Results 21 to 30 of about 401,503 (258)

A deep learning method for drug-target affinity prediction based on sequence interaction information mining [PDF]

PeerJ, 2023
Background A critical aspect of in silico drug discovery involves the prediction of drug-target affinity (DTA). Conducting wet lab experiments to determine affinity is both expensive and time-consuming, making it necessary to find alternative approaches.
Mingjian Jiang, Yunchang Shao, Yuanyuan Zhang, Wei Zhou, Shunpeng Pang   +4 more
doaj   +3 more sources

DCI-SiteDTA: drug-target affinity prediction based on binding sites detection and site-aware dual cross-interaction block [PDF]

BMC Bioinformatics
Background Predicting the binding affinity between drugs and proteins is crucial for accelerating drug discovery. However, traditional research methods typically treat binding site detection and affinity prediction as two separate tasks, lacking ...
Jinyang Zhang, Xingyang Li, Bo Wei, Yuni Zeng   +3 more
doaj   +2 more sources

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   +2 more sources

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
doaj   +2 more sources

GraphATT-DTA: Attention-Based Novel Representation of Interaction to Predict Drug-Target Binding Affinity [PDF]

Biomedicines, 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.
Haelee Bae, Hojung Nam
doaj   +2 more sources

Structure-free drug–target affinity prediction using protein and molecule language models [PDF]

Journal of Cheminformatics
Accurate prediction of drug-target affinity (DTA) is crucial for advancing drug discovery and optimizing experimental processes. Traditional DTA models often rely on handcrafted features or structural data, which can limit their generalizability and ...
Amir Hallaji Bidgoli, Morteza Mahdavi, Hamed Malek   +2 more
doaj   +2 more sources

ImageDTA: A Simple Model for Drug–Target Binding Affinity Prediction

ACS Omega
Predicting 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

SubMDTA: drug target affinity prediction based on substructure extraction and multi-scale features [PDF]

BMC Bioinformatics, 2023
Background Drug–target affinity (DTA) prediction is a critical step in the field of drug discovery. In recent years, deep learning-based methods have emerged for DTA prediction.
Shourun Pan, Leiming Xia, Lei Xu, Zhen Li   +3 more
doaj   +2 more sources

A meta learning and task adaptive approach for drug target affinity prediction [PDF]

Nature Communications
Accurate and robust prediction of drug-target affinity (DTA) plays a critical role in drug discovery. While deep learning has advanced DTA prediction, existing methods struggle with limited training data and poor generalization. In this study, we propose
Mengxuan Wan, Yanpeng Zhao, Yixin Zhang, Huiyan Xu, Duoyun Yi, Peng Zan, Song He, Xiaochen Bo   +7 more
doaj   +2 more sources

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
doaj   +3 more sources