2D-QSAR Modeling of Quinazolinone Derivatives as Angiotensin II Type 1a Receptor Blockers

Introduction

Controlling hypertension is considered to be a prime objective in the management of cardiovascular diseases (“Principles of Treatment,” 2009). Neurohormonal blockade of the renin-angiotensin system through inhibiting angiotensin-converting enzyme and angiotensin II has involved the pillar of treatment therapy of hypertension (Álvarez et al., 2004; Ma et al., 2010). Renin and angiotensin-converting enzyme (ACE) are two enzymes that work together to release the linear octapeptide angiotensin II, a potent vasoconstrictor that controls blood pressure homeostasis, fluid volume, and electrolyte balance (Pacurari et al., 2014; Piqueras & Sanz, 2020). Angiotensin II also activates the AT2-receptor subtype, which has been shown in experiments to mitigate the negative effects of AT1-receptor stimulation(Timmermans et al., 1992). Selective AT1 receptor blockade thus appears to be a viable therapeutic target in hypertension and cardiovascular disease. AT1-receptor blockers have an advantage over ACE inhibitors in that they enable hyper-stimulation of the AT2-receptor subtype by selectively blocking angiotensin II activities at AT1-receptors (Gradman, 2002). These drugs may not only inhibit angiotensin II's harmful hemodynamic effects, but they may also enhance its beneficial cardiovascular effects (Unger, 2001).

Computer-aided drug discovery is the lynchpin in the exploration and optimization of potential lead compounds (Bajorath, 2015). CADD methodologies help to determine the association of the respective compound with its target before chemical synthesis and biological testing (Yu & MacKerell Jr, 2017). Statistical analytical methods like QSAR correlate chemical structures and biological activities is a realistic technique that can be applied in the prediction of half-maximal inhibitory concentration (IC₅₀) values of new candidates(Aykul & Martinez-Hackert, 2016; Vyas et al., 2014).

Altogether approved Angiotensin Receptor Blockers (ARBs) show the presence of biphenyl, tetrazole, benzimidazole, or non-biphenyl non-tetrazole features (Abraham et al., 2015). Previous studies show that quinazolinone ring constitutes an alternative to imidazole ring for developing novel angiotensin II type 1a (AT-1a) receptor blockers (de Laszlo et al., 1993). Quinazolinones belong to a potent category of the molecular nucleus which is reported to have potent biological importance (Al-Obaid et al., 2009). Literature study shows there have been a large number of computational studies performed and QSAR models developed by de Laszlo et al.1993 (n_compounds = 41) (de Laszlo et al., 1993), Datar et al. 2004 (n_compounds = 28)(Datar et al., 2004), Pandya et al. 2004 (n_compounds = 17) (Pandya & Chaturvedi, 2004), Sharma et al.2014 (n_compounds = 19) (Sharma & Kohli, 2014) to design novel lead as AT-1a receptor blockers. However, models were developed using a small dataset of molecules only (no. of compounds = 17 to 41) and have poor statistical performance that needs to be updated with the current knowledge and newer reported analogs.

In the current research, we aim to develop a good, rational, and statistically robust QSAR model using a larger dataset of 114 Quinazolinone derivatives using easily interpretable molecular descriptors that can correctly identify structural features, with high external predictive ability to discover novel Angiotensin II Type 1a (AT-1a) receptor blocker with more favorable clinical profiles than current generation drugs. Therefore, a better understanding of structural features of Quinazolinones as AT-1a receptor blocker that would be of great significance to any drug design scheme.