Proteins are the essential biological macromolecules required to perform nearly all biological processes, and cellular functions. Proteins rarely carry out their tasks in isolation but interact with other proteins (known as protein–protein interaction)
and proteins and identify the binding residues along the peptides involved in the interactions. In addition, CAMP outperformed other state-of-the-art methods on binary peptide-protein interaction prediction. CAMP can serve as a useful tool in peptide-protein interaction prediction and identification ...
26 Moreover, there is another hot task, drug–target interaction (DTI) prediction,27, 28, 29, 30, 31 which is similar to CPI prediction. Although both are essentially interactions between chemical compounds and proteins, their predictions are significantly different as follows. First, in terms ...
MAPE-PPI: Towards Effective and Efficient Protein-Protein Interaction Prediction via Microenvironment-Aware Protein Embedding (Spotlight) Lirong Wu, Yijun Tian, Yufei Huang, Siyuan Li, Haitao Lin, Nitesh V Chawla, Stan Z. Li. InICLR, 2024. ...
Recent advances in protein-protein interaction (PPI) prediction and structural complex research has largely been guided by identifying interologs (conserved PPI across organisms) and co-evolutionary signals between residues47. However, distinguishing paralogs from orthologs (otherwise known as the “Paralog...
& Zhou, S. Improving compound–protein interaction prediction by building up highly credible negative samples. Bioinformatics 31, i221–i229 (2015). Article Google Scholar Gilson, M. K. et al. BindingDB in 2015: a public database for medicinal chemistry, computational chemistry and systems ...
deep learning model for protein-RNA interaction prediction evaluated in this study by a large margin. To jointly incorporate RNA sequence and secondary structure graph representations (Section 2.1.1), RPINet [36] uses a modified graph convolutional network (GCN). In each layer, the current node ...
and proteins and identify the binding residues along the peptides involved in the interactions. In addition, CAMP outperformed other state-of-the-art methods on binary peptide-protein interaction prediction. CAMP can serve as a useful tool in peptide-protein interaction prediction and identification ...
最后,作者进一步研究了CAMP在三个相关任务中的应用潜力,即多肽-蛋白结合域相互作用预测(peptide-PBD interaction)、结合亲和力评估和多肽的虚拟筛选。结果表明,CAMP在这三个相关任务上均获得出色表现。 我感觉,总的来说,方法并不是很新,分别得到嵌入特征在全连接层里面进行的预测。数据处理的方面,考虑的数据种类挺多...
The rapid growth of protein-protein interaction (PPI) data has led to the emergence of PPI network analysis. Despite advances in high-throughput techniques, the interactomes of several model organisms are still far from complete. Therefore, it is desirab