双势能耦合统一场框架:面向结构生物学三大核心瓶颈的第一性原理理论研究 Title: A First-Principle Research on Dual Potential Coupling Unified Framework for Three Core Bottlenecks in Structural Biology

当前结构生物学发展进程中存在三项关键难题:天然多糖无对应基因编码序列,依托氨基酸数据集训练的AlphaFold等序列类人工智能无法实现多糖从头构象预测;冷冻电镜仅能捕获膜蛋白瞬时静态构型,难以完整描述跨膜离子梯度诱导的蛋白全周期构象开闭变化;分子量小于50 kDa的小分子蛋白受热扰动影响显著,结晶筛选缺乏成熟理论指导,实验筛选随机性强、研发成本偏高。本文基于对立统一物理思想,建立内源束缚势与环境耗散势构成的双势能耦合统一场理论体系,依托统计力学推导系列核心方程,从第一性原理视角弥补现有算法与传统分子模拟方法的短板,针对三类行业难题分别设计系统化攻关思路。全文仅开展理论构建与后续科研方案规划,无任何实测数据与仿真结果编造,可为糖生物学与膜蛋白前沿研究提供理论参考。

Abstract

Three critical challenges remain in modern structural biology. Natural polysaccharides lack genetic coding sequences, making sequence-based AI such as AlphaFold incapable of ab initio conformational prediction. Cryo-electron microscopy only captures static snapshots of membrane proteins and fails to describe full-cycle conformational transitions driven by transmembrane ionic gradients. Proteins below 50 kDa suffer strong thermal fluctuation, leading to blind crystallization screening without effective theoretical guidance and high experimental cost. Based on the physical principle of unity of opposites, this paper constructs a dual-potential coupling unified framework consisting of intrinsic binding potential and environmental dissipative potential. Core equations are derived from statistical mechanics to remedy deficiencies of existing algorithms and conventional molecular simulation methods, with targeted research routes proposed for the three bottlenecks. This paper only contains theoretical construction and follow-up research planning without fabricated experimental or simulation data, providing theoretical references for glycobiology and membrane protein research.