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Protein Interaction Mapping

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Recent advances in predicting protein-protein interactions with the aid of artificial intelligence algorithms.

Current opinion in structural biology
Protein-protein interactions (PPIs) are essential in the regulation of biological functions and cell events, therefore understanding PPIs have become a key issue to understanding the molecular mechanism and investigating the design of drugs. Here we ...

Residue-Frustration-Based Prediction of Protein-Protein Interactions Using Machine Learning.

The journal of physical chemistry. B
The study of protein-protein interactions (PPIs) is important in understanding the function of proteins. However, it is still a challenge to investigate the transient protein-protein interaction by experiments. Hence, the computational prediction for...

Harnessing protein folding neural networks for peptide-protein docking.

Nature communications
Highly accurate protein structure predictions by deep neural networks such as AlphaFold2 and RoseTTAFold have tremendous impact on structural biology and beyond. Here, we show that, although these deep learning approaches have originally been develop...

Identifying Protein Subcellular Locations With Embeddings-Based node2loc.

IEEE/ACM transactions on computational biology and bioinformatics
Identifying protein subcellular locations is an important topic in protein function prediction. Interacting proteins may share similar locations. Thus, it is imperative to infer protein subcellular locations by taking protein-protein interactions (PP...

Deep Neural Network and Extreme Gradient Boosting Based Hybrid Classifier for Improved Prediction of Protein-Protein Interaction.

IEEE/ACM transactions on computational biology and bioinformatics
Understanding the behavioral process of life and disease-causing mechanism, knowledge regarding protein-protein interactions (PPI) is essential. In this paper, a novel hybrid approach combining deep neural network (DNN) and extreme gradient boosting ...

Computed structures of core eukaryotic protein complexes.

Science (New York, N.Y.)
Protein-protein interactions play critical roles in biology, but the structures of many eukaryotic protein complexes are unknown, and there are likely many interactions not yet identified. We take advantage of advances in proteome-wide amino acid coe...

DeepRank: a deep learning framework for data mining 3D protein-protein interfaces.

Nature communications
Three-dimensional (3D) structures of protein complexes provide fundamental information to decipher biological processes at the molecular scale. The vast amount of experimentally and computationally resolved protein-protein interfaces (PPIs) offers th...

pdCSM-PPI: Using Graph-Based Signatures to Identify Protein-Protein Interaction Inhibitors.

Journal of chemical information and modeling
Protein-protein interactions are promising sites for development of selective drugs; however, they have generally been viewed as challenging targets. Molecules targeting protein-protein interactions tend to be larger and more lipophilic than other dr...

Improved protein contact prediction using dimensional hybrid residual networks and singularity enhanced loss function.

Briefings in bioinformatics
Deep residual learning has shown great success in protein contact prediction. In this study, a new deep residual learning-based protein contact prediction model was developed. Comparing with previous models, a new type of residual block hybridizing 1...