Results 11 to 20 of about 401,503 (258)

Prediction of Drug-Target Affinity Using Attention Neural Network. [PDF]

Int J Mol Sci
Studying drug-target interactions (DTIs) is the foundational and crucial phase in drug discovery. Biochemical experiments, while being the most reliable method for determining drug-target affinity (DTA), are time-consuming and costly, making it challenging to meet the current demands for swift and efficient drug development. Consequently, computational
Tang X, Lei X, Zhang Y.
europepmc   +4 more sources

EMPDTA: An End-to-End Multimodal Representation Learning Framework with Pocket Online Detection for Drug–Target Affinity Prediction [PDF]

Molecules
Accurately predicting drug–target interactions is a critical yet challenging task in drug discovery. Traditionally, pocket detection and drug–target affinity prediction have been treated as separate aspects of drug–target interaction, with few methods ...
Dingkai Huang, Jiang Xie
doaj   +3 more sources

Drug-target binding affinity prediction based on power graph and word2vec

BMC Medical Genomics
Background Drug and protein targets affect the physiological functions and metabolic effects of the body through bonding reactions, and accurate prediction of drug-protein target interactions is crucial for drug development.
Jing Hu, Shuo Hu, Minghao Xia, Kangxing Zheng, Xiaolong Zhang   +4 more
doaj   +4 more sources

FingerDTA: A Fingerprint-Embedding Framework for Drug-Target Binding Affinity Prediction [PDF]

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, Juan Liu, Jian Zhang, Zhihui Yang, Feng Yang, Xiaolei Zhang   +5 more
doaj   +3 more sources

MTAF–DTA: multi-type attention fusion network for drug–target affinity prediction [PDF]

BMC Bioinformatics
Background The development of drug–target binding affinity (DTA) prediction tasks significantly drives the drug discovery process forward. Leveraging the rapid advancement of artificial intelligence, DTA prediction tasks have undergone a transformative ...
Jinghong Sun, Han Wang, Jia Mi, Jing Wan, Jingyang Gao   +4 more
doaj   +3 more sources

SAG-DTA: Prediction of Drug–Target Affinity Using Self-Attention Graph Network [PDF]

International Journal of Molecular Sciences, 2021
The prediction of drug–target affinity (DTA) is a crucial step for drug screening and discovery. In this study, a new graph-based prediction model named SAG-DTA (self-attention graph drug–target affinity) was implemented.
Shugang Zhang, Mingjian Jiang, Zhiqiang Wei   +2 more
exaly   +3 more sources

Mitigating cold-start problems in drug-target affinity prediction with interaction knowledge transferring [PDF]

Briefings in Bioinformatics, 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.
Tri Minh Nguyen, Thin Nguyen, Truyen Tran   +2 more
exaly   +3 more sources

DeepMHADTA: Prediction of Drug-Target Binding Affinity Using Multi-Head Self-Attention and Convolutional Neural Network

Current Issues in Molecular Biology, 2022
Drug-target interactions provide insight into the drug-side effects and drug repositioning. However, wet-lab biochemical experiments are time-consuming and labor-intensive, and are insufficient to meet the pressing demand for drug research and ...
Lei Deng, Yunyun Zeng, Hui Liu, Zixuan Liu, Xuejun Liu   +4 more
doaj   +2 more sources

BiComp-DTA: Drug-target binding affinity prediction through complementary biological-related and compression-based featurization approach.

PLoS Computational Biology, 2023
Drug-target binding affinity prediction plays a key role in the early stage of drug discovery. Numerous experimental and data-driven approaches have been developed for predicting drug-target binding affinity.
Mahmood Kalemati, Mojtaba Zamani Emani, Somayyeh Koohi   +2 more
doaj   +2 more sources

Sequence-based drug-target affinity prediction using weighted graph neural networks [PDF]

BMC Genomics, 2022
Background Affinity prediction between molecule and protein is an important step of virtual screening, which is usually called drug-target affinity (DTA) prediction. Its accuracy directly influences the progress of drug development.
Mingjian Jiang, Shuang Wang, Shugang Zhang, Wei Zhou, Yuanyuan Zhang, Zhen Li   +5 more
doaj   +2 more sources