Into the Unknown: From Structure to Disorder in Protein Function Prediction
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arXiv
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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866913923443195904 |
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| author | Kolarić, Đesika Chow, Chi Fung Willis Zhu, Rita Zi Toth-Petroczy, Agnes Alderson, T. Reid Pritišanac, Iva |
| author_facet | Kolarić, Đesika Chow, Chi Fung Willis Zhu, Rita Zi Toth-Petroczy, Agnes Alderson, T. Reid Pritišanac, Iva |
| contents | Intrinsically disordered regions (IDRs) account for one-third of the human proteome and play essential biological roles. However, predicting the functions of IDRs remains a major challenge due to their lack of stable structures, rapid sequence evolution, and context-dependent behavior. Many predictors of protein function neglect or underperform on IDRs. Recent advances in computational biology and machine learning, including protein language models, alignment-free approaches, and IDR-specific methods, have revealed conserved bulk features and local motifs within IDRs that are linked to function. This review highlights emerging computational methods that map the sequence-function relationship in IDRs, outlines critical challenges in IDR function annotation, and proposes a community-driven framework to accelerate interpretable functional predictions for IDRs. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_06004 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Into the Unknown: From Structure to Disorder in Protein Function Prediction Kolarić, Đesika Chow, Chi Fung Willis Zhu, Rita Zi Toth-Petroczy, Agnes Alderson, T. Reid Pritišanac, Iva Biomolecules Intrinsically disordered regions (IDRs) account for one-third of the human proteome and play essential biological roles. However, predicting the functions of IDRs remains a major challenge due to their lack of stable structures, rapid sequence evolution, and context-dependent behavior. Many predictors of protein function neglect or underperform on IDRs. Recent advances in computational biology and machine learning, including protein language models, alignment-free approaches, and IDR-specific methods, have revealed conserved bulk features and local motifs within IDRs that are linked to function. This review highlights emerging computational methods that map the sequence-function relationship in IDRs, outlines critical challenges in IDR function annotation, and proposes a community-driven framework to accelerate interpretable functional predictions for IDRs. |
| title | Into the Unknown: From Structure to Disorder in Protein Function Prediction |
| topic | Biomolecules |
| url | https://arxiv.org/abs/2506.06004 |