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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 and identifying promising drug candidates.
Marijan, Matija, Tanasijević, Ivan
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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, Arzucan Özgür, Elif Özkirimli Ölmez   +2 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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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, Xiangru Chen, Yujie Luo, Xuedong Li, Dezhong Peng   +4 more
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Drug-Target Binding Affinity Prediction Using Transformers [PDF]

, 2021
Abstract Drug discovery is generally difficult, expensive, and low success rate. One of the essential steps in the early stages of drug discovery and drug repurposing is identifying drug-target interactions. Binding affinity indicates the strength of drug-target pair interactions.
Mahsa Saadat, Armin Behjati, Fatemeh Zare-Mirakabad, Sajjad Gharaghani   +3 more
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Drug-target affinity prediction using applicability domain based on data density

, 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

Hierarchical graph representation learning for the prediction of drug-target binding affinity

Information Sciences, 2022
The identification of drug-target binding affinity (DTA) has attracted increasing attention in the drug discovery process due to the more specific interpretation than binary interaction prediction. Recently, numerous deep learning-based computational methods have been proposed to predict the binding affinities between drugs and targets benefiting from ...
Zhaoyang Chu, Feng Huang 0004, Haitao Fu, Yuan Quan, Xionghui Zhou, Shichao Liu 0002, Wen Zhang 0008   +6 more
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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, Elif Özkirimli Ölmez, Arzucan Özgür   +2 more
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GraphDTA: Predicting drug–target binding affinity with graph neural networks [PDF]

Bioinformatics, 2019
Abstract The 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.
Thin Nguyen, Hang Le 0003, Thomas P. Quinn, Tri Nguyen, Thuc Duy Le, Svetha Venkatesh   +5 more
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Quantitative prediction model for affinity of drug–target interactions based on molecular vibrations and overall system of ligand-receptor

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, Ting-ting Cao, Cong Min Jia, Xue-mei Tian, Yun Wang   +4 more
doaj   +1 more source