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<p>Understanding protein architecture and predicting its structural tolerance to profound remodeling is pivotal for engineering functional proteins. We present SplitSeek-Pro, a deep learning model that evaluates amino acid-level splittability in folded proteins, a property critical for protein engineering tasks such as circular permutation and split reconstitution. By integrating primary sequences with 3D structural features, SplitSeek-Pro achieves residue-resolution predictions through a two-stage training process: large-scale pre-training followed by high-quality fine-tuning. Experimental validation on three distinct proteins confirms its superior predictive power over existing methods. Notably, SplitSeek-Pro identifies characteristic segments that function as cohesive, integral fragments analogous to super-secondary structural motifs. These results establish SplitSeek-Pro as a robust tool for rational protein engineering and offer insights into the fundamental structural building blocks of protein folding. To facilitate community access, we provide an automated web server at <a href="http://splitseek.topo.bio">http://splitseek.topo.bio</a>.</p>

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SplitSeek-Pro: accurate prediction of splittable sites on protein structures

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年6月18日

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  • Yu-Xiang Wang,
  • Fengyi Jiang,
  • Tingjie Xu,
  • Lan-Xin Xing,
  • Yajie Liu,
  • Zhiwei Nie,
  • Jie Chen,
  • Wen-Bin Zhang

摘要

Understanding protein architecture and predicting its structural tolerance to profound remodeling is pivotal for engineering functional proteins. We present SplitSeek-Pro, a deep learning model that evaluates amino acid-level splittability in folded proteins, a property critical for protein engineering tasks such as circular permutation and split reconstitution. By integrating primary sequences with 3D structural features, SplitSeek-Pro achieves residue-resolution predictions through a two-stage training process: large-scale pre-training followed by high-quality fine-tuning. Experimental validation on three distinct proteins confirms its superior predictive power over existing methods. Notably, SplitSeek-Pro identifies characteristic segments that function as cohesive, integral fragments analogous to super-secondary structural motifs. These results establish SplitSeek-Pro as a robust tool for rational protein engineering and offer insights into the fundamental structural building blocks of protein folding. To facilitate community access, we provide an automated web server at http://splitseek.topo.bio.