[HTML][HTML] Protein–protein interaction prediction with deep learning: A comprehensive review
Most proteins perform their biological function by interacting with themselves or other
molecules. Thus, one may obtain biological insights into protein functions, disease …
molecules. Thus, one may obtain biological insights into protein functions, disease …
Transient protein–protein interactions
SE Acuner Ozbabacan, HB Engin… - … , Design & Selection, 2011 - academic.oup.com
Transient complexes are crucial for diverse biological processes such as biochemical
pathways and signaling cascades in the cell. Here, we give an overview of the transient …
pathways and signaling cascades in the cell. Here, we give an overview of the transient …
[HTML][HTML] The global phosphorylation landscape of SARS-CoV-2 infection
M Bouhaddou, D Memon, B Meyer, KM White… - Cell, 2020 - cell.com
The causative agent of the coronavirus disease 2019 (COVID-19) pandemic, severe acute
respiratory syndrome coronavirus 2 (SARS-CoV-2), has infected millions and killed …
respiratory syndrome coronavirus 2 (SARS-CoV-2), has infected millions and killed …
ScanNet: an interpretable geometric deep learning model for structure-based protein binding site prediction
Predicting the functional sites of a protein from its structure, such as the binding sites of small
molecules, other proteins or antibodies, sheds light on its function in vivo. Currently, two …
molecules, other proteins or antibodies, sheds light on its function in vivo. Currently, two …
Deciphering interaction fingerprints from protein molecular surfaces using geometric deep learning
Predicting interactions between proteins and other biomolecules solely based on structure
remains a challenge in biology. A high-level representation of protein structure, the …
remains a challenge in biology. A high-level representation of protein structure, the …
A transformer-based ensemble framework for the prediction of protein–protein interaction sites
The identification of protein–protein interaction (PPI) sites is essential in the research of
protein function and the discovery of new drugs. So far, a variety of computational tools …
protein function and the discovery of new drugs. So far, a variety of computational tools …
Protein–protein interaction site prediction through combining local and global features with deep neural networks
Abstract Motivation Protein–protein interactions (PPIs) play important roles in many
biological processes. Conventional biological experiments for identifying PPI sites are costly …
biological processes. Conventional biological experiments for identifying PPI sites are costly …
Structure-aware protein–protein interaction site prediction using deep graph convolutional network
Motivation Protein–protein interactions (PPI) play crucial roles in many biological processes,
and identifying PPI sites is an important step for mechanistic understanding of diseases and …
and identifying PPI sites is an important step for mechanistic understanding of diseases and …
PeSTo: parameter-free geometric deep learning for accurate prediction of protein binding interfaces
LF Krapp, LA Abriata, F Cortés Rodriguez… - Nature …, 2023 - nature.com
Proteins are essential molecular building blocks of life, responsible for most biological
functions as a result of their specific molecular interactions. However, predicting their …
functions as a result of their specific molecular interactions. However, predicting their …
A compact vocabulary of paratope-epitope interactions enables predictability of antibody-antigen binding
Antibody-antigen binding relies on the specific interaction of amino acids at the paratope-
epitope interface. The predictability of antibody-antigen binding is a prerequisite for de novo …
epitope interface. The predictability of antibody-antigen binding is a prerequisite for de novo …