targeting therapeutic cell surface receptors like PD-1 and PD-L1, achieving nanomolar affinity without extensive design and screening [7]. 2. Blocking allergens, with a designed binder for birch pollen allergen Bet v1 showing a 50% reduction in IgE binding in patient serum tests [7][8]. 3. Regulating CRISPR gene editing by designing a new inhibitory protein that significantly reduces Cas9's gene editing activity in HEK293 cells [8]. 4. Neutralizing deadly bacterial toxins, with a designed protein completely eliminating cell death caused by the toxin from Clostridium perfringens [8]. 5. Modifying AAV for targeted gene delivery by integrating mini-binders that specifically target HER2 and PD-L1 expressing cancer cells [8]. Impact and Future Potential - BindCraft addresses long-standing success rate bottlenecks in protein design and offers direct solutions for allergy treatment, gene editing safety, toxin neutralization, and targeted gene therapy [9]. - The open-source nature of the technology allows ordinary laboratories to design custom proteins, potentially reshaping drug development, disease diagnosis, and biotechnology [9].

闻乐 发自 凹非寺 量子位 | 公众号 QbitAI 借助AI， 新型蛋白质 合成周期大幅降低！ 这些蛋白质还能有效抵抗像大肠杆菌这类抗生素耐药细菌。 一项来自澳大利亚的研究发现，像大肠杆菌这类致病菌会通过 ChuA蛋白 （细菌中的一种外膜蛋白） 从宿主血红蛋白中"偷"血红素获取生长 所需的 铁 。 研究人员借助AI工具，成功设计出能与ChuA结合的蛋白质，这些蛋白质就像"门卫"一样，阻止ChuA与血红蛋白接触，从而抑制细菌生长。 并且，部分AI设计的蛋白质在 低纳摩尔浓度下 就能发挥作用。 该研究现已发表于 Nature Communications 。 这项研究由Gavin Knott教授和Rhys Grinter博士共同领衔，他们研发出的AI蛋白质设计平台是澳大利亚首个模拟 诺奖得主David Baker 工 作的平台，采用 端到端 的方式创建了多种蛋白质。 并且，平台使用的是全球科学家均可 免费 使用的AI驱动蛋白质设计工具，能够让更多科研人员能参与其中，推动该领域发展。 研究原理：用算法打造抗菌 "分子锁" 对于包括大肠杆菌和志贺氏菌在内的大多数细菌， 铁是其生长和导致感染所必需的关键营养物质 。 ...

#SynBio团队 | 以色列魏茨曼科学研究院 【SynBioCon】 获 悉 ， 以色列魏茨曼科学研究院科学家在新一期《自然》杂志发表文章称：他们利用基于酶工 作原理的计算机新算法设计出高效人工合成酶。这种新型酶不仅能催化天然蛋白质无法完成的化学反应， 其效率 更达到人工智能（AI）设计酶的100倍 ，标志着"按需定制"高效酶的新阶段即将来临。 传统计算机算法辅助设计的酶往往效率低下，需要耗费大量时间进行实验室优化。为突破这一瓶颈，研究团队独 辟蹊径，选择"肯普消除"（一种涉及从特定底物碳原子上移除质子的非天然化学反应）作为验证案例。 过去十年，AI蛋白质设计大行其道，但其工作机制主要模仿现有酶。相比之下，新算法的工作机制是基于物理原 理来构建酶。研究团队表示，AI在处理某些蛋白质设计时确实无可替代，但对于复杂催化反应仍力不从心。未来 需要将两种方法优势互补，才能设计出更完美的酶。 通过算法设计的一种酶（白色）将底物（红色、黄色和蓝色）包裹于其活性位点内。图片来源：《自然》网站 ▌ 参考信息： 本文部分 素 材 来 自全网 。由 作 者重新 编写，系作者个人观点，本平台发布仅为了传达一种不同观点，不代表对该 ...

Group 1 - The article discusses the first real theater-based neuroaesthetic experiment in China, conducted at Tsinghua University, where eight volunteers wore portable EEG devices while watching a dance performance to capture their neural activity in real-time [3][6]. - The NeuroHUB platform, developed by Boruikang, is highlighted for its ability to achieve millisecond-level synchronization of EEG and physiological signals in a real-world setting, marking a significant advancement in neuroaesthetic research [5][6]. - The experiment demonstrated that audience engagement significantly increases brain activity, revealing the neural connections between emotional responses and artistic experiences [6][7]. Group 2 - NeuroHUB showcases three core advantages: wireless freedom allowing natural seating in the theater, group super-scanning enabling real-time dialogue among multiple brains, and robust interference resistance against complex electromagnetic environments [7][9]. - The platform's modular design and wireless data transmission ensure a seamless experience for participants, maintaining the purity of the artistic experience during the performance [7]. - NeuroHUB's capability to synchronize data from over ten participants simultaneously represents a breakthrough in overcoming the limitations of traditional laboratory settings [8]. Group 3 - The article also mentions advancements in medical technology, including a new integrated solution for coronary function and imaging assessments approved for market release, which combines multiple evaluation metrics for enhanced surgical decision-making [11][12]. - The development of a fully magnetic levitation artificial heart by Xinxin Medical has been recognized as one of the top ten technological advancements in Jiangsu Province, showcasing significant progress in heart failure treatment [13][15]. - The iPSC-derived CAR-NK cell therapy developed by Qihan Biotech has achieved notable clinical results in treating refractory systemic sclerosis, marking a significant milestone in autoimmune disease treatment [16][17]. Group 4 - The article highlights the introduction of two first-in-class drugs by Dige Pharmaceutical, which will be presented at major international conferences, indicating ongoing innovation in the hematology sector [21]. - The J-VALVE TF system's 12-month clinical follow-up results demonstrate superior performance compared to similar products, emphasizing the potential of Chinese-developed medical devices on the international stage [22][24]. - The article concludes with advancements in AI-driven enzyme design and biodegradable medical devices, showcasing the ongoing evolution and innovation within the healthcare and biotechnology industries [25][35].

Core Insights - The recent breakthrough in AI enzyme design by MoleculeMind and Hong Kong Polytechnic University has been recognized at the ICML 2025 conference, marking a significant advancement in the field of AI enzyme design [1] - The traditional methods of enzyme discovery and optimization are time-consuming and costly, with a success rate of less than 1%, highlighting the urgent need for innovative solutions in the biomanufacturing sector [2] - The introduction of the SENZ method, which utilizes substrate structure similarity for enzyme design, represents a novel approach that could revolutionize enzyme generation [3][5] Industry Overview - Enzymes are crucial for the development of the trillion-dollar bio-economy, impacting sectors such as biomedicine, green chemistry, and environmental degradation [1] - The lack of ideal biocatalysts is a major barrier to scaling production in the biomanufacturing industry, leading to annual capacity losses exceeding $100 billion in pharmaceuticals, chemicals, and agriculture [2] - AI protein design has emerged as a promising solution to generate precise catalysts by learning from existing enzyme structure-function relationships, although it faces challenges with novel synthetic molecules due to limited training data [2] Company Developments - MoleculeMind has developed the SENZ method, which integrates biological data retrieval and generative AI to create enzymes without direct catalytic data, thus addressing a critical challenge in enzyme generation [3][5] - The SENZ method has demonstrated superior performance compared to traditional enzyme design methods, potentially providing tailored solutions for complex drug synthesis and environmental remediation [6] - MoleculeMind is expanding its capabilities in "on-demand design" across various fields, including antibodies, vaccines, and industrial enzymes, aiming to provide innovative biological solutions for health, environmental, and sustainability challenges [7]