Protein–RNA interaction prediction with deep learning: structure matters

J Wei, S Chen, L Zong, X Gao, Y Li - Briefings in bioinformatics, 2022 - academic.oup.com
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 …

Comprehensive review and empirical analysis of hallmarks of DNA-, RNA-and protein-binding residues in protein chains

J Zhang, Z Ma, L Kurgan - Briefings in bioinformatics, 2019 - academic.oup.com
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 …

SCRIBER: accurate and partner type-specific prediction of protein-binding residues from proteins sequences

J Zhang, L Kurgan - Bioinformatics, 2019 - academic.oup.com
Motivation Accurate predictions of protein-binding residues (PBRs) enhances understanding
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

J Zhang, S Basu, L Kurgan - Nucleic Acids Research, 2024 - academic.oup.com
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 …

DELPHI: accurate deep ensemble model for protein interaction sites prediction

Y Li, GB Golding, L Ilie - Bioinformatics, 2021 - academic.oup.com
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 …

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 …

DeepCleave: a deep learning predictor for caspase and matrix metalloprotease substrates and cleavage sites

F Li, J Chen, A Leier, T Marquez-Lago, Q Liu… - …, 2020 - academic.oup.com
Motivation Proteases are enzymes that cleave target substrate proteins by catalyzing the
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

A Katuwawala, B Zhao, L Kurgan - Bioinformatics, 2022 - academic.oup.com
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 …

Single‐sequence‐based prediction of protein secondary structures and solvent accessibility by deep whole‐sequence learning

R Heffernan, K Paliwal, J Lyons, J Singh… - Journal of …, 2018 - Wiley Online Library
Predicting protein structure from sequence alone is challenging. Thus, the majority of
methods for protein structure prediction rely on evolutionary information from multiple …

DescribePROT: database of amino acid-level protein structure and function predictions

B Zhao, A Katuwawala, CJ Oldfield… - Nucleic Acids …, 2021 - academic.oup.com
We present DescribePROT, the database of predicted amino acid-level descriptors of
structure and function of proteins. DescribePROT delivers a comprehensive collection of 13 …