DeepDTA: deep drug–target binding affinity prediction [PDF]
Bioinformatics, 2018 Abstract Motivation The identification of novel drug–target (DT) interactions is a substantial part of the drug discovery process. Most of the computational methods that have been proposed to predict DT interactions have focused on binary classification, where the goal is to determine whether a DT ...
Öztürk, Hakime +2 more
openaire +3 more sources
GraphDTA: Predicting drug–target binding affinity with graph neural networks [PDF]
Bioinformatics, 2019 AbstractThe development of new drugs is costly, time consuming, and often accompanied with safety issues. Drug repurposing can avoid the expensive and lengthy process of drug development by finding new uses for already approved drugs. In order to repurpose drugs effectively, it is useful to know which proteins are targeted by which drugs. Computational
Thin Nguyen +5 more
openaire +4 more sources
ImageDTA: A Simple Model for Drug–Target Binding Affinity Prediction
ACS OmegaPredicting the drug-target binding affinity (DTA) is crucial in drug discovery, and an increasing number of researchers are using artificial intelligence techniques to make such predictions. Many effective deep neural network prediction models have been proposed. However, current methods need improvement in accuracy, complexity, and efficiency. In this
Li Han, Ling Kang, Quan Guo
doaj +3 more sources
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
A Multibranch Neural Network for Drug-Target Affinity Prediction Using Similarity Information [PDF]
ACS OmegaJing Chen, Xiaolin Yang, Haoyu Wu
doaj +2 more sources
The benefits of in silico modeling to identify possible small-molecule drugs and their off-target interactions [PDF]
, 2018 Accepted for publication in a future issue of Future Medicinal Chemistry.The research into the use of small molecules as drugs continues to be a key driver in the development of molecular databases, computer-aided drug design software and collaborative ...
Blomberg N +6 more
core +2 more sources
Drug-target affinity prediction using graph neural network and contact maps. [PDF]
RSC Adv, 2020 Prediction of drug–target affinity by constructing both molecule and protein graphs.
Jiang M +6 more
europepmc +4 more sources
BMC Bioinformatics, 2021 Background The study of drug–target interactions (DTIs) affinity plays an important role in safety assessment and pharmacology. Currently, quantitative structure–activity relationship (QSAR) and molecular docking (MD) are most common methods in research ...
Xian-rui Wang +4 more
doaj +1 more source
Evolutionary conservation of influenza A PB2 sequences reveals potential target sites for small molecule inhibitors. [PDF]
, 2017 The influenza A basic polymerase protein 2 (PB2) functions as part of a heterotrimer to replicate the viral RNA genome. To investigate novel PB2 antiviral target sites, this work identified evolutionary conserved regions across the PB2 protein sequence ...
Kukol, A. +3 more
core +3 more sources
Target identification of small molecules: an overview of the current applications in drug discovery
BMC Biotechnology, 2023 Target identification is an essential part of the drug discovery and development process, and its efficacy plays a crucial role in the success of any given therapy.
Yasser Tabana +4 more
doaj +1 more source