Drug–Target Affinity Prediction Based on Cross-Modal Fusion of Text and Graph
Applied SciencesDrug–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
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SAG-DTA: Prediction of Drug-Target Affinity Using Self-Attention Graph Network. [PDF]
Int J Mol Sci, 2021 Zhang S +5 more
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Mitigating cold-start problems in drug-target affinity prediction with interaction knowledge transferring. [PDF]
Brief Bioinform, 2022 Nguyen TM, Nguyen T, Tran T.
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Drug-target affinity prediction using applicability domain based on data density [PDF]
, 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
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Impact of Protein Representations on Drug-Target Affinity Prediction
and target proteins can significantly hasten the drug discovery and development process. Utilizing artificial intelligence (AI) models to predict drug-target affinity (DTA) is an affordable and efficient strategy for sifting out undesirable molecules ...
Marijan, Matija, Tanasijević, Ivan
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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
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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
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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 ...
Hakime Öztürk +2 more
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Deep drug-target binding affinity prediction with multiple attention blocks [PDF]
Briefings in Bioinformatics, 2021 Abstract Drug-target interaction (DTI) prediction has drawn increasing interest due to its substantial position in the drug discovery process. Many studies have introduced computational models to treat DTI prediction as a regression task, which directly predict the binding affinity of drug-target pairs.
Yuni Zeng +4 more
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Multilevel Attention Models for Drug Target Binding Affinity Prediction [PDF]
Neural Processing Letters, 2021 Drug-Target Binding Affinity (DTBA) prediction is one class of Drug-Target Interaction problem (DTI), where the focus is to predict the binding strength of a drug-target pair. Several machine learning approaches have been developed for this purpose. However, almost all rely on the use of increasingly sophisticated inputs to improve the obtained results
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