Cargando…
Prediction of the Antioxidant Response Elements' Response of Compound by Deep Learning
The antioxidant response elements (AREs) play a significant role in occurrence of oxidative stress and may cause multitudinous toxicity effects in the pathogenesis of a variety of diseases. Determining if one compound can activate AREs is crucial for the assessment of potential risk of compound. Her...
Autores principales: | Bai, Fang, Hong, Ding, Lu, Yingying, Liu, Huanxiang, Xu, Cunlu, Yao, Xiaojun |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6554289/ https://www.ncbi.nlm.nih.gov/pubmed/31214568 http://dx.doi.org/10.3389/fchem.2019.00385 |
Ejemplares similares
-
Deciphering the Allosteric Effect of Antagonist Vismodegib on Smoothened Receptor Deactivation Using Metadynamics Simulation
por: An, Xiaoli, et al.
Publicado: (2019) -
Computational Insight Into the Small Molecule Intervening PD-L1 Dimerization and the Potential Structure-Activity Relationship
por: Shi, Danfeng, et al.
Publicado: (2019) -
Conformation Transition of Intracellular Part of Glucagon Receptor in Complex With Agonist Glucagon by Conventional and Accelerated Molecular Dynamics Simulations
por: Bai, Qifeng, et al.
Publicado: (2019) -
Computational Insights Into the Inhibition Mechanism of Proanthocyanidin B2 on Tau Hexapeptide (PHF6) Oligomer
por: Li, Qin, et al.
Publicado: (2021) -
Deep Learning for Deep Chemistry: Optimizing the Prediction of Chemical Patterns
por: Cova, Tânia F. G. G., et al.
Publicado: (2019)