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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2504.00764 |
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| _version_ | 1866909785010470912 |
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| author | Yang, Li Wang, Dongbo |
| author_facet | Yang, Li Wang, Dongbo |
| contents | How DNA-binding proteins locate specific genomic targets remains a central challenge in molecular biology. Traditional protein-centric approaches, which rely on wet-lab experiments and visualization techniques, often lack genome-wide resolution and fail to capture physiological dynamics in living cells. Here, we introduce a DNA-centric strategy that leverages in vivo N6-methyladenine (6mA) data to decode the logic of protein-DNA recognition. By integrating linguistically inspired modeling with machine learning, we reveal two distinct search modes: a protein-driven diffusion mechanism and a DNA sequence-driven mechanism, wherein specific motifs function as protein traps. We further reconstruct high-resolution interaction landscapes at the level of individual sequences and trace the evolutionary trajectories of recognition motifs across species. This framework addresses fundamental limitations of protein-centered approaches and positions DNA itself as an intrinsic reporter of protein-binding behavior. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_00764 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A DNA-Centric Mechanism for Protein Targeting in 6mA Methylation Yang, Li Wang, Dongbo Quantitative Methods How DNA-binding proteins locate specific genomic targets remains a central challenge in molecular biology. Traditional protein-centric approaches, which rely on wet-lab experiments and visualization techniques, often lack genome-wide resolution and fail to capture physiological dynamics in living cells. Here, we introduce a DNA-centric strategy that leverages in vivo N6-methyladenine (6mA) data to decode the logic of protein-DNA recognition. By integrating linguistically inspired modeling with machine learning, we reveal two distinct search modes: a protein-driven diffusion mechanism and a DNA sequence-driven mechanism, wherein specific motifs function as protein traps. We further reconstruct high-resolution interaction landscapes at the level of individual sequences and trace the evolutionary trajectories of recognition motifs across species. This framework addresses fundamental limitations of protein-centered approaches and positions DNA itself as an intrinsic reporter of protein-binding behavior. |
| title | A DNA-Centric Mechanism for Protein Targeting in 6mA Methylation |
| topic | Quantitative Methods |
| url | https://arxiv.org/abs/2504.00764 |