AI 中文总结
本研究将生物多价结合过程建模为统计力学问题，推导其为平滑交叉而非相变，提出三个约束并建立统一方程，解释抗体等体系的亲和力与选择性本质。
AI 中文摘要
生物识别极少依赖单一强键，而是通过在水中拥挤、可变形的表面间同时形成多个弱键实现。本综述将该过程发展为统计力学问题：计数两个多价对象的结合方式等价于图上的经典单体-二聚体问题，其严格结论为：多价结合的表观切换始终是平滑的交叉，而非相变。由此衍生三个约束：排斥表面层是必需的而非设计选择；键之间并非独立作用；由于自由能以指数形式进入速率，受体数量的微小变化可使结合寿命改变数个数量级。一组方程可覆盖抗体、脂蛋白和T细胞识别，在这些体系中，决定结果的并非单个键的强度，而是固定总量如何分配到多个键上：亲和力是分子的属性，选择性是组装体的属性。
英文摘要
Biological recognition rarely rests on one strong bond. It works by forming many weak ones at once, between crowded, deformable surfaces in water. This review develops that process as a problem in statistical mechanics. Counting the ways two multivalent objects can bind proves to be the classical monomer-dimer problem on a graph, with a rigorous consequence: the apparent switching of multivalent binding is always a smooth crossover, never a phase transition. Three constraints follow. A repulsive surface layer is obligatory rather than a design choice; bonds do not act independently; and since free energies enter rates exponentially, small changes in receptor number shift binding lifetimes by orders of magnitude. One set of equations then covers antibodies, lipoproteins, and T cell recognition. In each, what decides the outcome is not the strength of any single bond but how a fixed total is spread over many: affinity is a property of a molecule, selectivity a property of an assembly.
Comments41 pages and 9 Figures
