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QSAR, structure-based pharmacophore modelling and biological evaluation of novel platelet ADP receptor (P2Y12) antagonist.


ABSTRACT: P2Y12 has a key role in platelet aggregation and thrombus formation via an ADP-induced platelet activation mechanism. Recently, P2Y12 antagonists have become of great interest in the clinical management of antithrombotic therapy. In light of this, we explored the pharmacophoric space of P2Y12 using structure-based pharmacophore modelling. Subsequently, genetic algorithm and multiple linear regression analyses were conducted to select the best combination of physicochemical descriptors and pharmacophoric models to create useful predictive quantitative structure-activity relationship (QSAR) equation (r 2 = 0.9135, r (adj) 2 = 0.9147, r (PRESS) 2 = 0.9129, LOF = 0.3553). One pharmacophoric model emerged in the QSAR equation and was validated by analysing receiver operating characteristic (ROC) curves. The model was then used to screen 200 000 compounds from the National Cancer Institute (NCI) database. The top-ranked hits were in vitro tested, where their IC50's range between 4.20 to 35.00 μM when measured via the electrode aggregometry assay. Whilst, the VASP phosphorylation assay showed 29.70% platelet reactivity index for NSC618159, which is superior to that of ticagrelor.

SUBMITTER: Al-Najjar BO 

PROVIDER: S-EPMC9945858 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature

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QSAR, structure-based pharmacophore modelling and biological evaluation of novel platelet ADP receptor (P2Y<sub>12</sub>) antagonist.

Al-Najjar Belal O BO   Abbas Manal A MA   Sibai Obada A OA   Saqallah Fadi G FG   Al-Kabariti Aya Y AY  

RSC medicinal chemistry 20221122 2


P2Y<sub>12</sub> has a key role in platelet aggregation and thrombus formation <i>via</i> an ADP-induced platelet activation mechanism. Recently, P2Y<sub>12</sub> antagonists have become of great interest in the clinical management of antithrombotic therapy. In light of this, we explored the pharmacophoric space of P2Y<sub>12</sub> using structure-based pharmacophore modelling. Subsequently, genetic algorithm and multiple linear regression analyses were conducted to select the best combination o  ...[more]

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