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iNucRes-ASSH: Identifying nucleic acid-binding residues in proteins by using self-attention-based structure-sequence hybrid neural network.
- Source :
-
Proteins [Proteins] 2024 Mar; Vol. 92 (3), pp. 395-410. Date of Electronic Publication: 2023 Nov 01. - Publication Year :
- 2024
-
Abstract
- Interaction between proteins and nucleic acids is crucial to many cellular activities. Accurately detecting nucleic acid-binding residues (NABRs) in proteins can help researchers better understand the interaction mechanism between proteins and nucleic acids. Structure-based methods can generally make more accurate predictions than sequence-based methods. However, the existing structure-based methods are sensitive to protein conformational changes, causing limited generalizability. More effective and robust approaches should be further explored. In this study, we propose iNucRes-ASSH to identify nucleic acid-binding residues with a self-attention-based structure-sequence hybrid neural network. It improves the generalizability and robustness of NABR prediction from two levels: residue representation and prediction model. Experimental results show that iNucRes-ASSH can predict the nucleic acid-binding residues even when the experimentally validated structures are unavailable and outperforms five competing methods on a recent benchmark dataset and a widely used test dataset.<br /> (© 2023 Wiley Periodicals LLC.)
- Subjects :
- Proteins chemistry
Neural Networks, Computer
Algorithms
Nucleic Acids
Subjects
Details
- Language :
- English
- ISSN :
- 1097-0134
- Volume :
- 92
- Issue :
- 3
- Database :
- MEDLINE
- Journal :
- Proteins
- Publication Type :
- Academic Journal
- Accession number :
- 37915276
- Full Text :
- https://doi.org/10.1002/prot.26626