Study of Pyrimidine-4-carboxamide Derivatives as HIV-1 Integrase Inhibitors Using QSAR and DFT Calculations

Study of Pyrimidine-4-carboxamide Derivatives as HIV-1 Integrase Inhibitors Using QSAR and DFT Calculations

B. Elidrissi, A. Ousaa, M. Ghamali, S. Chtita, M. A. Ajana, M. Bouachrine, T. Lakhlifi
DOI: 10.4018/IJQSPR.2018010107
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Abstract

A Quantitative Structure–Activity Relationship (QSAR) study was performed to predict HIV-1 integrase inhibition activity (pIC50) of thirty-five 5-hydroxy-6-oxo-1,6-dihydropyrimidine-4-carboxamide compounds using the electronic and physico-chemical descriptors computed respectively, with Gaussian 03W and ACD/ChemSketch programs. The structures of all compounds were optimized using the hybrid Density Functional Theory (DFT) at the B3LYP/6-31G(d) level of theory. In both approaches, 28 compounds were assigned as the training set and the rest as the test set. These compounds were analyzed by the principal components analysis (PCA) method, the descendant Multiple Linear Regression (MLR) analyses and the Artificial Neural Network (ANN). The robustness of the obtained models was assessed by leave-many-out cross-validation, and external validation through a test set. This study shows that the MLR has served marginally better to predict pIC50 activity, when compared with the results given by predictions made with a (4-3-1) ANN model.
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Introduction

Integrase is an enzymatic protein produced by RNA retroelements such as retroviruses or retrotransposons. It catalyses the integration step of the replicative cycle of these infectious agents. The foreign DNA is thus “integrated” into the genome of the host organism. This enzyme is particularly studied because it constitutes a therapeutic target of great interest for the treatment of infections by human retroviruses such as the AIDS virus (HIV) (Grinsztejn, 2007).

HIV infects the human immunity system when the viral genome penetrates the nuclear genome of vital cells. It then works through a recombination process catalyzed by the virus-encoded enzyme integrase. According to recent clinical findings, HIV integrase plays an important role during the HIV life cycle. However, the principal problem faced by antiretroviral drugs is emergence of drug resistant HIV strain and hence drug combination therapy, termed as highly active antiretroviral therapy (HAART), was introduced (Moore & Chaisson, 1999). HIV integrase is a potential enzyme target for antiretroviral therapy (Moore & Chaisson, 1999; Li et al., 2015). It plays a specific role to mediate integration of viral DNA formed by reverse transcriptase from RNA template into host DNA. In the process of integration, the integrase enzyme along with several proteins binds on viral DNA to form pre-integration complex (PIC). The integrase enzyme in PIC cleaves off homologous dinucleotide from each 3’ end of viral DNA. This cleavage creates a reactive intermediate with 3’ hydroxyl group which is followed by strand transfer reaction. During this transfer generated by the last reaction, the 3’ hydroxyl group formed during 3’ processing attacks the opposite end of host DNA and forms a new bond. Hence, viral DNA is integrated into host DNA (Pommier et al., 2005). Now, there exist three integrase inhibitors approved by US-FDA: Dolutegravir approved in 2013, Elvitegravir was approved in August 2012 for use in adult patients starting HIV treatment for the first time and Raltegravir was approved by the FDA in October 2007 (Ribeiro et al., 2012). Resistance to Raltegravir and occasionally to Elvitegravir is identified (Gu, 2014). Dolutegravir is the only second-generation strand transfer integrase inhibitor approved by FDA for a large population of HIV-positive patients. Since August 2013, it has also been expected to treat HIV-2 infection (Charpentier et al., 2008).

In the current study, the authors have modeled the HIV-1 integrase inhibitor of 5-hydroxy-6-oxo-1,6-dihydropyrimidine-4-carboxamide derivatives with different substitutions (Table 1), using several statistical tools namely Principal Components Analysis (PCA), Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) calculations (Shah et al., 2014). Using the Quantitative Structure–Activity Relationship (QSAR) method, the activities of chemical compounds can be determined from their molecular structures (Goodarzi et al., 2009). Thus, based on accurate experimental data of only some of the chemicals in one group, the biological activity of chemicals in the whole group can be predicted using the suitable models, including compounds that have not been experimentally synthesized yet (D J. et al., 1991; Burden et al., 2000).

The objective of this work is to develop predictive QSAR models of the HIV-1 integrase inhibitor activity of our studied molecules. Thus, a number of quantum chemical methods and calculations have been performed in order to study the molecular structure and their inhibitor activity (Sakar et al., 2004).

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