QSAR-Based Computational Approaches to Accelerate the Discovery of Sigma-2 Receptor (S2R) Ligands as Therapeutic Drugs.

Yu, Yangxi; Dong, Hiep; Peng, Youyi; Welsh, William J

Yu, Yangxi; Dong, Hiep; Peng, Youyi; Welsh, William J.

Afiliação

Yu Y; Department of Pharmacology, Robert Wood Johnson Medical School, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA.
Dong H; Department of Medicinal Chemistry, Ernest Mario School of Pharmacy, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA.
Peng Y; Biomedical Informatics Shared Resource, Rutgers Cancer Institute of New Jersey, Rutgers, The State University of New Jersey, New Brunswick, NJ 08903, USA.
Welsh WJ; Department of Pharmacology, Robert Wood Johnson Medical School, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA.

Molecules ; 26(17)2021 Aug 30.

Article em En | MEDLINE | ID: mdl-34500703

Assuntos

Receptores sigma/química; Receptores sigma/metabolismo; Algoritmos; Humanos; Relação Quantitativa Estrutura-Atividade

Palavras-chave

QSAR; Sigma-2 receptor (S2R); drug discovery; optimization algorithms; pharmacophore model

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Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Receptores sigma Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Molecules Assunto da revista: BIOLOGIA Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos

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