发现进化模型难以预测罕见肽链交联结构，挑战现有蛋白结构预测范式。
Non-Canonical Crosslinks Confound Evolutionary Protein Structure Models
- 用硫-α碳交联肽构建域外测试集，突破传统进化数据限制。
- 5种未解析结构的肽中，模型精度仅0.0%至19.2% GDT-TS。
- 提示需引入物理机制模型，推动生物分子结构预测发展。
基于进化的蛋白质结构预测模型近年来取得突破性进展，但其泛化能力受限于进化先验，在缺乏丰富同源数据的序列上表现不佳。本文提出一种新的域外基准，基于硫肽类（sactipeptides）——一类核糖体合成并经翻译后修饰的肽（RiPPs），其特征为半胱氨酸残基与主链间形成硫-α碳硫醚交联。我们评估了近期模型对10个已知有明确翻译后修饰的硫肽的结构预测能力，其中5个结构尚未实验解析。这一任务对基于进化的模型构成严峻挑战，结果显示其性能有限（硫-α碳距离预测的GDT-TS仅为0.0%至19.2%）。结果表明，需发展融合物理规律的模型以持续推进生物分子结构预测。
原文摘要 · Abstract (English)
Evolution-based protein structure prediction models have achieved breakthrough success in recent years. However, they struggle to generalize beyond evolutionary priors and on sequences lacking rich homologous data. Here we present a novel, out-of-domain benchmark based on sactipeptides, a rare class of ribosomally synthesized and post-translationally modified peptides (RiPPs) characterized by sulfur-to-$α$-carbon thioether bridges creating cross-links between cysteine residues and backbone. We evaluate recent models on predicting conformations compatible with these cross-links bridges for the 10 known sactipeptides with elucidated post-translational modifications. Crucially, the structures of 5 of them have not yet been experimentally resolved. This makes the task a challenging problem for evolution-based models, which we find exhibit limited performance (0.0% to 19.2% GDT-TS on sulfur-to-$α$-carbon distance). Our results point at the need for physics-informed models to sustain progress in biomolecular structure prediction.
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