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市场调查报告书
商品编码
1938472
结构生物资讯市场-全球产业规模、份额、趋势、机会及预测(依产品/服务、大分子、应用、最终用户、地区及竞争格局划分),2021-2031年Structural Bioinformatics Market - Global Industry Size, Share, Trends, Opportunity and Forecast, Segmented By Product & Services, By Macromolecule, By Application, By End User, By Region & Competition, 2021-2031F |
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全球结构生物资讯市场预计将从 2025 年的 2.7 亿美元成长到 2031 年的 4.7 亿美元,复合年增长率为 9.68%。
该领域利用计算技术分析和预测生物大分子的三维结构,其根本驱动力源于高效药物发现和精准医疗的迫切需求,而这两者都依赖精确的分子建模。大规模涌入的蛋白质体学数据需要复杂的解读,进一步强化了这个驱动力。世界蛋白质资料库(WPDB)2024年的存檔资料就收录了229,659个公开可用的结构,便印证了这一点。
| 市场概览 | |
|---|---|
| 预测期 | 2027-2031 |
| 市场规模:2025年 | 2.7亿美元 |
| 市场规模:2031年 | 4.7亿美元 |
| 复合年增长率:2026-2031年 | 9.68% |
| 成长最快的细分市场 | 蛋白质 |
| 最大的市场 | 北美洲 |
然而,结构生物学和资料科学领域专业人才的短缺是限制市场成长的主要因素。分析庞大且多样化的资料集的复杂性为商业机构带来了瓶颈,因为所需的专业技能十分稀缺。这种人才短缺,加上不同平台间资料互通性方面的挑战,限制了结构生物资讯解决方案的可扩展性,并减缓了其在产业内的普及应用。
加速药物发现和开发流程是关键的成长引擎,它正在变革传统的标靶识别和先导化合物优化方法。透过整合计算方法,研究人员可以预测分子相互作用并改善化合物性质,从而显着缩短进入临床试验所需的时间和资金。这项策略转变得益于对人工智慧驱动生物学的大量投资;例如,Xaira Therapeutics 于 2024 年 4 月成功资金筹措超过 10 亿美元的资金,用于建立一个旨在革新药物发现工作流程的平台。
此外,高效能运算和云端运算基础设施的进步为处理海量生物资料集提供了至关重要的基础。从本地系统向可扩展云环境的转变,促进了分子动力学模拟和蛋白质折迭预测等资源彙整任务的发展。 NVIDIA预测,到2024年底,资料中心营收将达到308亿美元,这主要得益于医疗保健运算需求的成长;Schrodinger预测,到2024年第三季度,软体营收将达到3,190万美元,这反映了对分子建模工具的持续商业需求,这些都印证了上述趋势。
全球结构生物资讯市场面临的一大障碍是能够有效弥合结构生物学和资料科学之间鸿沟的专业人才严重短缺。业界需要具备「双语」能力的人才,既能理解分子相互作用,又能应用先进的演算法建模和机器学习技术。随着蛋白质体学数据量呈指数级增长,缺乏能够管理这些资讯的人才正在造成研究瓶颈,延缓药物研发进程,并降低研发投资的盈利。
人才短缺严重限制了该行业采用和扩展先进计算工具的能力。皮斯托亚联盟 (Pistoia Alliance) 2025 年的报告显示,34% 的生命科学实验室认为缺乏内部技能是采用人工智慧的主要障碍,而且这一比例逐年上升。由于缺乏设计和维护复杂生物资讯学流程的合格人员,企业难以将高通量结构资料投入实际应用,最终阻碍了市场扩张和精准医疗的应用。
深度学习与人工智慧的融合正迅速发展,其应用范围已从预测单一蛋白质链扩展到模拟包含DNA、RNA和小分子等多种分子的复杂多模态生物复合物。新的计算框架克服了传统方法在模拟异构系统方面的局限性,并能更全面地理解细胞机制和动态相互作用网络。例如,GoogleDeepMind于2024年5月发布的AlphaFold 3,与现有方法相比,将蛋白质交互作用预测的准确率提高了50%,标誌着该领域的技术飞跃。
同时,该领域正朝着从头蛋白质设计的方向发展,不再分析现有实体,而是利用生成式人工智慧创建新型可程式设计结构。这种方法能够产生具有自然界不存在的序列的定制酶和结合蛋白,从而有效地绕过进化的限制。 EvolutionaryScale 正是这一趋势的体现,该公司于 2024 年 6 月成功资金筹措了1.42 亿美元,用于推进 ESM3 模型的演进,并成功设计出不同于天然形式的新型萤光蛋白。
The Global Structural Bioinformatics Market is projected to expand from USD 0.27 Billion in 2025 to USD 0.47 Billion by 2031, registering a CAGR of 9.68%. This field, which utilizes computational techniques to analyze and predict the three-dimensional structures of biological macromolecules, is fundamentally driven by the urgent need for efficient drug discovery and precision medicine reliant on accurate molecular modeling. These drivers are bolstered by the massive influx of proteomic data necessitating sophisticated interpretation, a trend highlighted by the Worldwide Protein Data Bank's 2024 archive, which housed 229,659 released structures.
| Market Overview | |
|---|---|
| Forecast Period | 2027-2031 |
| Market Size 2025 | USD 0.27 Billion |
| Market Size 2031 | USD 0.47 Billion |
| CAGR 2026-2031 | 9.68% |
| Fastest Growing Segment | Proteins |
| Largest Market | North America |
However, market growth is significantly hindered by a shortage of professionals possessing the dual expertise required to navigate structural biology and data science. The complexity of analyzing large, heterogeneous datasets creates a bottleneck for commercial entities, as the specialized skills needed are scarce. This talent deficit, coupled with challenges in achieving data interoperability across different platforms, limits the scalability of structural bioinformatics solutions and retards their broader industrial implementation.
Market Driver
The acceleration of drug discovery and development processes acts as a primary growth engine, transforming traditional approaches to target identification and lead optimization. By integrating computational methods, researchers can predict molecular interactions and refine compound properties, thereby drastically cutting the time and capital needed to reach clinical trials. This strategic shift is validated by massive investments in AI-driven biology, such as Xaira Therapeutics securing over $1 billion in April 2024 to build a platform aimed at revolutionizing drug discovery workflows.
Furthermore, advancements in high-performance computing and cloud infrastructure provide the essential backbone for handling extensive biological datasets. The shift from on-premise systems to scalable cloud environments facilitates resource-heavy tasks like molecular dynamics simulations and protein folding predictions. This trend is underscored by NVIDIA's record Data Center revenue of $30.8 billion in late 2024, driven by healthcare computing needs, and Schrodinger's reported software revenue of $31.9 million in the third quarter of 2024, reflecting the sustained commercial demand for molecular modeling tools.
Market Challenge
A critical impediment to the Global Structural Bioinformatics Market is the acute shortage of skilled professionals who can effectively bridge the gap between structural biology and data science. The industry demands a workforce with "bilingual" proficiency, capable of understanding molecular interactions while applying advanced algorithmic modeling and machine learning. As proteomic data volumes surge, the inability to recruit staff who can manage this information creates research bottlenecks, delaying drug discovery timelines and diminishing the return on R&D investments.
This workforce deficiency significantly restricts the industry's ability to adopt and scale sophisticated computational tools. In 2025, the Pistoia Alliance reported that 34 percent of life science laboratories identified a lack of in-house skills as the main obstacle to adopting artificial intelligence, a figure that has increased from previous years. Without qualified personnel to architect and maintain complex bioinformatics pipelines, companies face difficulties in operationalizing high-throughput structural data, which ultimately stalls market expansion and the application of precision medicine.
Market Trends
The integration of deep learning and AI is rapidly evolving from predicting single protein chains to modeling complex, multi-modal biological assemblies involving DNA, RNA, and small molecules. New computational frameworks address historical limitations in modeling heterogeneous systems, offering a more holistic view of cellular machinery and dynamic interaction networks. For instance, Google DeepMind's AlphaFold 3, released in May 2024, demonstrated a 50 percent improvement in prediction accuracy for protein interactions compared to existing methods, signifying a major technological leap.
Concurrently, the sector is witnessing a shift toward de novo protein design, moving from analyzing existing entities to generating novel, programmable structures via generative AI. This approach enables the creation of purpose-built enzymes and binders with sequences that do not exist in nature, effectively bypassing evolutionary constraints. This trend is exemplified by EvolutionaryScale, which secured $142 million in June 2024 to advance its ESM3 model, successfully designing a novel fluorescent protein distinct from natural variants.
Report Scope
In this report, the Global Structural Bioinformatics Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:
Company Profiles: Detailed analysis of the major companies present in the Global Structural Bioinformatics Market.
Global Structural Bioinformatics Market report with the given market data, TechSci Research offers customizations according to a company's specific needs. The following customization options are available for the report: