Detection of circular permutations by Protein Language Models
Fuente:
arXiv
Enregistré dans:
| Auteurs principaux: | , , |
|---|---|
| Format: | Preprint |
| Publié: |
2024
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
| _version_ | 1866916348071772160 |
|---|---|
| author | Hu, Yue Huang, Bin Zang, Chunzi |
| author_facet | Hu, Yue Huang, Bin Zang, Chunzi |
| contents | Protein circular permutations are crucial for understanding protein evolution and functionality. Traditional detection methods, sequence-based or structure-based, struggle with accuracy and computational efficiency, the latter also limited by treating proteins as rigid bodies. The plmCP method, utilizing a protein language model, not only speeds up the detection process but also enhances the accuracy of identifying circular permutations, contributing significantly to protein research and engineering by acknowledging structural flexibility. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_15087 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Detection of circular permutations by Protein Language Models Hu, Yue Huang, Bin Zang, Chunzi Quantitative Methods Protein circular permutations are crucial for understanding protein evolution and functionality. Traditional detection methods, sequence-based or structure-based, struggle with accuracy and computational efficiency, the latter also limited by treating proteins as rigid bodies. The plmCP method, utilizing a protein language model, not only speeds up the detection process but also enhances the accuracy of identifying circular permutations, contributing significantly to protein research and engineering by acknowledging structural flexibility. |
| title | Detection of circular permutations by Protein Language Models |
| topic | Quantitative Methods |
| url | https://arxiv.org/abs/2404.15087 |