Novel machine learning approaches revolutionize protein knowledge
Breakthrough methods in machine learning (ML), protein structure prediction, and novel
ultrafast structural aligners are revolutionizing structural biology. Obtaining accurate models …
ultrafast structural aligners are revolutionizing structural biology. Obtaining accurate models …
Machine learning solutions for predicting protein–protein interactions
Proteins are “social molecules.” Recent experimental evidence supports the notion that
large protein aggregates, known as biomolecular condensates, affect structurally and …
large protein aggregates, known as biomolecular condensates, affect structurally and …
PredictProtein-predicting protein structure and function for 29 years
Abstract Since 1992 PredictProtein (https://predictprotein. org) is a one-stop online resource
for protein sequence analysis with its main site hosted at the Luxembourg Centre for …
for protein sequence analysis with its main site hosted at the Luxembourg Centre for …
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 …
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 …
Protein embeddings and deep learning predict binding residues for various ligand classes
One important aspect of protein function is the binding of proteins to ligands, including small
molecules, metal ions, and macromolecules such as DNA or RNA. Despite decades of …
molecules, metal ions, and macromolecules such as DNA or RNA. Despite decades of …
Embeddings from deep learning transfer GO annotations beyond homology
Knowing protein function is crucial to advance molecular and medical biology, yet
experimental function annotations through the Gene Ontology (GO) exist for fewer than 0.5 …
experimental function annotations through the Gene Ontology (GO) exist for fewer than 0.5 …
DeepProSite: structure-aware protein binding site prediction using ESMFold and pretrained language model
Motivation Identifying the functional sites of a protein, such as the binding sites of proteins,
peptides, or other biological components, is crucial for understanding related biological …
peptides, or other biological components, is crucial for understanding related biological …
DeepDISOBind: accurate prediction of RNA-, DNA-and protein-binding intrinsically disordered residues with deep multi-task learning
Proteins with intrinsically disordered regions (IDRs) are common among eukaryotes. Many
IDRs interact with nucleic acids and proteins. Annotation of these interactions is supported …
IDRs interact with nucleic acids and proteins. Annotation of these interactions is supported …
Regulation of Rim4 distribution, function, and stability during meiosis by PKA, Cdc14, and 14-3-3 proteins
Meiotic gene expression in budding yeast is tightly controlled by RNA-binding proteins
(RBPs), with the meiosis-specific RBP Rim4 playing a key role in sequestering mid-late …
(RBPs), with the meiosis-specific RBP Rim4 playing a key role in sequestering mid-late …