Results 31 to 40 of about 160,727 (166)

DeepDTAGen: a multitask deep learning framework for drug-target affinity prediction and target-aware drugs generation [PDF]

Nature Communications
Identifying novel drugs that can interact with target proteins is a highly challenging, time-consuming, and costly task in drug discovery and development. Numerous machine learning-based models have recently been utilized to accelerate the drug discovery
Pir Masoom Shah, Huimin Zhu, Zhangli Lu, Kaili Wang, Jing Tang, Min Li   +5 more
doaj   +2 more sources

Drug-target binding affinity prediction based on power graph and word2vec

BMC Medical Genomics
Background Drug and protein targets affect the physiological functions and metabolic effects of the body through bonding reactions, and accurate prediction of drug-protein target interactions is crucial for drug development.
Jing Hu, Shuo Hu, Minghao Xia, Kangxing Zheng, Xiaolong Zhang   +4 more
doaj   +3 more sources

MEGDTA: multi-modal drug-target affinity prediction based on protein three-dimensional structure and ensemble graph neural network [PDF]

BMC Genomics
Background Drug development is a time-consuming and costly endeavor, and utilizing computer-aided methods to predict drug-target affinity (DTA) can significantly accelerate this process.
Zhanwei Hou, Yijun Li, Haixia Zhai, Junwei Luo, Yulian Ding, Yi Pan   +5 more
doaj   +2 more sources

DTBind: A Mechanism-Driven Deep Learning Framework for Accurate Prediction of Drug–Target Molecular Recognition [PDF]

Research
Accurate prediction of drug–target molecular recognition is essential for early-stage drug discovery, spanning binding occurrence, binding site localization, and binding affinity estimation.
Qiuyu Li, Zeyu Xu, Yanhao Zhu, Wanyun Zhou, Mingming Guan, Shiqing Zhao, Mengyuan Liu, Bin Liu, Juntao Liu   +8 more
doaj   +2 more sources

Recent trends in machine learning and deep learning-based prediction of G-protein coupled receptor-ligand binding affinities [PDF]

Frontiers in Bioinformatics
Accurately predicting protein-ligand binding affinity is key in drug discovery. Machine Learning and Deep Learning methods used in the drug discovery process have advanced the prediction of drug–target binding affinities, particularly for G protein ...
Joshua Stephenson, Konda Reddy Karnati
doaj   +2 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   +3 more sources

Deep drug-target binding affinity prediction with multiple attention blocks [PDF]

Briefings in Bioinformatics, 2021
Abstract Drug-target interaction (DTI) prediction has drawn increasing interest due to its substantial position in the drug discovery process. Many studies have introduced computational models to treat DTI prediction as a regression task, which directly predict the binding affinity of drug-target pairs.
Yuni, Zeng, Xiangru, Chen, Yujie, Luo, Xuedong, Li, Dezhong, Peng   +4 more
openaire   +2 more sources

Drug-Target Binding Affinity Prediction Using Transformers [PDF]

, 2021
AbstractDrug discovery is generally difficult, expensive, and low success rate. One of the essential steps in the early stages of drug discovery and drug repurposing is identifying drug-target interactions. Binding affinity indicates the strength of drug-target pair interactions.
Mahsa Saadat, Armin Behjati, Fatemeh Zare-Mirakabad, Sajjad Gharaghani   +3 more
openaire   +1 more source

A Multibranch Neural Network for Drug-Target Affinity Prediction Using Similarity Information [PDF]

ACS Omega
Jing Chen, Xiaolin Yang, Haoyu Wu
doaj   +2 more sources

GraphDTA: Predicting drug–target binding affinity with graph neural networks [PDF]

Bioinformatics, 2019
AbstractThe development of new drugs is costly, time consuming, and often accompanied with safety issues. Drug repurposing can avoid the expensive and lengthy process of drug development by finding new uses for already approved drugs. In order to repurpose drugs effectively, it is useful to know which proteins are targeted by which drugs. Computational
Thin Nguyen, Hang Le, Thomas P Quinn, Tri Nguyen, Thuc Duy Le, Svetha Venkatesh   +5 more
openaire   +4 more sources