Results 21 to 30 of about 501,527 (238)

DCGAN-DTA: Predicting drug-target binding affinity with deep convolutional generative adversarial networks [PDF]

BMC Genomics
Background In recent years, there has been a growing interest in utilizing computational approaches to predict drug-target binding affinity, aiming to expedite the early drug discovery process.
Mahmood Kalemati, Mojtaba Zamani Emani, Somayyeh Koohi   +2 more
doaj   +3 more sources

Deep Drug–Target Binding Affinity Prediction Base on Multiple Feature Extraction and Fusion [PDF]

ACS Omega
Accurate drug–target binding affinity (DTA) prediction is crucial in drug discovery. Recently, deep learning methods for DTA prediction have made significant progress.
Zepeng Li, Yuni Zeng, Mingfeng Jiang, Bo Wei   +3 more
doaj   +3 more sources

MSGNN-DTA: Multi-Scale Topological Feature Fusion Based on Graph Neural Networks for Drug-Target Binding Affinity Prediction. [PDF]

Int J Mol Sci, 2023
The accurate prediction of drug–target binding affinity (DTA) is an essential step in drug discovery and drug repositioning. Although deep learning methods have been widely adopted for DTA prediction, the complexity of extracting drug and target protein ...
Wang S, Song X, Zhang Y, Zhang K, Liu Y, Ren C, Pang S.   +6 more
europepmc   +3 more sources

Prediction of drug–target binding affinity using similarity-based convolutional neural network [PDF]

Scientific Reports, 2021
Identifying novel drug–target interactions (DTIs) plays an important role in drug discovery. Most of the computational methods developed for predicting DTIs use binary classification, whose goal is to determine whether or not a drug–target (DT) pair ...
Jooyong Shim, Zhen-Yu Hong, Insuk Sohn, Changha Hwang   +3 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

PRGNet: a Parallel Residual Graph Network for enhanced drug-target binding affinity prediction [PDF]

BMC Genomics
Predicting drug-target binding affinity (DTA) remains a cornerstone of structure-based drug discovery but is still constrained by fundamental methodological trade-offs.
Jing Liu, Aamir Mehmood, Haiqi Liu, Yishu Liu, Dongqing Wei, Daixi Li   +5 more
doaj   +2 more sources

Comparison Study of Computational Prediction Tools for Drug-Target Binding Affinities [PDF]

Frontiers in Chemistry, 2019
The drug development is generally arduous, costly, and success rates are low. Thus, the identification of drug-target interactions (DTIs) has become a crucial step in early stages of drug discovery.
Maha Thafar, Maha Thafar, Arwa Bin Raies, Somayah Albaradei, Somayah Albaradei, Magbubah Essack, Vladimir B. Bajic   +6 more
doaj   +4 more sources

MGF-DTA: A Multi-Granularity Fusion Model for Drug-Target Binding Affinity Prediction. [PDF]

Int J Mol Sci
Drug–target affinity (DTA) prediction is one of the core components of drug discovery. Despite considerable advances in previous research, DTA tasks still face several limitations with insufficient multi-modal information of drugs, the inherent sequence length limitation of protein language models, and single attention mechanisms that fail to capture ...
Ni Z, Wei B, Zeng Y.
europepmc   +4 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

MFR-DTA: a multi-functional and robust model for predicting drug-target binding affinity and region. [PDF]

Bioinformatics, 2023
Motivation Recently, deep learning has become the mainstream methodology for drug–target binding affinity prediction. However, two deficiencies of the existing methods restrict their practical applications.
Hua Y, Song X, Feng Z, Wu X.
europepmc   +2 more sources