Results 301 to 310 of about 2,729,950 (336)
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Journal of Chemical Information and Modeling, 2019
We propose a novel deep learning approach for predicting drug-target interaction using a graph neural network. We introduce a distance-aware graph attention algorithm to differentiate various types of intermolecular interactions.
Jaechang Lim +5 more
semanticscholar +1 more source
We propose a novel deep learning approach for predicting drug-target interaction using a graph neural network. We introduce a distance-aware graph attention algorithm to differentiate various types of intermolecular interactions.
Jaechang Lim +5 more
semanticscholar +1 more source
Predicting Drug-Target Interaction Via Self-Supervised Learning
IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2023Recent advances in graph representation learning provide new opportunities for computational drug-target interaction (DTI) prediction. However, it still suffers from deficiencies of dependence on manual labels and vulnerability to attacks. Inspired by the success of self-supervised learning (SSL) algorithms, which can leverage input data itself as ...
Jiatao Chen +5 more
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GSL-DTI: Graph Structure Learning Network for Drug-Target Interaction Prediction.
MethodsMOTIVATION Drug-target interaction prediction is an important area of research to predict whether there is an interaction between a drug molecule and its target protein.
Z. E., Guanyu Qiao, Guohua Wang, Yang Li
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Multi-View Drug Target Interaction Prediction
2021, (Drug-Target Interaction DTI).
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Machine learning in drug-target interaction prediction: current state and future directions.
Drug Discovery Today, 2020Predicting the strength of binding affinity between compounds and proteins with reasonable accuracy is crucial in drug discovery. Computational prediction of binding affinity between compounds and targets greatly enhances the probability of finding lead ...
Sofia D'souza, P. K. V., Balaji S
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Characterizing Drug–Target Interactions: Shifting towards the Clinic
Trends in Pharmacological Sciences, 2020Recently, Perrin et al. reported the application of thermal proteome profiling (TPP), a cellular thermal shift assay with an unbiased proteomics readout to complex tissue samples from model organisms and patient-derived whole blood. This study demonstrates for the first time that TPP enables organ-specific drug target engagement and identification ...
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Protein-Protein Interactions as Drug Targets
2012Over the last two decades, a number of protein-protein interactions (PPIs) have been targeted by the pharmaceutical industry. Pharma as a whole has historically considered PPIs to be undruggable or at the very least high-risk targets, and the relative lack of success in modulating PPIs with small molecules has done little to change this prevailing view.
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Inferring Chemogenomic Features from Drug‐Target Interaction Networks
Molecular Informatics, 2013AbstractDrug effects are mainly caused by the interactions between drug molecules and target proteins including primary targets and off‐targets. Understanding of the molecular mechanisms behind overall drugtarget interactions is crucial in the drug design process.
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Drug-Target Interaction Prediction with PIGLET
bioRxivDrug-target interaction (DTI) prediction is a key task for computed-aided drug development that has been widely approached by deep learning models.
K. A. Carpenter, R. Altman
semanticscholar +1 more source
Supervised graph co-contrastive learning for drug-target interaction prediction
Bioinform., 2022Yang Li +3 more
semanticscholar +1 more source