Your browser doesn't support javascript.
loading
Design of novel quinoline derivatives as antibreast cancer using 3D-QSAR, molecular docking and pharmacokinetic investigation.
El Rhabori, Said; El Aissouq, Abdellah; Chtita, Samir; Khalil, Fouad.
Afiliação
  • El Rhabori S; Laboratory of Processes, Materials and Environment (LPME), Sidi Mohamed Ben Abdellah University, Faculty of Science and Technology, Fez.
  • El Aissouq A; Laboratory of Processes, Materials and Environment (LPME), Sidi Mohamed Ben Abdellah University, Faculty of Science and Technology, Fez.
  • Chtita S; Laboratory of Analytical and Molecular Chemistry, Faculty of Sciences Ben M'Sik, Hassan II University of Casablanca, Casablanca, Morocco.
  • Khalil F; Laboratory of Processes, Materials and Environment (LPME), Sidi Mohamed Ben Abdellah University, Faculty of Science and Technology, Fez.
Anticancer Drugs ; 33(9): 789-802, 2022 10 01.
Article em En | MEDLINE | ID: mdl-36136985
Breast cancer has been one of the most challenging women's cancers and leading cause of mortality for decades. There are several studies being conducted all the time to find a cure for breast cancer. Quinoline derivatives have shown their potential as antitumor agents in breast cancer therapy. In this work, three-dimensional quantitative structure-activity relationships (3D-QSAR) and molecular docking with aromatase enzyme (Protein Data Bank: 3S7S) studies were performed to suggest the current scenario of quinoline derivatives as antitumor agents and to refine the path of these derivatives to discover and develop new drugs against breast cancer. For developing the 3D-QSAR model, comparative molecular similarity indices analysis (CoMSIA) and comparative molecular field analysis (CoMFA) were included. To attain the high level of predictability, the best CoMSIA model was applied. External validation utilizing a test set has been used in order to validate the predictive capabilities of the built model. According to the findings, electrostatic, hydrophobic and hydrogen bond donor, and acceptor fields had a significant impact on antibreast cancer activity. Thus, we generated a variety of novel effective aromatase inhibitors based on prior findings and we predicted their inhibitory activity using the built model. In addition, absorption, distribution, metabolism, elimination and toxicity properties were employed to explore the effectiveness of new drug candidates.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Limite: Female / Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Limite: Female / Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article