ArticleFrontiers in bioengineering and biotechnology2022
Prediction of DNA-Binding Protein-Drug-Binding Sites Using Residue Interaction Networks and Sequence Feature.
Article in Frontiers in bioengineering and biotechnology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 8 citations in OpenAlex.
- Computational approaches to druggable site identification: Current status and future perspective.Acta pharmaceutica Sinica. B · 2026Review
- iProtDNA-SMOTE: Enhancing protein-DNA binding sites prediction through imbalanced graph neural networks.PloS one · 2025Article
- Electrochemical Properties of Fused Pyrimidine-Triazole Heterocyclic Molecules as Novel Drug Candidates.Turkish journal of pharmaceutical sciences · 2024Article
- AP-2δ Is the Most Relevant Target of AP-2 Family-Focused Cancer Therapy and Affects Genome Organization.Cells · 2022Article
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
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Abstract
Identification of protein-ligand binding sites plays a critical role in drug discovery. However, there is still a lack of targeted drug prediction for DNA-binding proteins. This study aims at the binding sites of DNA-binding proteins and drugs, by mining the residue interaction network features, which can describe the local and global structure of amino acids, combined with sequence feature. The predictor of DNA-binding protein-drug-binding sites is built by employing the Extreme Gradient Boosting (XGBoost) model with random under-sampling. We found that the residue interaction network features can better characterize DNA-binding proteins, and the binding sites with high betweenness value and high closeness value are more likely to interact with drugs. The model shows that the residue interaction network features can be used as an important quantitative indicator of drug-binding sites, and this method achieves high predictive performance for the binding sites of DNA-binding protein-drug. This study will help in drug discovery research for DNA-binding proteins.
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