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.

Afiliación

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 en En | MEDLINE | ID: mdl-34500703

Asunto(s)

Receptores sigma/química; Receptores sigma/metabolismo; Algoritmos; Humanos; Relación Estructura-Actividad Cuantitativa

Palabras clave

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

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Receptores sigma Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Molecules Asunto de la revista: BIOLOGIA Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Suiza

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