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arXiv 2602.16255q-bio.BMmath-phmath.MPnlin.PSnlin.SI
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离散Hasimoto映射的分段可积性用于分析和设计螺旋肽

Piecewise integrability of the discrete Hasimoto map for analytic prediction and design of helical peptides

College of Mathematics and System Science, Xinjiang University(新疆大学数学与系统科学学院);Xinjiang Key Laboratory of Biological Resources and Genetic Engineering, College of Life Science and Technology, Xinjiang University(新疆大学生命科学与技术学院);Shenzhen X-Institute(深圳X研究院)

Yiquan Wang

AI总结:

本研究通过分析螺旋肽的分段可积性,利用离散Hasimoto映射实现高精度主链结构预测与设计,揭示扭率非均匀性是偏离可积性的主因。

摘要:

通过离散非线性薛定谔方程表示蛋白质主链几何结构,为生物结构与可积系统之间的理论联系提供了桥梁。尽管该框架的全局应用受到手性退化和非局部相互作用的限制,螺旋肽可以被建模为分段可积系统,在特定几何边界内离散Hasimoto映射仍然适用。我们通过分析映射(ϕ,ψ)→(κ,τ)将生化二面角与弗莱奈框架参数联系起来,针对50条螺旋肽链进行分析。这种转换是全局信息保持的,但在螺旋盆地内(中位数雅可比条件数31)是病态的,表明手性信息损失主要源于局部坐标压缩,而非拓扑奇点。利用从离散色散关系导出的局部可积性误差E[n],我们显示偏离可积性的主要驱动因素是扭率非均匀性,而曲率保持刚性。该度量标准识别出可积岛屿,其中分析色散关系可对主链坐标进行亚埃精度(中位数RMSD 0.77 Å)的预测,从而实现一种分割策略,以隔离结构缺陷并修剪非可积终端模糊部分。仅评估这些可积岛屿,色散关系可为数据集的88%提取高精度结构核心。在定义的可积性区域内,逆主链设计是可行的,其中设计约束本质上减少为控制扭率均匀性。这些发现将Hasimoto形式化从定性描述推进到精确的定量框架,用于分析和设计局部蛋白质几何结构,限于分段可积性范围内。

英文摘要:

The representation of protein backbone geometry through the discrete nonlinear Schrödinger equation provides a theoretical connection between biological structure and integrable systems. Although the global application of this framework is constrained by chiral degeneracies and non-local interactions, helical peptides can be modeled as piecewise integrable systems where the discrete Hasimoto map remains applicable within specific geometric boundaries. We delineate these boundaries through an analytic mapping $(ϕ,ψ) \rightarrow (κ,τ)$ between biochemical dihedral angles and Frenet frame parameters for 50 helical peptide chains. This transformation is globally information-preserving but ill-conditioned within the helical basin (median Jacobian condition number 31), suggesting chiral information loss arises primarily from local coordinate compression rather than topological singularities. Using a local integrability error $E[n]$ derived from the discrete dispersion relation, we show deviations from integrability are driven predominantly by torsion non-uniformity, while curvature remains rigid. This metric identifies integrable islands where the analytic dispersion relation predicts backbone coordinates with sub-angstrom accuracy (median RMSD 0.77\,Å), enabling a segmentation strategy that isolates structural defects and trims non-integrable terminal fraying. Evaluating only these integrable islands, the dispersion relation extracts high-accuracy structural cores for 88\% of the dataset. Inverse backbone design is feasible within a defined integrability zone where the design constraint reduces essentially to controlling torsion uniformity. These findings advance the Hasimoto formalism from a qualitative descriptor toward a precise quantitative framework for analyzing and designing local protein geometry within the limits of piecewise integrability.

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