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Protein–RNA interaction prediction with deep learning: structure matters
Protein–RNA interactions are of vital importance to a variety of cellular activities. Both
experimental and computational techniques have been developed to study the interactions …
experimental and computational techniques have been developed to study the interactions …
Comprehensive review and empirical analysis of hallmarks of DNA-, RNA-and protein-binding residues in protein chains
Proteins interact with a variety of molecules including proteins and nucleic acids. We review
a comprehensive collection of over 50 studies that analyze and/or predict these interactions …
a comprehensive collection of over 50 studies that analyze and/or predict these interactions …
SCRIBER: accurate and partner type-specific prediction of protein-binding residues from proteins sequences
Motivation Accurate predictions of protein-binding residues (PBRs) enhances understanding
of molecular-level rules governing protein–protein interactions, helps protein–protein …
of molecular-level rules governing protein–protein interactions, helps protein–protein …
HybridDBRpred: improved sequence-based prediction of DNA-binding amino acids using annotations from structured complexes and disordered proteins
Current predictors of DNA-binding residues (DBRs) from protein sequences belong to two
distinct groups, those trained on binding annotations extracted from structured protein-DNA …
distinct groups, those trained on binding annotations extracted from structured protein-DNA …
DELPHI: accurate deep ensemble model for protein interaction sites prediction
Motivation Proteins usually perform their functions by interacting with other proteins, which is
why accurately predicting protein–protein interaction (PPI) binding sites is a fundamental …
why accurately predicting protein–protein interaction (PPI) binding sites is a fundamental …
Global, in situ analysis of the structural proteome in individuals with Parkinson's disease to identify a new class of biomarker
MT Mackmull, L Nagel, F Sesterhenn… - Nature structural & …, 2022 - nature.com
Parkinson's disease (PD) is a prevalent neurodegenerative disease for which robust
biomarkers are needed. Because protein structure reflects function, we tested whether …
biomarkers are needed. Because protein structure reflects function, we tested whether …
DeepCleave: a deep learning predictor for caspase and matrix metalloprotease substrates and cleavage sites
Motivation Proteases are enzymes that cleave target substrate proteins by catalyzing the
hydrolysis of peptide bonds between specific amino acids. While the functional proteolysis …
hydrolysis of peptide bonds between specific amino acids. While the functional proteolysis …
DisoLipPred: accurate prediction of disordered lipid-binding residues in protein sequences with deep recurrent networks and transfer learning
Motivation Intrinsically disordered protein regions interact with proteins, nucleic acids and
lipids. Regions that bind lipids are implicated in a wide spectrum of cellular functions and …
lipids. Regions that bind lipids are implicated in a wide spectrum of cellular functions and …
Single‐sequence‐based prediction of protein secondary structures and solvent accessibility by deep whole‐sequence learning
Predicting protein structure from sequence alone is challenging. Thus, the majority of
methods for protein structure prediction rely on evolutionary information from multiple …
methods for protein structure prediction rely on evolutionary information from multiple …
DescribePROT: database of amino acid-level protein structure and function predictions
We present DescribePROT, the database of predicted amino acid-level descriptors of
structure and function of proteins. DescribePROT delivers a comprehensive collection of 13 …
structure and function of proteins. DescribePROT delivers a comprehensive collection of 13 …