Results 11 to 20 of about 5,508,972 (143)

DeepMHADTA: Prediction of Drug-Target Binding Affinity Using Multi-Head Self-Attention and Convolutional Neural Network

open access: yesCurrent Issues in Molecular Biology, 2022
Drug-target interactions provide insight into the drug-side effects and drug repositioning. However, wet-lab biochemical experiments are time-consuming and labor-intensive, and are insufficient to meet the pressing demand for drug research and ...
Lei Deng   +4 more
doaj   +2 more sources

Drug-Online: an online platform for drug-target interaction, affinity, and binding sites identification using deep learning

open access: yesBMC Bioinformatics
Background Accurately identifying drug-target interaction (DTI), affinity (DTA), and binding sites (DTS) is crucial for drug screening, repositioning, and design, as well as for understanding the functions of target.
Xin Zeng   +5 more
doaj   +2 more sources

BiComp-DTA: Drug-target binding affinity prediction through complementary biological-related and compression-based featurization approach.

open access: yesPLoS Computational Biology, 2023
Drug-target binding affinity prediction plays a key role in the early stage of drug discovery. Numerous experimental and data-driven approaches have been developed for predicting drug-target binding affinity.
Mahmood Kalemati   +2 more
doaj   +2 more sources

Drug-target binding affinity prediction based on power graph and word2vec

open access: yesBMC Medical Genomics
Background Drug and protein targets affect the physiological functions and metabolic effects of the body through bonding reactions, and accurate prediction of drug-protein target interactions is crucial for drug development.
Jing Hu   +4 more
doaj   +2 more sources

Prediction of Drug-Target Affinity Using Attention Neural Network

open access: yesInternational Journal of Molecular Sciences
Studying drug-target interactions (DTIs) is the foundational and crucial phase in drug discovery. Biochemical experiments, while being the most reliable method for determining drug-target affinity (DTA), are time-consuming and costly, making it ...
Xin Tang, Xiu-Juan Lei, Yuchen Zhang
semanticscholar   +2 more sources

Affinity2Vec: drug-target binding affinity prediction through representation learning, graph mining, and machine learning

open access: yesScientific Reports, 2022
Drug-target interaction (DTI) prediction plays a crucial role in drug repositioning and virtual drug screening. Most DTI prediction methods cast the problem as a binary classification task to predict if interactions exist or as a regression task to ...
Maha A. Thafar   +5 more
doaj   +2 more sources

EMPDTA: An End-to-End Multimodal Representation Learning Framework with Pocket Online Detection for Drug–Target Affinity Prediction

open access: yesMolecules
Accurately predicting drug–target interactions is a critical yet challenging task in drug discovery. Traditionally, pocket detection and drug–target affinity prediction have been treated as separate aspects of drug–target interaction, with few methods ...
Dingkai Huang, Jiang Xie
doaj   +2 more sources

Drug–Target Affinity Prediction Based on Cross-Modal Fusion of Text and Graph

open access: yesApplied Sciences
Drug–target affinity (DTA) prediction is a critical step in virtual screening and significantly accelerates drug development. However, existing deep learning-based methods relying on single-modal representations (e.g., text or graphs) struggle to fully ...
Jucheng Yang, Fushun Ren
doaj   +2 more sources

Studies and analysis of drug-target interactions by affinity chromatography and related techniques: A review

open access: yesJournal of Pharmaceutical Analysis
The characterization of drug-target interactions is a key component of drug discovery, testing, and development. Affinity chromatography is one approach that can be used for this type of analysis.
David S. Hage   +7 more
doaj   +2 more sources

Drug-target affinity prediction using applicability domain based on data density [PDF]

open access: yes, 2021
In the pursuit of research and development of drug discovery, the computational prediction of the target affinity of a drug candidate is useful for screening compounds at an early stage and for verifying the binding potential to an unknown target.
Shunya, Sugita, Masahito, Ohue
core   +1 more source

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