Results 211 to 220 of about 5,903,465 (247)

An interpretable framework applying protein words to predict protein-small molecule complementary pairing rules. [PDF]

Chem Sci
Chen J, Zhong J, Tani TH, Su Z, Zhang X, Tian B.   +5 more
europepmc   +1 more source

In-silico study of active phytochemicals and molecular mechanism of Hydrocotyle javanica Thunb.in treating MDR enterobacterial infection. [PDF]

Bioresour Bioprocess
Paul D, Ghosh M, Mandal M.
europepmc   +1 more source

GraphDTA for predicting drug–target binding affinity

openaire   +1 more source

The value of target-site physiologically-based pharmacokinetics for high-affinity small molecules: a mechanistic foundation for precision dosing in oncology and hematology. [PDF]

Cancer Chemother Pharmacol
van der Gaag S, Oprea-Lager DE, Vis AN, Hendrikse H, Bartelink IH.   +4 more
europepmc   +1 more source

BoltzOmics: Predicting genetic variant effects on drug binding with Boltz-2. [PDF]

iScience
Ngo K, Carraway KL, Clancy CE, Amini H.
europepmc   +1 more source

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Multimodal contrastive representation learning for drug-target binding affinity prediction

Methods, 2023
In the biomedical field, the efficacy of most drugs is demonstrated by their interactions with targets, meanwhile, accurate prediction of the strength of drug-target binding is extremely important for drug development efforts. Traditional bioassay-based drug-target binding affinity (DTA) prediction methods cannot meet the needs of drug R&D in the era ...
Zheng Gao, Chunping Ouyang, Yongbin Liu   +2 more
exaly   +3 more sources

Drug-target continuous binding affinity prediction using multiple sources of information

Expert Systems With Applications, 2021
Abstract Drug-target binding affinity prediction has a significant role in the search for new drugs or novel targets for existing drugs. The vast majority of recent computational approaches, presented for the task of drug-target binding affinity prediction, make use of a single source to measure drug-drug or protein-protein similarities ...
Eghbal Mansoori, Mansoor Zolghadri Jahromi, Betsabeh Tanoori   +2 more
exaly   +3 more sources

Co-VAE: Drug-Target Binding Affinity Prediction by Co-Regularized Variational Autoencoders

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022
Identifying drug-target interactions has been a key step in drug discovery. Many computational methods have been proposed to directly determine whether drugs and targets can interact or not. Drug-target binding affinity is another type of data which could show the strength of the binding interaction between a drug and a target.
Xing-Ming Zhao, Limin Li, Tianjiao Li
exaly   +4 more sources

TransVAE-DTA: Transformer and variational autoencoder network for drug-target binding affinity prediction

Computer Methods and Programs in Biomedicine
Recent studies have emphasized the significance of computational in silico drug-target binding affinity (DTA) prediction in the field of drug discovery and drug repurposing. However, existing DTA prediction approaches suffer from two major deficiencies that impede their progress.
Changjian Zhou, Zhongzheng Li, Jia Song 0007, Wensheng Xiang   +3 more
exaly   +4 more sources

Prediction of drug–target binding affinity based on multi-scale feature fusion

Computers in Biology and Medicine
Accurate prediction of drug-target binding affinity (DTA) plays a pivotal role in drug discovery and repositioning. Although deep learning methods are widely used in DTA prediction, two significant challenges persist: (i) how to effectively represent the complex structural information of proteins and drugs; (ii) how to precisely model the mutual ...
Liu Zun, Jian-Yu Shi, Hui Yu
exaly   +4 more sources