Results 251 to 260 of about 141,734 (283)

Rethinking the generalization of drug target affinity prediction algorithms via similarity aware evaluation

International Conference on Learning Representations
Drug-target binding affinity prediction is a fundamental task for drug discovery. It has been extensively explored in literature and promising results are reported.
Chenbin Zhang, Zhiqiang Hu, Chuchu Jiang, Wen Chen, Jie Xu, Shaoting Zhang   +5 more
semanticscholar   +1 more source

Drug-target interaction/affinity prediction: Deep learning models and advances review

Computers in Biology and Medicine
64 pages, 7 figures, 10 ...
Zahed Rahmati, Mohammad Akbari, Ali Vefghi   +2 more
exaly   +4 more sources

Prediction of drug-target binding affinity based on deep learning models

Computers in Biology and Medicine
The prediction of drug-target binding affinity (DTA) plays an important role in drug discovery. Computerized virtual screening techniques have been used for DTA prediction, greatly reducing the time and economic costs of drug discovery. However, these techniques have not succeeded in reversing the low success rate of new drug development.
Yuanyuan Chen
exaly   +3 more sources

AttentionDTA: prediction of drug–target binding affinity using attention model

2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2019
In bioinformatics, machine learning-based prediction of drug-target interaction (DTI) plays an important role in virtual screening of drug discovery. DTI prediction, which have been treated as a binary classification problem, depends on the concentration of two molecules, the interaction between two molecules, and other factors.
Qichang Zhao, Fen Xiao, Mengyun Yang, Yaohang Li, Jianxin Wang 0001   +4 more
openaire   +1 more source

MFF-DTA: Multi-scale Feature Fusion for Drug-Target Affinity Prediction.

Methods
Accurately predicting drug-target affinity is crucial in expediting the discovery and development of new drugs, which is a complex and risky process. Identifying these interactions not only aids in screening potential compounds but also guides further ...
Xiwei Tang, Wanjun Ma, Mengyun Yang, Wenjun Li   +3 more
semanticscholar   +1 more source

Contrastive Meta-Learning for Drug-Target Binding Affinity Prediction

2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2022
Mei Li, Sihan Xu, Xiangrui Cai, Zhong Zhang 0001, Hua Ji   +4 more
openaire   +1 more source

MHAN-DTA: A Multiscale Hybrid Attention Network for Drug-Target Affinity Prediction

IEEE journal of biomedical and health informatics
Drug-target affinity prediction is a key challenge in the drug discovery process. Recent advances have demonstrated the great potential of deep learning in predicting affinities; however, existing approaches learn the representation of drug-target ...
Jiaren Li, Xiangpeng Bi, Wenjian Ma, Huasen Jiang, Shanglong Liu, Yun Lu, Zhiqiang Wei, Shugang Zhang   +7 more
semanticscholar   +1 more source

Drug-target Affinity Prediction by Molecule Secondary Structure Representation Network

Current Medicinal Chemistry
Introduction: Identification of drug-target interactions (DTI) is a crucial step in drug development with high specificity and low toxicity. To accelerate the process, computer-aided DTI prediction algorithms have been used to screen compounds or targets rapidly. Furthermore, DTI prediction can be used to identify potential targets for existing drugs,
Yuewei, Tang, Yunhai, Li, Pengpai, Li, Zhi-Ping, Liu   +3 more
openaire   +2 more sources

MMFA-DTA: Multimodal Feature Attention Fusion Network for Drug-Target Affinity Prediction for Drug Repurposing Against SARS-CoV-2.

Journal of Chemical Theory and Computation
The continuous emergence of novel infectious diseases poses a significant threat to global public health security, necessitating the development of small-molecule inhibitors that directly target pathogens. The RNA-dependent RNA polymerase (RdRp) and main
Guanxing Chen, Haohuai He, Qiujie Lv, Lu Zhao, C. Chen   +4 more
semanticscholar   +1 more source

Classification prediction of drug target binding affinity based on the MolrProtTrans model

Analytical Biochemistry
Predicting drug-target interactions is essential for virtual drug screening. While many models predict the binding affinity between small molecules and proteins, they often overemphasize molecular features while overlooking important protein characteristics, leading to biased predictions.
Yicun Lin, Yuanfeng Li, Wei Sun, Jian Wang   +3 more
openaire   +2 more sources