Results 61 to 70 of about 333,304 (136)

SMFF-DTA: using a sequential multi-feature fusion method with multiple attention mechanisms to predict drug-target binding affinity

BMC Biology
Background Drug-target binding affinity (DTA) prediction can accelerate the drug screening process, and deep learning techniques have been used in all facets of drug research.
Xun Wang, Zhijun Xia, Runqiu Feng, Tongyu Han, Hanyu Wang, Wenqian Yu, Xingguang Wang   +6 more
doaj   +1 more source

GS-DTA: integrating graph and sequence models for predicting drug-target binding affinity

BMC Genomics
Background Drug-target binding affinity (DTA) prediction is vital in drug discovery and repositioning, more and more researchers are beginning to focus on this. Many effective methods have been proposed.
Junwei Luo, Ziguang Zhu, Zhenhan Xu, Chuanle Xiao, Jingjing Wei, Jiquan Shen   +5 more
doaj   +1 more source

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

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

Fusing Sequence and Structural Knowledge by Heterogeneous Models to Accurately and Interpretively Predict Drug-Target Affinity. [PDF]

Molecules, 2023
Zeng X, Zhong KY, Jiang B, Li Y.
europepmc   +1 more source

Enabling target-aware molecule generation to follow multi objectives with Pareto MCTS

Communications Biology
Target-aware drug discovery has greatly accelerated the drug discovery process to design small-molecule ligands with high binding affinity to disease-related protein targets.
Yaodong Yang, Guangyong Chen, Jinpeng Li, Junyou Li, Odin Zhang, Xujun Zhang, Lanqing Li, Jianye Hao, Ercheng Wang, Pheng-Ann Heng   +9 more
doaj   +1 more source

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

Brief Bioinform, 2022
Nguyen TM, Nguyen T, Tran T.
europepmc   +1 more source

KANPM-DTA: improving drug-target affinity prediction with Kolmogorov-Arnold networks and pretrained models. [PDF]

Brief Bioinform
Rakib MDYK, Alamin MH, Li J, Mamun SS, Gobena KA, Ren S.   +5 more
europepmc   +1 more source

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

Int J Mol Sci, 2021
Zhang S, Jiang M, Wang S, Wang X, Wei Z, Li Z.   +5 more
europepmc   +1 more source

Impact of Protein Representations on Drug-Target Affinity Prediction

and target proteins can significantly hasten the drug discovery and development process. Utilizing artificial intelligence (AI) models to predict drug-target affinity (DTA) is an affordable and efficient strategy for sifting out undesirable molecules and identifying promising drug candidates.
Marijan, Matija, Tanasijević, Ivan
openaire   +1 more source

3DProtDTA: a deep learning model for drug-target affinity prediction based on residue-level protein graphs. [PDF]

RSC Adv, 2023
Voitsitskyi T, Stratiichuk R, Koleiev I, Popryho L, Ostrovsky Z, Henitsoi P, Khropachov I, Vozniak V, Zhytar R, Nechepurenko D, Yesylevskyy S, Nafiiev A, Starosyla S.   +12 more
europepmc   +1 more source