Core Viewpoint - Bayer is committed to enhancing its focus and resource investment in China's innovation ecosystem, aiming to collaborate with local innovators to discover the next significant breakthroughs in drug development [1]. Group 1: Competition Announcement - Bayer China has officially launched the "Co-Creation New Drug" competition, inviting Chinese innovators and biotechnology companies to submit and showcase their innovative research pipelines, drug molecules, or new technologies with breakthrough potential [1]. Group 2: Target Therapeutic Areas - The competition focuses on several key therapeutic areas, including: - Precision Oncology - Precision Cardiorenal Diseases - Immunology & Inflammation [2]. Group 3: Research Pipeline Stages - The competition accepts submissions at various stages of the research pipeline, ranging from early pre-clinical candidate compounds (pre-PCC) to clinical proof of concept (clinical PoC) [2]. Group 4: Drug Molecule Forms - Eligible drug molecule forms include: - Biologics - Small molecules (SMOL) - Conjugated drugs (XDC) - Genetic medicine - Small nucleic acid drugs (siRNA) - Molecular glue - Other platform technologies [3]. Group 5: Evaluation Criteria - Submissions will be evaluated by a review committee composed of Bayer China's and global R&D and business development experts based on innovation level, key data, advancement speed, and alignment with Bayer's R&D strategy [4].

撰文丨王聪 编辑丨王多鱼 排版丨水成文 麻疹病毒 （MeV） 是一种高度传染性的不分节段负链 RNA 病毒，属于副粘病毒科，每年导致数百万例感染，目前尚无获批的抗病毒药物。其 由大蛋白 （L） 和四聚体磷蛋白 （P） 组成的病毒聚合酶复合物是关键的抗病毒靶点。 2025 年 7 月 7 日，上海科技大学 张贺桥 / Roger Kornberg 团队在国际顶尖学术期刊 Cell 上发表了题为： Structures of the measles virus polymerase complex with non-nucleoside inhibitors and mechanism of inhibition 的研究论文。 该研究解析了 麻疹病毒 （MeV） 聚合酶 复合物及其与非核苷抑制剂结合后的结构，并揭示了抑制机制，为抗病毒药物的理性设计奠定了基础。 在这项最新研究中，研究团队确定了麻疹病毒聚合酶复合物 apo 状态下以及与两种非核苷抑制剂 ERDRP-0519 和 AS-136A 结合时的冷冻电镜结构， 分辨率分 别为 3.0 Å、 3.4 Å 和 3.3 Å。 结果显示，抑制剂结合会引发 麻疹病毒聚 ...

Core Viewpoint - The article discusses the development of a novel artificial intelligence-based protein engineering computational simulation method called AiCE, which integrates structural and evolutionary constraints to enhance protein evolution and function design without the need for specialized AI model training [4][12]. Group 1: Protein Engineering Overview - Protein engineering involves modifying amino acid sequences to alter protein structure and function, offering significant potential in both basic research and industrial applications, with market size expected to exceed hundreds of billions [2]. - Current strategies in protein engineering, such as rational design and directed evolution, face challenges including high costs and long experimental cycles, limiting their scalability [2]. Group 2: AI in Protein Engineering - The rapid advancement of artificial intelligence has led to its application in life sciences, particularly in simulating mutations and functional modifications of proteins [3]. - Existing AI models struggle with generalizability across various proteins and require substantial computational and experimental resources, necessitating the development of more efficient and universal protein engineering strategies [3]. Group 3: AiCE Method Development - The AiCE method allows for efficient protein evolution simulation and function design without the need for training dedicated AI models, significantly reducing computational costs [4][12]. - AiCE utilizes existing universal inverse folding models to predict amino acid sequences based on given protein structures, enhancing the accuracy of predictions [5][6]. Group 4: Performance and Applications - AiCE single module achieved a 16% prediction accuracy using 60 deep mutational scanning datasets, with a 37% performance improvement over unrestricted methods [6]. - AiCE multi module predicts mutation combinations effectively while maintaining low computational costs, demonstrating comparable predictive capabilities to larger models [7]. Group 5: Experimental Validation - The research team validated AiCE's functionality across eight diverse proteins, including deaminases and nucleases, confirming its simplicity, efficiency, and versatility [9][10]. - The development of new base editors with enhanced precision and activity, such as enABE8e and enDdd1-DdCBE, showcases AiCE's practical applications in precision medicine and molecular breeding [9][10]. Group 6: Significance and Future Directions - The study highlights the importance of developing efficient bioinformatics tools to reduce computational burdens, making AI-driven protein engineering accessible to more researchers [12]. - The advancements presented in this research mark a significant step forward in the field of protein evolution, elevating AI-based approaches to a new level [12].

该研究以： AI-enabled drug prediction and gene network analysis reveal therapeutic use of vorinostat for Rett Syndrome in preclinical models 为题，于 2025 年 7 月 1 日，发表在了 Communications Medicine 期刊。 撰文丨王聪 编辑丨王多鱼 排版丨水成文 开发出一种有效的 Rett 综合征 疗法一直极具挑战性，这在很大程度上是因为这种罕见的遗传疾病 （ 每 10000 名女孩中就有 1 名患病 ） 所伴有的认知和身体 损伤十分复杂，患者因 X 染色体上的 MeCP2 基因突变，导致出现重复的手部动作、语言障碍和癫痫发作，同时还伴有非神经系统器官 （ 包括消化系统、肌肉 骨骼系统和免疫系统 ） 的问题。 而现在，哈佛大学 Wyss 研究所的研究团队通过利用人工智能 （AI） 驱动的药物发现流程取得了重大突破，他们发现，一种名为 伏立诺他 （ Vorinostat， 一种 已获美国 FDA 批准用于治疗皮肤 T 细胞淋巴瘤的组蛋白去乙酰化酶抑制剂） 的药 ...

撰文丨王聪 编辑丨王多鱼 排版丨水成文 炎症性衰老 （ inflammaging ） ，即与年龄相关的慢性炎症增加，被认为是 衰老 的一个标志。然而，目前对于基于循环细胞因子来衡量炎症性衰老还没有达成 一致的方法。 近日 ，加拿大 舍布鲁克大学和美国哥伦比亚大学的研究人员合作，在 Nature 子刊 Nature Aging 上发表了题为 ： Nonuniversality of inflammaging across human populations 的研究论文。 该研究通过比较工业化人群 （来自 意大利和新加坡的人群 ） 和非工业化人群 （来自 玻利维亚和马来西亚的原住民 ） ，发现 炎症性衰老 （ inflammaging ） 在不同群体中并不具有普遍性， 生活方式工业化程度较低的人群可能不会经历炎症性衰老。因此， 炎症性衰老可能只是工业化生活方式的副产物，因此在全球不 同人群中存在着显著差异。 短期炎症对于治愈感染至关重要，但长期炎症暴露 （炎症性衰老） 已知会增加生物学衰老和出现年龄相关性疾病的风险。不过，之前并不确定炎症性衰老对所有 人群的影响是否一致。 在这项新研究中，研究团队评估了在意大利的 ...

Core Viewpoint - Ferroptosis has emerged as a promising anti-tumor treatment strategy, distinct from apoptosis and necroptosis, characterized by uncontrolled lipid peroxidation and high levels of ferrous ions (Fe2+) and reactive oxygen species (ROS) [2][3][7]. Group 1: Mechanism and Inducers of Ferroptosis - GPX4 utilizes glutathione (GSH) to reduce lipid peroxides to lipid alcohols, making targeting GPX4 or GSH a potential strategy for cancer therapy [3]. - Lipid peroxidation may serve as a "find me" signal, enhancing tumor immunotherapy effectiveness [3]. - Inducers of ferroptosis, such as RSL3 and erastin, have shown efficacy in inducing ferroptosis in mouse tumor models and human tumor cell lines [3][4]. Group 2: Research Findings on Acevaltrate - A recent study identified acevaltrate (ACE) as a novel ferroptosis inducer that targets both PCBP1/2 and GPX4 in colorectal cancer cells, leading to rapid and strong induction of ferroptosis [4][8]. - ACE increases intracellular Fe2+ levels by targeting and reducing the expression of iron chaperone proteins PCBP1/2, while also inhibiting GPX4 activity, disrupting the antioxidant system in colorectal cancer cells [9][12]. - Animal experiments indicate that ACE demonstrates superior therapeutic effects compared to known ferroptosis inducers and first-line clinical cancer drugs like capecitabine and TAS-102 [10][12]. Group 3: Implications for Clinical Treatment - The dual mechanism of ACE not only enhances the induction of ferroptosis but also addresses the compensatory resistance issues associated with single-target ferroptosis inducers [12]. - ACE's multi-target characteristics suggest a potential for high efficacy and low toxicity in selectively killing tumor cells, providing a new strategy for clinical treatment of colorectal cancer [12].

Core Viewpoint - The research indicates that sleep is essential for preventing the disruption of the brain phosphoproteome, which is crucial for survival [2][3]. Group 1: Importance of Sleep - Sleep is an indispensable behavior preserved across all animal species, and long-term sleep deprivation (Pr-SD) can lead to mortality in various species [1]. - The core molecular basis linking sleep deprivation-induced lethality and sleep homeostasis in mammals remains unclear [8]. Group 2: Mechanisms and Functions of Sleep - Numerous factors affecting sleep duration or quality have been reported, including biological clock genes, neural circuits, specific kinase signaling pathways, and neurotransmitters [6]. - Research has identified several functions related to sleep, such as cognition, metabolic waste clearance, metabolism, and immune function [6]. Group 3: Research Methodology - The Disk-over-water (DOW) method is utilized to study sleep deprivation by placing animals on a disk above water, forcing them to stay awake [10]. - The study observed an "irreversible point" (PONE) state in rats during DOW experiments, characterized by irreversible mortality even after sleep deprivation is terminated [11]. Group 4: Findings on PONE State - Analysis of the PONE state revealed that the balance of the brain phosphoproteome is critical for sleep regulation and the mortality caused by Pr-SD [12]. - Mice in the PONE state were unable to enter natural sleep, and their brain phosphoproteome exhibited significant disruption, closely related to the PONE state rather than the duration of sleep deprivation [13]. Group 5: Implications for Sleep and Health - Dysfunction in brain kinases or phosphatases affects the development of the PONE state and leads to corresponding sleep abnormalities [14]. - Restorative sleep of 80 minutes daily can significantly delay cognitive decline and restore the brain phosphoproteome [14]. - The findings suggest that sleep is vital for maintaining the homeostasis of the brain phosphoproteome, and its disruption may influence lethality caused by long-term sleep deprivation [14].

Core Viewpoint - The article discusses the development of a virtual cell model called STATE by Arc Institute, which aims to predict cellular responses to various drug and genetic interventions, thereby enhancing the success rate of clinical trials and drug discovery [3][12]. Group 1: Virtual Cell Model STATE - STATE is designed to predict the responses of various cell types, including stem cells, cancer cells, and immune cells, to drugs and genetic disturbances [3][12]. - The model is trained on data from 167 million cells and over 100 million disturbance data points, covering 70 different cell lines [3][7]. - STATE consists of two interconnected modules: State Embedding (SE) and State Transition (ST), which allow for the prediction of RNA expression changes based on initial transcriptomes and disturbances [6][7]. Group 2: Performance and Advantages - STATE significantly outperforms existing computational methods, showing a 50% improvement in distinguishing disturbance effects and double the accuracy in identifying differentially expressed genes [7][9]. - The model is the first to surpass simple linear baseline models in all tests conducted [7]. - It focuses on single-cell RNA sequencing data, which is currently the only unbiased data available at scale for researchers [7]. Group 3: Data Collection and Causality - The research team compensates for the limitations of single-cell RNA sequencing data by collecting large-scale disturbance data through experiments like CRISPR gene editing [8][9]. - Disturbance data captures causal relationships between genes, providing insights into biological mechanisms that observational data cannot [8][9]. Group 4: Future Developments and Applications - The ultimate goal of the virtual cell model is to help scientists explore a vast space of combinatorial possibilities for cellular changes, which is impractical to test experimentally [12]. - The team has introduced Cell_Eval, a comprehensive evaluation framework for virtual cell modeling, focusing on biologically relevant metrics [12]. - A virtual cell challenge has been launched, offering a $100,000 prize to encourage innovation in this field [12].

撰文丨王聪 编辑丨王多鱼 排版丨水成文 接受免疫检查点阻断 （ICB） 疗法的 非小细胞肺癌 （NSCLC） 患者很少出现完全的临床响应，开发能够实现肿瘤完全消退的治疗策略是临床面临的一大挑战。 大多数患者最多只有部分临床响应，这一事实提示我们，个体肿瘤内部的免疫压力程度或敏感性并不一致。 事实上，多区域取样研究揭示了抗肿瘤免疫的广泛肿瘤内异质性，不同肿瘤区域在免疫细胞浸润程度、新抗原表达以及 T 细胞受体 （TCR） 库方面存在显著差 异。局部免疫逃逸可能会产生严重的临床后果，而且肿瘤中存在不止一处"冷肿瘤"区 （免疫细胞浸润不良） 的患者预后尤其不佳。 尽管 肿瘤由多个遗传上不同的克隆组成，但由于无法从人类癌症中分离并培养出单个亚克隆，因此，这种遗传多样性是否会影响免疫逃逸的可能性，目前仍不清 楚。 2025 年 7 月 3 日，弗朗西斯·克里克研究所、 荷兰癌症研究所、伦敦大学学院癌症研究所的研究人员在 Cancer Cell 期刊发表 了题为： Subclonal immune evasion in non-small cell lung cancer 的研究论文。 该研究利用 非小细胞肺癌 的不同肿 ...

编辑丨王多鱼 排版丨水成文 在动物基因组中，被称为 增强子 （ enhancer ） 的调控性 DNA 元件控制着特定细胞类型中基因表达的精确时空模式。然而，增强子在细胞核内的空间组织以调 控靶基因的方式，目前仍知之甚少。 2025 年 7 月 2 日 ，北京大学生物医学前沿创新中心 （ BIOPIC ） /昌平实验室 谢晓亮 院士团队在 Nature Genetics 期刊发表了题为 ： Single-cell Micro-C profiles 3D genome structures at high resolution and characterizes multi-enhancer hubs 的研究论文。 研究团队开发了 单细胞 Micro-C （scMicro-C） 技术，这种是基 于微球菌核酸酶 （ Micrococcal nuclease ） 的 3D 基因组图谱技术，能够以 高分辨率描绘 3D 基因组结构，并表征了 多增强子中心 （ multi-enhancer hub ） ，即多个增强子与基因启动子相关联，形成空间簇。 此外，该研究还观察到，在单细胞 3D 基因组结构中，具有 PES 的基因 ...