QSAR Modeling Using Quantum Chemical Descriptors of Benzimidazole Analogues With Antiparasitic Properties

QSAR Modeling Using Quantum Chemical Descriptors of Benzimidazole Analogues With Antiparasitic Properties

Christiaan Jardinez, José L. Medina-Franco
DOI: 10.4018/IJQSPR.2018070105
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Abstract

This article describes how benzimidazole is a privileged scaffold that has been used as a basis to develop antiparasitic compounds. Herein, the relationship between the chemical structure and biological activity against Trichomonas vaginalis of sixty nine benzimidazole analogues was studied using Density Functional Theory and multiple linear regression analysis. The best QSAR model obtained highlights the correlation between the pIC50 with frontier orbital energy gap, Van der Waals volume, number of hydrophobic atoms, Harmonic Oscillator Model of Aromaticity Index, partition coefficient, and number of total second C(sp3). The model has values of R2 = 0.784, Q2 = 0.720 with the validation parameters: F-test = 37.51, SPRESS = 0.274, and SDEP = 0.262. The average values of R2adj (Obs) and (Calc) are very close (0.763 and 0.760 respectively), which suggests a relatively stable predictively of the model for these data. The QSAR model developed can be employed to estimate the biological activity of new compounds based on a benzimidazole core scaffold.
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Introduction

The protozoan of Trichomonas vaginalis (T. vaginalis) causes a sexually transmitted disease known as trichomonosis. Each year the World Health Organization reports more than 160 million new cases of this disease (“Global Prevalence and Incidence of Selected Curable Sexually Transmitted Infections: Overview and Estimate,” 2001). In order to treat this disease, some benzimidazoles are currently used as drugs. Benzimidazoles have a large impact in clinical medicine because of their therapeutic properties as antiparasitic agents (Kleeman, Engel, Kutscher, & Reichert, 1999). In fact, the benzimidazole ring shows an important heterocyclic system having different biological activities against various pathogens such as Kiehsiella pneumoniae (Yalçin & Şener, 1993), T. vaginalis (Navarrete-Vázquez et al., 2003), Candida albicans (Şener, Yalçin, & Sungur, 1991; Turker, Sener, Yalcin, Akbulut, & Kayalidere, 1990), among others. In the search for new drugs that act against the protozoan T. vaginalis, Pérez-Villanueva et al. reported a series of synthetic benzimidazoles as promising antiparasitic agents (Pérez-Villanueva, Medina-Franco, et al., 2011). The authors of that work emphasized that that set of benzimidazoles was obtained through an extensive investigation of several years. The authors determined the biological activity of the benzimidazoles against a series of parasites including T. vaginalis (Andrzejewska et al., 2002; Andrzejewska et al., 2004; Hernández-Luis et al., 2010; Navarrete-Vázquez et al., 2006; Navarrete-Vázquez et al., 2003; Pérez-Villanueva, Romo-Mancillas, et al., 2011; Valdez-Padilla et al., 2009). The changes of the antiparasitic activity against T. vaginalis of that set of compounds is due to substitutions in positions 1, 2, 5 and 6 of the benzimidazole ring (see below). Of note, the molecular target associated with the antiparasitic activity vs. T. vaginalis remains unknown.

Computational chemistry allows exploring and predicting the biological activities of untested compounds reducing time and resources of experimental studies (Navarrete-Vázquez et al., 2006; Zhang, Golbraikh, Oloff, Kohn, & Tropsha, 2006; Zheng et al., 2013). In fact, some drugs available in the clinic were designed with the aid of quantitative structure-activity relationship studies (QSAR). QSAR models have been useful for understanding the relationship of molecular properties against the biological activity of different compounds. These models help in the development of new molecules with desirable biological properties (Nargotra et al., 2009).

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