GraphATT-DTA: Attention-Based Novel Representation of Interaction to Predict Drug-Target Binding Affinity [PDF]
, 2022 Drug-target binding affinity (DTA) prediction is an essential step in drug discovery. Drug-target protein binding occurs at specific regions between the protein and drug, rather than the entire protein and drug.
Bae, Haelee +3 more
core +1 more source
Explainable deep drug–target representations for binding affinity prediction
BMC Bioinformatics, 2022 Background Several computational advances have been achieved in the drug discovery field, promoting the identification of novel drug–target interactions and new leads. However, most of these methodologies have been overlooking the importance of providing
Nelson R. C. Monteiro +5 more
doaj +1 more source
FingerDTA: A Fingerprint-Embedding Framework for Drug-Target Binding Affinity Prediction
Big Data Mining and Analytics, 2023 Many efforts have been exerted toward screening potential drugs for targets, and conducting wet experiments remains a laborious and time-consuming approach.
Xuekai Zhu +5 more
doaj +1 more source
GANsDTA: Predicting Drug-Target Binding Affinity Using GANs
Frontiers in Genetics, 2020 The computational prediction of interactions between drugs and targets is a standing challenge in drug discovery. State-of-the-art methods for drug-target interaction prediction are primarily based on supervised machine learning with known label ...
Lingling Zhao +4 more
doaj +1 more source
Neural Networks, 2023 The accurate prediction of drug-target affinity (DTA) is a crucial step in drug discovery and design. Traditional experiments are very expensive and time-consuming.
Hong-Jie Wu +7 more
semanticscholar +1 more source
DTA+VAE: Drug Target Affinity prediction with SELFIES String via variational autoencoder and Transformer6 protein model [PDF]
, 2023 A crucial step in drug discovery is identifying drug-target interactions. Over the years, there have been many computational methods to determine whether a drug and a target will interact or not.
Patel, Yakin
core +1 more source
Drug–target affinity prediction using graph neural network and contact maps
RSC Advances, 2020 Computer-aided drug design uses high-performance computers to simulate the tasks in drug design, which is a promising research area. Drug–target affinity (DTA) prediction is the most important step of computer-aided drug design, which could speed up drug
Mingjian Jiang +6 more
semanticscholar +1 more source
Breaking the barriers of data scarcity in drug-target affinity prediction [PDF]
Briefings Bioinform., 2022 Accurate prediction of drug-target affinity (DTA) is of vital importance in early-stage drug discovery, facilitating the identification of drugs that can effectively interact with specific targets and regulate their activities.
Qizhi Pei +8 more
semanticscholar +1 more source
Naphthoquinone derivatives exert their antitrypanosomal activity via a multi-target mechanism [PDF]
, 2013 Recently, we reported on a new class of naphthoquinone derivatives showing a promising anti-trypanosomatid profile in cell-based experiments. The lead of this series (B6, 2-phenoxy-1,4-naphthoquinone) showed an ED(50) of 80 nM against Trypanosoma brucei ...
Mazet Muriel +82 more
core +3 more sources
Mitigating cold-start problems in drug-target affinity prediction with interaction knowledge transferring [PDF]
Briefings Bioinform., 2022 Predicting the drug-target interaction is crucial for drug discovery as well as drug repurposing. Machine learning is commonly used in drug-target affinity (DTA) problem.
T. Nguyen, Thin Nguyen, T. Tran
semanticscholar +1 more source