标题： BioScore：一种用于多样化生物分子复合物的基础评分函数 显示英文标题

标题： BioScore: A Foundational Scoring Function For Diverse Biomolecular Complexes

摘要： 生物分子复合物的结构评估对于将分子模型转化为功能见解至关重要，这有助于我们理解生物学并促进药物发现。然而，当前基于结构的评分函数在不同生物分子系统中往往缺乏通用性。我们提出了BioScore，这是一种基础评分函数，通过具有定制模块的双尺度几何图学习框架，解决了数据稀疏性、跨系统表示和任务兼容性等关键挑战，用于结构评估和亲和力预测。BioScore支持多种任务，包括亲和力预测、构象排序和基于结构的虚拟筛选。在涵盖蛋白质、核酸、小分子和碳水化合物的16个基准测试中，BioScore始终优于或匹配70种传统方法和深度学习方法。我们新提出的PPI基准进一步实现了对蛋白质-蛋白质复合物评分的全面评估。BioScore表现出广泛的应用性：(1) 在混合结构数据上进行预训练，可使蛋白质-蛋白质亲和力预测提高多达40%，抗原-抗体结合相关性提高超过90%；(2) 跨系统通用性使得零样本和少样本预测的相关性提升高达71%；(3) 其统一表示能够捕捉化学挑战性系统，如环肽，使亲和力预测提高超过60%。BioScore为复杂生物分子景观中的结构评估建立了一个强大且通用的框架。 显示英文摘要

摘要： Structural assessment of biomolecular complexes is vital for translating molecular models into functional insights, shaping our understanding of biology and aiding drug discovery. However, current structure-based scoring functions often lack generalizability across diverse biomolecular systems. We present BioScore, a foundational scoring function that addresses key challenges -- data sparsity, cross-system representation, and task compatibility -- through a dual-scale geometric graph learning framework with tailored modules for structure assessment and affinity prediction. BioScore supports a wide range of tasks, including affinity prediction, conformation ranking, and structure-based virtual screening. Evaluated on 16 benchmarks spanning proteins, nucleic acids, small molecules, and carbohydrates, BioScore consistently outperforms or matches 70 traditional and deep learning methods. Our newly proposed PPI Benchmark further enables comprehensive evaluation of protein-protein complex scoring. BioScore demonstrates broad applicability: (1) pretraining on mixed-structure data boosts protein-protein affinity prediction by up to 40% and antigen-antibody binding correlation by over 90%; (2) cross-system generalizability enables zero- and few-shot prediction with up to 71% correlation gain; and (3) its unified representation captures chemically challenging systems such as cyclic peptides, improving affinity prediction by over 60%. BioScore establishes a robust and generalizable framework for structural assessment across complex biomolecular landscapes.