Results 51 to 60 of about 5,508,972 (143)

LEP-AD: language embedding of proteins and attention to drugs predicts drug-target interactions

Journal of Cheminformatics
Introduction Predicting drug–target interactions remains a significant challenge in drug development and lead optimization. Recent advances have leveraged machine learning algorithms to model drug–target interactions from molecular and sequence data ...
Reem Alsulami, Robert Lehmann, Anuj Daga, Sumeer A. Khan, Raik Grünberg, Ahmed Abogosh, David Gomez Cabrero, Stefan T. Arold, Robert Hoehndorf, Jesper Tegner, Narsis A. Kiani   +10 more
doaj   +1 more source

Target engagement of ginsenosides in mild cognitive impairment using mass spectrometry-based drug affinity responsive target stability

Journal of Ginseng Research, 2022
Background: Mild cognitive impairment (MCI) is a transitional condition between normality and dementia. Ginseng is known to have effects on attenuating cognitive deficits in neurogenerative diseases.
Zhu Zhu, Ruimei Li, Wei Qin, Hantao Zhang, Yao Cheng, Feiyan Chen, Cuihua Chen, Lin Chen, Yunan Zhao   +8 more
doaj   +1 more source

Fusing Sequence and Structural Knowledge by Heterogeneous Models to Accurately and Interpretively Predict Drug–Target Affinity

Molecules, 2023
Drug–target affinity (DTA) prediction is crucial for understanding molecular interactions and aiding drug discovery and development. While various computational methods have been proposed for DTA prediction, their predictive accuracy remains limited ...
Xin Zeng, Kailun Zhong, Bei Jiang, Yi Li
semanticscholar   +1 more source

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

IEEE/ACM Transactions on Computational Biology & Bioinformatics, 2020
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.
T. Nguyen, Thin Nguyen, T. Le, T. Tran
semanticscholar   +1 more source

The processes of reform in Victoria’s alcohol and other drug sector, 2011-2014 [PDF]

, 2014
This paper explores issues and concerns related to the 2014 alcohol and other drug sector recommissioning process in Victoria. Overview In mid-2014, the Victorian Alcohol and Drug Association approached the Drug Policy Modelling Program, at the ...
Drug Policy Modelling Program
core  

gene-fam-with-drug-target

, 2016
data for Fig.5: gene-fam-with-drug-target.txt column 1: HGNC gene family ID or name column 2: number of drug target genes (gene products) in the (HGNC) gene family column 3: number of genes in the (HGNC) gene family (possibly including pseudogenes ...
Wentian Li (28857), Pedro Miramontes (373939), Miramontes, Pedro, Oscar Fontanelli (3133830), Li, Wentian, Fontanelli, Oscar   +5 more
core   +1 more source

Antiviral Drug Target Identification and Ligand Discovery

, 2023
This chapter intends to provide a general overview of web-based resources available for antiviral drug discovery studies. First, we explain how the structure for a potential viral protein target can be obtained and then highlight some of the main ...
Patel, Hershna, Sengupta, Dipankar
core   +1 more source

Biochemical and structural characterization of mycobacterial aspartyl-tRNA synthetase AspS, a promising TB drug target [PDF]

, 2014
The human pathogen Mycobacterium tuberculosis is the causative agent of pulmonary tuberculosis (TB), a disease with high worldwide mortality rates. Current treatment programs are under significant threat from multi-drug and extensively-drug resistant ...
VijayaShankar Nataraj, Reynolds Robert C., Nicholas J Loman, Lloyd, AJ, Besra, Gurdyal S., Klaus Fütterer, Ballell, L, Reynolds, Robert C., Abrahams, Katherine A, Loman, Nicholas J., Hobrath Judith V., Gurcha Sudagar S., Alderwick, LJ, Abrahams, Katherine A., Gurcha, SS, Cox, Jonathan A G, Abrahams Katherine A., Hobrath, JV, Loman, Nicholas J, Carlos Alemparte, Lluis Ballell, Bhatt, Apoorva; id_orcid, Cox Jonathan A. G., Loman, NJ, Besra, GS, Reynolds, Robert C, Alemparte Carlos, Alderwick, Luke J, Gurcha, Sudagar S, Besra, Gurdyal S; id_orcid, Abrahams, KA, Besra Gurdyal S., Hobrath, Judith V, Barros, D, Robert C Reynolds, Loman Nicholas J., Bhatt, A, Ballell, Lluis, Nataraj, VijayaShankar, Lloyd, Adrian J., Apoorva Bhatt, Bhatt Apoorva, Nataraj, V, Alemparte, Carlos, Lloyd, Adrian J, Fütterer, K, Hobrath, Judith V., Veeraraghavan Usha, Cox, Jonathan A. G., Cox, JA, Barros David, Veeraraghavan, Usha, Bhatt, Apoorva, Adrian J Lloyd, Jonathan A G Cox, Usha, V, Gurdyal S Besra, David Barros, Lloyd Adrian J., Reynolds, RC, Alderwick, Luke J., Ballell Lluis, Usha Veeraraghavan, Fütterer Klaus, Barros, David, Nataraj, Vijaya-Shankar, Luke J Alderwick, Gurcha, Sudagar S., Alderwick Luke J., Judith V Hobrath, Sudagar S Gurcha, Usha, Veeraraghavan, Nataraj VijayaShankar, Alemparte, C, Fütterer, Klaus, Katherine A Abrahams   +75 more
core   +1 more source

SAG-DTA: Prediction of Drug–Target Affinity Using Self-Attention Graph Network

International Journal of Molecular Sciences, 2021
The prediction of drug–target affinity (DTA) is a crucial step for drug screening and discovery. In this study, a new graph-based prediction model named SAG-DTA (self-attention graph drug–target affinity) was implemented.
Shu-Gang Zhang, Mingjian Jiang, Shuang Wang, Xiaofeng Wang, Zhiqiang Wei, Zhen Li   +5 more
semanticscholar   +1 more source

A review of deep learning methods for ligand based drug virtual screening

Fundamental Research
Drug discovery is costly and time consuming, and modern drug discovery endeavors are progressively reliant on computational methodologies, aiming to mitigate temporal and financial expenditures associated with the process.
Hongjie Wu, Junkai Liu, Runhua Zhang, Yaoyao Lu, Guozeng Cui, Zhiming Cui, Yijie Ding   +6 more
doaj   +1 more source