撰文丨王聪 编辑丨王多鱼 排版丨水成文 Notch 信号通路 是一种进化上最保守的信号通路之一，在免疫细胞、神经元、血管内皮细胞、心肌细胞以及其他细胞谱系中是关键的发育命运决定因子，尤其是 T 细胞 的 发育和功能。 在体外从祖细胞/干细胞分化生成许多细胞类型都需要激活 Notch 信号通路。然而，在实验室中模拟这种高度机械性、依赖接触的信号通路，一直是个巨大的挑 战。 2025 年 8 月 1 日，哈佛大学医学院/波士顿儿童医院 George Daley 团队联合诺奖得主、蛋白质设计先驱 David Baker 教授，在国际顶尖学术期刊 Cell 上发表 了题为 ： Design of soluble Notch agonists that drive T cell development and boost immunity 的研究论文。 该研究利用 David Baker 教授团队开发的 AI 蛋白 设计工具 Rosetta ，成功设计生成了全球首个 可溶性 Notch 激动剂 ，这种可溶性蛋白能够在悬浮培养中模拟 Notch 信号通路的激活，实现了 T 细胞高效分化，并显著增强了 T 细胞功能及其抗肿 ...

针对产业实际需求，MoleculeOS进行了针对性优化。长效药物设计、药物精准递送、酶催化率提升等产业需求，往往是复杂的系统性工 程，需要综合运用多种AI算法针对多个目标展开设计。MoleculeOS将多种AI算法封装成自动化流程，沉淀出一系列药物设计、酶设计 工作流和解决方案。涵盖条件激活型抗体设计、scFV设计、mini - protein设计、多肽设计、抗体人源化、亲和力成熟、蛋白可开发性等 多个药物研发技术平台，以及酶活性设计、酶稳定性设计、酶表达设计等工业酶优化设计平台。目前，这些方案已在多个产业项目上得 到验证，能够瞄准创新药设计、合成生物学等真实产业应用需求，"一键即达"定制具备特定功能的蛋白质。 值得一提的是，MoleculeOS拥有对话式的AI Agent，让不具备AI背景的生物学家也能通过与AI对话，快速、精准地设计出高价值分子， 降低了技术使用门槛。 生物经济领域对蛋白质设计需求巨大，但传统方法存在诸多弊端。过往科学家在实验室通过实验筛选进行蛋白质设计，耗时耗力且成功 率极低，创新药研发领域十年十亿美金的"双十定律"便是典型体现。如今，AI的介入为这一领域带来变革。"AI设计＋少量实验验 ...

Core Viewpoint - Synthetic biology is poised to reshape the world through innovations such as novel antibody drugs, mRNA vaccines, and DNA data storage, with DNA synthesis as the foundational technology [1] Industry Status: Supply and Demand "Time Lag" - The high-throughput DNA synthesis sector in China is experiencing a "time lag" between supply and demand, with various applications yet to fully materialize [4] Challenges and Opportunities on the Marathon Track - Increased capital influx has led to intense competition focused on capacity and pricing, hindering the establishment of true technological barriers and sustainable business models [5] - The company aims to be a "marathon runner" in the industry, focusing on long-term value creation and resilience through economic cycles [5] Performance Priority and Cost Optimization - The company prioritizes performance as the cornerstone of technological value, ensuring high-quality synthesis before pursuing cost reductions through innovation and process optimization [6] Robust Operational System: Building a Value-Driven Moat - Long-term development is rooted in core value and robust operational capabilities, with a focus on customer value and a resilient operational system [7] - The company controls the entire supply chain from raw materials to delivery, enhancing risk resistance and ensuring stable delivery [7] Supply Side: Industry Outlook Attracting Capital - The high-throughput DNA synthesis market has seen over twelve companies emerge, with intense price competition and rapid cost declines [8] - The market capacity is projected to be between 100-150 million RMB by 2025, with potential demand growth offset by rapid price declines [8] Core Technology Deep Self-Research - The company has developed a high-throughput synthesis platform from scratch, continuously optimizing key processes to ensure quality while optimizing costs [9] Ignite 3.0: Reducing Burden and Accelerating Innovation - The company has launched the Ignite 3.0 platform, designed to address core industry pain points and enhance the development of synthetic biology [10] - Ignite 3.0 integrates high throughput, quality, and short cycles, supporting oligo pools of varying sizes and achieving a low error rate of below 0.2% [11] Performance Data Evidence - The platform can synthesize 680,000 independent points in a single run, with a synthesis length of up to 200nt and a coverage rate exceeding 99.9% [12] - The uniformity of the synthesized products is demonstrated with a 95/5 percentile ratio of 1.82, ensuring equal sampling in downstream screening [14] Future Prospects: Open Experience - Ignite 3.0 is not just a synthesizer but a validated "full-process solution," with high-quality oligo pools already showing strong competitiveness in various fields [19] - The company invites research users to apply for testing the Ignite 3.0 platform, aiming to expand into high-throughput gene construction [19]

超级智能体驱动AI蛋白设计闭环 在科学研究和产品研发中，AI生成的设计只有通过真实实验验证，才能完成"从想法到发现"的完整闭环。此次平台上线的干湿迭代案例，详细展示了从AI生 成初步设计方案，到实验团队落地执行，再到依据实验反馈进行AI重设计的全过程。整个过程紧密协同，展现出平台强大的任务管理、数据追踪与反馈联动 能力。通过该案例，用户可以清晰理解如何利用科学超智能体进行快速原型验证与多轮优化，也可以参考该流程创建自己的个性化迭代任务。干湿实验的高 效融合，将极大加速科学研究从构想到验证的全过程。 底层技术&AI | 途深智合 【SynBioCon】 获 悉， 6月20日，途深智合自主研发的蛋白质设计平台正式升级为 ProteinNova （www.proteinnova.com） ； 并 上线AI AGENT驱动 的蛋白设计全流程功能 。 途深与镁伽科技、迪赢生物两家产业链企业打通了AI蛋白设计的干实验、 高通量 基因合成和自动化湿实验流程，实现 AI-Driven Closed-Loop Protein Design. 关于途深智合 途深智合致力于通过超智能加速科学突破与产品创新。公司打造了多模态大模型、 ...