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Prediction of Orthosteric and Allosteric Regulations on Cannabinoid Receptors Using Supervised Machine Learning Classifiers

Designing highly selective compounds to protein subtypes and developing allosteric modulators targeting them are critical considerations to both drug discovery and mechanism studies for cannabinoid receptors. It is challenging but in demand to have classifiers to identify active ligands from inactiv...

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Detalhes bibliográficos
Publicado no:Mol Pharm
Main Authors: Bian, Yuemin, Jing, Yankang, Wang, Lirong, Ma, Shifan, Jun, Jaden Jungho, Xie, Xiang-Qun
Formato: Artigo
Idioma:Inglês
Publicado em: 2019
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC6732211/
https://ncbi.nlm.nih.gov/pubmed/31013097
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1021/acs.molpharmaceut.9b00182
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