Fukui Indices as QSAR Model Descriptors: The Case of the Anti-HIV Activity of 1-2-[(Hydroxyethoxy) Methyl]-6-(Phenylthio) Thymine Derivatives

Fukui Indices as QSAR Model Descriptors: The Case of the Anti-HIV Activity of 1-2-[(Hydroxyethoxy) Methyl]-6-(Phenylthio) Thymine Derivatives

Ali Rahmouni (Modeling and Calculation Methods Laboratory, Tahar Moulay University of Saida, Saida, Algeria), Moufida Touhami (Modeling and Calculation Methods Laboratory, Tahar Moulay University of Saida, Saida, Algeria) and Tahar Benaissa (Physical and Chemical Studies Laboratory, Tahar Moulay University of Saida, Saida, Algeria)
DOI: 10.4018/IJCCE.2017070103

Abstract

This article describes the Quantitative structure–activity relationship models of 1-[2-hydroxyethoxy-methyl]-6-(phenylthio) thymine inhibition of the human immunodeficiency virus (HIV-1) reverse transcriptase (RT) was developed using the multi linear regressions method. These studies were performed using 60 compounds with the help of quantum descriptors as Ionization Potential, Electron Affinity, Softness, global Electrophilicity index and Fukui functions. These indices are obtained at the DFT/B3LYP level of quantum calculation. The statistical quality of the QSAR models was assessed using statistical parameters R2. Good agreements between experimental and calculated log1/EC50 values of anti-HIV activity were obtained. Four QSAR models are presented and the best one use nine molecular quantum descriptors.
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Introduction

Human immunodeficiency virus, or HIV, is the virus that causes acquired immune deficiency syndrome (AIDS). The HIV attacks the immune system by damaging or killing a specific type of white blood cell called a T-lymphocyte, also called a CD4+ or T-helper cell (Conner & Villarreal, 2013; Moss, 2013; Murphy & Weaver, 2016; Nowak & McMechael,1995).

Non-nucleoside reverse transcriptase inhibitors (NNRTIs), are a class of antiretroviral drugs (Cihlar & Ray, 2010; Zhan et al., 2013; Li et al., 2012; King et al., 2002), bind to and block HIV reverse transcriptase (an HIV enzyme). HIV uses polymerase also known as reverse transcriptase (RT) to convert its RNA into DNA . The enzyme synthesizes a double stranded DNA copy of the genomic RNA. The DNA molecule can then integrate into the host genome and become a functional component of its genetic makeup (Temin & Baltimore, 1972). These inhibitors include TIBO, HEPT, Nevirapine, Pyridinone, BHAP, and R-APA. Among them HEPT has proved to be a potent and selective inhibitor of HIV-1(Garg et al., 1999).

1-[(2-hydroxyethoxy) methyl] -6- (phenyl thio) thymine, known as the HETP derivatives are an important series of non-nucleoside inhibitors described in 1989 (Miyasaka et al., 1989) and was revealed as being a potent and selective inhibitor of HIV-1, HETP is one of the most selective drugs due to its high specificity and less toxicity (Baba et al.,1989).

Anti-HIV inhibition QSAR models have been developed (Luco & Ferretti, 1997; Douali et al., 2004; Shaik et al., 2013; Hansch & Zhang, 1992; Inthajak et al., 2017; Prakasvudhisarn & Lawtrakul, 2008; Arakawa et al., 2006; Hannonghua et al., 1996; Toropova et al., 2014; Weekes & Fogel, 2003) for HEPT derivatives (Figure 1). Using different training sets these models are based on Multiple Linear Regression (MLR) (Luco & Ferretti, 1997), Partial Least Squares (PLS) (Luco & Ferretti, 1997), Artificial Neural Network (ANN) (Douali et al., 2004) and Support Vector Machines (SVM) (Shaik et al., 2013). Several structural descriptors and physicochemical variables were used to characterize the studied HEPT derivatives.

Table 1.
Statistical parameters of different constructed QSAR models
Statistical methodsR2Number of moleculesRef
ANN0.958
0.825
80
107
(Douali et al., 2004)
(Shaik et al., 2013
MLR0.799
0.944
0.951
107
33
107
(Shaik et al., 2013)
(Hansch & Zhang, 1992)
(Luco & Ferretti, 1997)
PLS0.943
0.944
79
107
(Luco & Ferretti, 1997)
(Luco & Ferretti, 1997)
SVM0.817107(Shaik et al., 2013)

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