The prediction of interactions between proteins using the graph-based technique can be implemented in two ways: molecular structure-based and PPI network-based. Yang et al.35 have proposed the signed variational graph auto-encoder (S-VGAE) to predict the interactions between proteins by considering...
Recent breakthroughs in highly accurate protein structure prediction using deep neural networks have made considerable progress in solving the structure prediction component of the ‘protein folding problem’. However, predicting detailed mechanisms of h
The quaternary structure (QS) of a protein is determined by measuring its molecular weight in solution. The data have to be extracted from the literature, and they may be missing even for proteins that have a crystal structure reported in the Protein Data Bank (PDB). The PDB and other data...
Navigating the landscape of enzyme design: from molecular simulations to machine learning Jiahui Zhoua, Meilan Huang Chemical Society Reviews (2024) Structure Prediction and Computational Protein Design for Efficient Biocatalysts and Bioactive Proteins Rebecca Buller, Jiri Damborsky, Donald Hilvert, Uwe Bo...
Qi YJ, Klein-Seetharaman J, Bar-Joseph Z: Random forest similarity for protein-protein interaction prediction from multiple sources. 2005, Singapore: World Scientific Publ Co Pte Ltd Google Scholar Shi M-G, Xia J-F, Li X-L, Huang D-S: Predicting protein-protein interactions from sequence...
Protein folding has become a tractable problem with the significant advances in deep learning-driven protein structure prediction. Here we propose FoldPAthreader, a protein folding pathway prediction method that uses a novel folding force field model by
A kernel machine could for instance predict whether a protein is an enzyme or not (binary classification), in terms of weighted similarity to other proteins. Being similar to an enzymexiwill drive the prediction towards the positive (enzyme) class (positive weightwi), while being similar to a...
An expanded evaluation of protein function prediction methods shows an improvement in accuracy. Genome Biol. 2016;17(1):1–19. Article Google Scholar Johnson A, Lewis J, Alberts B. Molecular biology of the cell. New York: Garland Science; 2002. Google Scholar Kaltofen E, Trager BM. ...
Familial thrombophilia due to a previously unrecognized mechanism characterized by poor anticoagulant response to activated protein C: Prediction of a cofactor to activated protein C Proc Natl Acad Sci USA, 90 (1993), p. 1004 CrossrefView in ScopusGoogle Scholar 25 Bertina RM, Koeleman BPC, Koster...
Here, we use RosettaDock to assemble protein complex subunits that were generated using AF2 and employ covalent labeling data to improve protein complex structure prediction. In this study, we develop the computational framework (Supplementary Fig. 1) for using covalent labeling data in protein ...