ArkDTA: attention regularization guided by non-covalent interactions for explainable drug-target binding affinity prediction. [PDF]
Bioinformatics, 2023 Motivation Protein–ligand binding affinity prediction is a central task in drug design and development. Cross-modal attention mechanism has recently become a core component of many deep learning models due to its potential to improve model explainability.
Gim M +7 more
europepmc +2 more sources
GeneralizedDTA: combining pre-training and multi-task learning to predict drug-target binding affinity for unknown drug discovery. [PDF]
BMC Bioinformatics, 2022 Accurately predicting drug-target binding affinity (DTA) in silico plays an important role in drug discovery. Most of the computational methods developed for predicting DTA use machine learning models, especially deep neural networks, and depend on large-
Lin S, Shi C, Chen J.
europepmc +2 more sources
WideDTA: prediction of drug-target binding affinity
CoRR, 2019 Motivation: Prediction of the interaction affinity between proteins and compounds is a major challenge in the drug discovery process. WideDTA is a deep-learning based prediction model that employs chemical and biological textual sequence information to predict binding affinity.
Hakime Öztürk +2 more
openaire +2 more sources
Optimized hydrophobic interactions and hydrogen bonding at the target-ligand interface leads the pathways of drug-designing. [PDF]
PLoS ONE, 2010 Weak intermolecular interactions such as hydrogen bonding and hydrophobic interactions are key players in stabilizing energetically-favored ligands, in an open conformational environment of protein structures.
Rohan Patil +5 more
doaj +1 more source
Journal of Cheminformatics, 2022 Motivation Drug-target binding affinity (DTA) reflects the strength of the drug-target interaction; therefore, predicting the DTA can considerably benefit drug discovery by narrowing the search space and pruning drug-target (DT) pairs with low binding ...
Junjie Wang +4 more
doaj +1 more source
Metabolites, 2022 Affinity selection-mass spectrometry (AS-MS) is a label-free binding assay system that uses UHPLC-MS size-based separation methods to separate target-compound complexes from unbound compounds, identify bound compounds, classify compound binding sites ...
Thabo Ramatapa +5 more
doaj +1 more source
Structure-inclusive similarity based directed GNN: a method that can control information flow to predict drug-target binding affinity. [PDF]
BioinformaticsMotivation Exploring the association between drugs and targets is essential for drug discovery and repurposing. Comparing with the traditional methods that regard the exploration as a binary classification task, predicting the drug–target binding ...
Huang J +6 more
europepmc +2 more sources
Journal of Clinical Tuberculosis and Other Mycobacterial Diseases, 2021 Background: Mycobacterium tuberculosis protein target (DNA gyrase) is a type II topoisomerase target present in all bacteria. The enzyme comprises of two subunits A and B.
Gideon Adamu Shallangwa +1 more
doaj +1 more source
Probing the interaction of the diarylquinoline TMC207 with its target mycobacterial ATP synthase. [PDF]
PLoS ONE, 2011 Infections with Mycobacterium tuberculosis are substantially increasing on a worldwide scale and new antibiotics are urgently needed to combat concomitantly emerging drug-resistant mycobacterial strains.
Anna C Haagsma +6 more
doaj +1 more source
ResDTA: Predicting Drug-Target Binding Affinity Using Residual Skip Connections
CoRR, 2023 40 pages, 10 figures, 2 tables.
Partho Ghosh, Md. Aynal Haque
openaire +2 more sources