Multi-PLI: interpretable multi‐task deep learning model for unifying protein–ligand interaction datasets
The assessment of protein–ligand interactions is critical at early stage of drug discovery.
Computational approaches for efficiently predicting such interactions facilitate drug …
Computational approaches for efficiently predicting such interactions facilitate drug …
Correction to: A new paradigm for applying deep learning to protein–ligand interaction prediction
In the originally published version of this manuscript, there are four inaccuracies in the data
descriptions within the main text, which exhibit minor discrepancies compared to the data in …
descriptions within the main text, which exhibit minor discrepancies compared to the data in …
DeepDock: enhancing ligand-protein interaction prediction by a combination of ligand and structure information
The prediction of precise protein-ligand binding activities can accelerate drug discovery by
virtual screening-a computational technique that predicts whether a small molecule ligand is …
virtual screening-a computational technique that predicts whether a small molecule ligand is …
A new paradigm for applying deep learning to protein–ligand interaction prediction
Protein–ligand interaction prediction presents a significant challenge in drug design.
Numerous machine learning and deep learning (DL) models have been developed to …
Numerous machine learning and deep learning (DL) models have been developed to …
A cascade graph convolutional network for predicting protein–ligand binding affinity
Accurate prediction of binding affinity between protein and ligand is a very important step in
the field of drug discovery. Although there are many methods based on different …
the field of drug discovery. Although there are many methods based on different …
Predicting or pretending: artificial intelligence for protein-ligand interactions lack of sufficiently large and unbiased datasets
Predicting protein-ligand interactions using artificial intelligence (AI) models has attracted
great interest in recent years. However, data-driven AI models unequivocally suffer from a …
great interest in recent years. However, data-driven AI models unequivocally suffer from a …
Quality Matters: Deep Learning-Based Analysis of Protein-Ligand Interactions with Focus on Avoiding Bias
The efficient and accurate prediction of protein-ligand binding affinities is an extremely
appealing yet still unresolved goal in computational pharmacy. In recent years, many …
appealing yet still unresolved goal in computational pharmacy. In recent years, many …
Multi-Level Contrastive Learning for Protein-Ligand Binding Residue Prediction
Protein-ligand interactions play a crucial role in various biological functions, with their
accurate prediction being pivotal for drug discovery and design processes. Traditional …
accurate prediction being pivotal for drug discovery and design processes. Traditional …
Interactiongraphnet: A novel and efficient deep graph representation learning framework for accurate protein–ligand interaction predictions
Accurate quantification of protein–ligand interactions remains a key challenge to structure-
based drug design. However, traditional machine learning (ML)-based methods based on …
based drug design. However, traditional machine learning (ML)-based methods based on …
Binding affinity prediction for protein–ligand complex using deep attention mechanism based on intermolecular interactions
Background Accurate prediction of protein–ligand binding affinity is important for lowering
the overall cost of drug discovery in structure-based drug design. For accurate predictions …
the overall cost of drug discovery in structure-based drug design. For accurate predictions …