QSAR modeling and molecular docking studies of 2-oxo-1, 2-dihydroquinoline-4- carboxylic acid derivatives as p-glycoprotein inhibitors for combating cancer multidrug resistance.

Lahyaoui, M; Diane, A; El-Idrissi, H; Saffaj, T; Rodi, Y Kandri; Ihssane, B

Lahyaoui, M; Diane, A; El-Idrissi, H; Saffaj, T; Rodi, Y Kandri; Ihssane, B.

Afiliação

Lahyaoui M; Laboratory of Applied Organic Chemistry, Faculty of Science and Technology, Sidi Mohamed Ben Abdellah University, USMBA, Po. Box 2626 Fez, Morocco.
Diane A; Laboratory of Applied Organic Chemistry, Faculty of Science and Technology, Sidi Mohamed Ben Abdellah University, USMBA, Po. Box 2626 Fez, Morocco.
El-Idrissi H; Laboratory of Applied Organic Chemistry, Faculty of Science and Technology, Sidi Mohamed Ben Abdellah University, USMBA, Po. Box 2626 Fez, Morocco.
Saffaj T; Laboratory of Applied Organic Chemistry, Faculty of Science and Technology, Sidi Mohamed Ben Abdellah University, USMBA, Po. Box 2626 Fez, Morocco.
Rodi YK; Laboratory of Applied Organic Chemistry, Faculty of Science and Technology, Sidi Mohamed Ben Abdellah University, USMBA, Po. Box 2626 Fez, Morocco.
Ihssane B; Laboratory of Applied Organic Chemistry, Faculty of Science and Technology, Sidi Mohamed Ben Abdellah University, USMBA, Po. Box 2626 Fez, Morocco.

Heliyon ; 9(1): e13020, 2023 Jan.

Article em En | MEDLINE | ID: mdl-36747956

Palavras-chave

Deep learning; Machine learning; Molecular docking; PCA; QSAR; Quinoline

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Heliyon Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Marrocos País de publicação: Reino Unido

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