Results 11 to 20 of about 600,341 (272)

GANsDTA: Predicting Drug-Target Binding Affinity Using GANs

Frontiers in Genetics, 2020
The computational prediction of interactions between drugs and targets is a standing challenge in drug discovery. State-of-the-art methods for drug-target interaction prediction are primarily based on supervised machine learning with known label ...
Lingling Zhao, Junjie Wang, Long Pang, Yang Liu, Jun Zhang   +4 more
doaj   +3 more sources

Explainable deep drug–target representations for binding affinity prediction

BMC Bioinformatics, 2022
Background Several computational advances have been achieved in the drug discovery field, promoting the identification of novel drug–target interactions and new leads. However, most of these methodologies have been overlooking the importance of providing
Nelson R. C. Monteiro, Carlos J. V. Simões, Henrique V. Ávila, Maryam Abbasi, José L. Oliveira, Joel P. Arrais   +5 more
doaj   +3 more sources

GEFA: Early Fusion Approach in Drug-Target Affinity Prediction [PDF]

IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2022
Predicting the interaction between a compound and a target is crucial for rapid drug repurposing. Deep learning has been successfully applied in drug-target affinity (DTA) problem. However, previous deep learning-based methods ignore modeling the direct interactions between drug and protein residues.
Tri Minh Nguyen, Thin Nguyen, Thao Minh Le, Truyen Tran   +3 more
openaire   +5 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   +2 more sources

DrugForm-DTA: Towards real-world drug-target binding affinity model

Computational and Structural Biotechnology Journal
Drug-target affinity (DTA) prediction is a fundamental challenge in drug discovery. Computational methods for predicting DTA can greatly assist drug design by narrowing the search space and reducing the number of protein-ligand complexes with low ...
Ivan Khokhlov, Anna Tashchilova, Nikolai Bugaev-Makarovskiy, Olga Glushkova, Vladimir Yudin, Anton Keskinov, Sergey Yudin, Dmitry Svetlichnyy, Veronika Skvortsova   +8 more
doaj   +3 more sources

GEFormerDTA: drug target affinity prediction based on transformer graph for early fusion [PDF]

Scientific Reports
Predicting the interaction affinity between drugs and target proteins is crucial for rapid and accurate drug discovery and repositioning. Therefore, more accurate prediction of DTA has become a key area of research in the field of drug discovery and drug
Youzhi Liu, Linlin Xing, Longbo Zhang, Hongzhen Cai, Maozu Guo   +4 more
doaj   +2 more sources

GramSeq-DTA: A Grammar-Based Drug–Target Affinity Prediction Approach Fusing Gene Expression Information [PDF]

Biomolecules
Drug–target affinity (DTA) prediction is a critical aspect of drug discovery. The meaningful representation of drugs and targets is crucial for accurate prediction. Using 1D string-based representations for drugs and targets is a common approach that has
Kusal Debnath, Pratip Rana, Preetam Ghosh   +2 more
doaj   +2 more sources

A geometric graph-based deep learning model for drug-target affinity prediction [PDF]

BMC Bioinformatics
In structure-based drug design, accurately estimating the binding affinity between a candidate ligand and its protein receptor is a central challenge.
Md Masud Rana, Farjana Tasnim Mukta, Duc D. Nguyen   +2 more
doaj   +2 more sources

MDNN-DTA: a multimodal deep neural network for drug-target affinity prediction [PDF]

Frontiers in Genetics
Determining drug-target affinity (DTA) is a pivotal step in drug discovery, where in silico methods can significantly improve efficiency and reduce costs.
Xu Gao, Xu Gao, Mengfan Yan, Mengfan Yan, Chengwei Zhang, Chengwei Zhang, Gang Wu, Gang Wu, Jiandong Shang, Jiandong Shang, Congxiang Zhang, Congxiang Zhang, Kecheng Yang, Kecheng Yang   +13 more
doaj   +2 more sources

A comprehensive review of the recent advances on predicting drug-target affinity based on deep learning [PDF]

Frontiers in Pharmacology
Accurate calculation of drug-target affinity (DTA) is crucial for various applications in the pharmaceutical industry, including drug screening, design, and repurposing.
Xin Zeng, Shu-Juan Li, Shuang-Qing Lv, Meng-Liang Wen, Yi Li   +4 more
doaj   +2 more sources