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2D-QSAR Modeling of Quinazolinone Derivatives as Angiotensin II Type 1a Receptor Blockers
Abstract
Angiotensin receptor blockers (ARBs) are a group of drugs primarily used in the treatment of cardiovascular disease. Multiple quantitative structural activity relationship (QSAR) models established for prediction of angiotensin II type 1a (AT-1a) receptor blocking activity of quinazolinone derivatives to investigate the structural attributes that have significant correlation with biological activity. The genetic algorithm (GA) approach was used to generate a highly predictive models using easily interpretable Py, OEstate and Padel descriptors. OECD principles have been followed to develop statistically robust QSAR models (R2tr = 0.8055 – 0.8625) with good external predictivity (CCCex = 0.7528-0.8450). The multiple QSAR models successfully identified that increase in surface area of negatively charge carbon atom within four bonds from N atom, presence of tetrazole substituents and sp3 N atoms governs the AT-1a receptor blocking activity. The validated QSAR models of present study might be helpful for evaluation AT-1a receptor blocking activity to identify novel hits.
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