[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 …
Computational approaches for the design of modulators targeting protein-protein interactions
ABSTRACT Background Protein-protein interactions (PPIs) are intriguing targets for
designing novel small-molecule inhibitors. The role of PPIs in various infectious and …
designing novel small-molecule inhibitors. The role of PPIs in various infectious and …
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 …
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 …
AlphaFold2-aware protein–DNA binding site prediction using graph transformer
Protein–DNA interactions play crucial roles in the biological systems, and identifying protein–
DNA binding sites is the first step for mechanistic understanding of various biological …
DNA binding sites is the first step for mechanistic understanding of various 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 …
Fast and accurate protein function prediction from sequence through pretrained language model and homology-based label diffusion
Protein function prediction is an essential task in bioinformatics which benefits disease
mechanism elucidation and drug target discovery. Due to the explosive growth of proteins in …
mechanism elucidation and drug target discovery. Due to the explosive growth of proteins in …
Open-source machine learning in computational chemistry
The field of computational chemistry has seen a significant increase in the integration of
machine learning concepts and algorithms. In this Perspective, we surveyed 179 open …
machine learning concepts and algorithms. In this Perspective, we surveyed 179 open …
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 …
Machine learning on protein–protein interaction prediction: models, challenges and trends
Protein–protein interactions (PPIs) carry out the cellular processes of all living organisms.
Experimental methods for PPI detection suffer from high cost and false-positive rate, hence …
Experimental methods for PPI detection suffer from high cost and false-positive rate, hence …