Researchers often model folded protein structures as graphs with amino acids as the vertices and edges representing contacts between amino acids. The vertices in these graphs are naturally ordered in the amino acid sequence order. There are many different graph construction methods and there is no ...
Many successful methods combine transformers17,18 and geometric deep learning7 representing structures as graphs or point clouds and integrate the requirement of the invariance or equivariance of the neural network23,24,25,26,27,28,29. The major breakthroughs come from the field of protein folding30...
The 3D structures of all proteins utilized in this study are downloaded in PDB format from the RCSB Protein Data Bank (https://www.rcsb.org). It limits the number of samples in both PPI datasets as the structural information is not available for all proteins. The final statistics of these...
Five different geometric self-supervised learning methods based on protein structures are further proposed to pretrain the encoder, includingMultivew Contrast,Residue Type Prediction,Distance Prediction,Angle Prediction,Dihedral Prediction. Through extensively benchmarking these pretraining techniques on diverse ...
Conclusions: GATSol captures 3D dimensional features of proteins by building protein graphs, which significantly improves the accuracy of protein solubility prediction. Recent advances in protein structure modeling allow our method to incorporate spatial structure features extracted from predicted structures ...
A non-redundant set of 455 protein oligomers is used in this study. The oligomeric protein structures as a whole are represented as graphs, with each amino acid as a node and the strength of non-covalent interactions (I, evaluated as given in the methods section) between them determining the...
Unlike fibrous proteins like collagen and gelatin that can be easily electrospun into fibril structures, the globular soy protein should be unfolded via denaturation to be enabled to produce fibrous bodies (Vega-Lugo & Lim, 2008). To solve such limitations, other synthetic/natural polymers can be...
“off-the-shelf” GNNs could incorporate some basic geometric structures of molecules, such as distances and angles, through modeling the complexes as homophilic graphs, these solutions seldom take into account the higher-level geometric attributes like curvatures and homology, and also heterophilic ...
This computation maps and visualizes the electrostatic field values induced by a protein structure, which allows studying the potential role of electrostatics in a variety of activities of these structures. Graphs All graphs were generated using PRISM GraphPad, gnuplot83, and seaborn python library84....
Bank (PDB)19, a repository of three-dimensional structures of proteins, nucleic acids, and complex assemblies, has experienced significant recent growth, reaching almost 170,000 entries. Large databases of comparative models such as SWISS-MODEL also provide valuable resources for studying structure–...