Results 41 to 50 of about 333,304 (136)

Prediction of drug–target binding affinity using similarity-based convolutional neural network

Scientific Reports, 2021
Identifying novel drug–target interactions (DTIs) plays an important role in drug discovery. Most of the computational methods developed for predicting DTIs use binary classification, whose goal is to determine whether or not a drug–target (DT) pair ...
Jooyong Shim, Zhen-Yu Hong, Insuk Sohn, Changha Hwang   +3 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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Enhanced information cross-attention fusion for drug–target binding affinity prediction [PDF]

PeerJ Computer Science
Background The rapid development of artificial intelligence has permeated many fields, with its application in drug discovery becoming increasingly mature.
Ailu Fei, Yihan Wang, Tiantian Ruan, Yekang Zhang, Min Yao, Li Wang   +5 more
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Affinity2Vec: drug-target binding affinity prediction through representation learning, graph mining, and machine learning

Scientific 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, Mona Alshahrani, Somayah Albaradei, Takashi Gojobori, Magbubah Essack, Xin Gao   +5 more
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Discovering the Biological Target of 5-epi-Sinuleptolide Using a Combination of Proteomic Approaches

Marine Drugs, 2017
Sinuleptolide and its congeners are diterpenes with a norcembranoid skeleton isolated from the soft coral genus Sinularia. These marine metabolites are endowed with relevant biological activities, mainly associated with cancer development.
Elva Morretta, Roberta Esposito, Carmen Festa, Raffaele Riccio, Agostino Casapullo, Maria Chiara Monti   +5 more
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ELECTRA-DTA: a new compound-protein binding affinity prediction model based on the contextualized sequence encoding

Journal of Cheminformatics, 2022
Motivation Drug-target binding affinity (DTA) reflects the strength of the drug-target interaction; therefore, predicting the DTA can considerably benefit drug discovery by narrowing the search space and pruning drug-target (DT) pairs with low binding ...
Junjie Wang, NaiFeng Wen, Chunyu Wang, Lingling Zhao, Liang Cheng   +4 more
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WideDTA: prediction of drug-target binding affinity

, 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.
Öztürk, Hakime, Ozkirimli, Elif, Özgür, Arzucan   +2 more
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Target engagement of ginsenosides in mild cognitive impairment using mass spectrometry-based drug affinity responsive target stability

Journal of Ginseng Research, 2022
Background: Mild cognitive impairment (MCI) is a transitional condition between normality and dementia. Ginseng is known to have effects on attenuating cognitive deficits in neurogenerative diseases.
Zhu Zhu, Ruimei Li, Wei Qin, Hantao Zhang, Yao Cheng, Feiyan Chen, Cuihua Chen, Lin Chen, Yunan Zhao   +8 more
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Predicting drug–target binding affinity with cross-scale graph contrastive learning

Briefings in Bioinformatics, 2023
Abstract Identifying the binding affinity between a drug and its target is essential in drug discovery and repurposing. Numerous computational approaches have been proposed for understanding these interactions. However, most existing methods only utilize either the molecular structure information of drugs and targets or the interaction ...
Wang, Jingru, Xiao, Yihang, Shang, Xuequn, Peng, Jiajie   +3 more
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Drug-Online: an online platform for drug-target interaction, affinity, and binding sites identification using deep learning

BMC 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, Guang-Peng Su, Shu-Juan Li, Shuang-Qing Lv, Meng-Liang Wen, Yi Li   +5 more
doaj   +1 more source