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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Accesso online: | https://arxiv.org/abs/2503.17368 |
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| _version_ | 1866912286715674624 |
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| author | Lacombe, Romain |
| author_facet | Lacombe, Romain |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_17368 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Non-Canonical Crosslinks Confound Evolutionary Protein Structure Models Lacombe, Romain Biomolecules Artificial Intelligence 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. |
| title | Non-Canonical Crosslinks Confound Evolutionary Protein Structure Models |
| topic | Biomolecules Artificial Intelligence |
| url | https://arxiv.org/abs/2503.17368 |