LIVIVO - The Search Portal for Life Sciences

zur deutschen Oberfläche wechseln
Advanced search

Search results

Result 1 - 2 of total 2

Search options

  1. Article ; Online: 3D-QSAR Study of the Chalcone Derivatives as Anticancer Agents

    Larbi ElMchichi / Assia Belhassan / Tahar Lakhlifi / Mohammed Bouachrine

    Journal of Chemistry, Vol

    2020  Volume 2020

    Abstract: For their biological properties and particularly for their anticancer activities, chalcones are widely studied. In this work, we have submitted diverse sets of chalcone derivatives to the 3D-QSAR (3-dimensional quantitative structural-activity ... ...

    Abstract For their biological properties and particularly for their anticancer activities, chalcones are widely studied. In this work, we have submitted diverse sets of chalcone derivatives to the 3D-QSAR (3-dimensional quantitative structural-activity relationship) to study their anticancer activities against HTC116 (human colon cancer), relying on the 3-dimensional descriptors: steric and electrostatic descriptors for the CoMFA (comparative molecular field analysis) method and steric, electrostatic, hydrophobic, H-bond donor, and H-bond acceptor descriptors for the CoMSIA method. CoMFA as well as the CoMSIA model have encouraging values of the cross-validation coefficient (Q2) of 0.608 and 0.806 and conventional correlation coefficient (R2) of 0.960 and 0.934, respectively. Furthermore, values of R2test have been obtained as 0.75 and 0.90, respectively. Besides, y-randomization test was also performed to validate our 3D-QSAR models. Based on these satisfactory results, ten new compounds have been designed and predicted by in silico ADMET method. This study could expand the understanding of chalcone derivatives as anticancer agents and would be of great help in lead optimization for early drug discovery of highly potent anticancer activity.
    Keywords Chemistry ; QD1-999
    Subject code 540
    Language English
    Publishing date 2020-01-01T00:00:00Z
    Publisher Hindawi Limited
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    More links

    Kategorien

  2. Article ; Online: Molecular Docking, Drug likeness Studies and ADMET prediction of Flavonoids as Platelet-Activating Factor (PAF) Receptor Binding

    Mohammed BOUACHRINE / Larbi Elmchichi / Abdellah El Aissouq / Assia BELHASSAN / Hanane Zaki / Abdelkrim Ouammou / Tahar Lakhlifi

    Chemical Review and Letters, Vol 4, Iss 3, Pp 145-

    2021  Volume 152

    Abstract: Studies and scientific research indicate that the platelet-activating factor (PAF) is a major pro-inflammatory mediator in the initiation and development of cancer. There is also evidence confirming that PAF is an integral part of suppressing the immune ... ...

    Abstract Studies and scientific research indicate that the platelet-activating factor (PAF) is a major pro-inflammatory mediator in the initiation and development of cancer. There is also evidence confirming that PAF is an integral part of suppressing the immune system and promoting the appearance of a malignant tumor. For this reason, it is useful to analyze the molecular docking data of eleven flavonoids derivatives isolated from the active leaf extracted from chromolaena odorata with their anti-PAF activity. As a result, it is evident that the natural product of flavonoids may have a positive effect in the development of both therapeutic and preventive agents for platelet activating factor (PAF) antagonist and suggests potential guidelines for the design of PAF inhibitors. Based on the docking score analysis, drug likeness study, and ADMET prediction. We found that six compounds respect all drug-likeness rules and can be used as a potent molecule for inhibition of platelet activating factor (PAF).
    Keywords flavonoids ; platelet-activating factor (paf) ; docking study ; admet ; Chemistry ; QD1-999
    Subject code 306
    Language English
    Publishing date 2021-05-01T00:00:00Z
    Publisher Iranian Chemical Science and Technologies Association
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    More links

    Kategorien

To top