Regression Analysis and Docking Study of Pyrimidine Based Compounds as anti-Tuberculosis Therapeutic Agents

Received: 09/Apr/2019, Accepted: 19/Apr/2019, Online: 30/Apr/2019 AbstractIn the drug-design process, structure activity relationship is an important tool for estimation of biological activity of the unknown compounds. In this process, the objective is development of a relationship between structural features of molecules and the property of interest i. e. biological activity. On the basis of this relationship, the biological activity can be predicted for new candidate structures. Initially, the forty two substituted pyrimidine molecules with known biological activities were considered as known set for regression analysis model building purpose. The properties module from Datawarrior used to calculate descriptors. Structure activity model indicates that these descriptors have significant relationships with observed bioactivity. We have observed a high relationship between experimental and predicted activity values, indicating the validation and the excellent quality of the derived model. In the present study, the new substituted pyrimidine molecules are designed, optimized and their descriptors were calculated using Datawarrior modules. Then by using the Regression analysis model, their biological activities are studied as well as inhibition studies for the 1QPQ by molecular docking method are also carried out. Thus on the basis of regression analysis study and docking study of substituted pyrimidine derivatives, we can conclude that these compounds on further studies may prove to be therapeutic agent against tuberculosis.


I. INTRODUCTION
In the drug-design process, quantitative structure activity relationship (QSAR) has come to play a major role. In this process, the objective is development of a relationship between structural features and the property of interest, so that property values can be predicted for new candidate structures. [1] The goal of QSAR modeling is to establish a trend in the descriptor values, which parallels the trend in biological activity. [2] As per the techniques developed in the recent period, the experimental property values have been related directly to structure information. The structure of the molecule is represented in a mathematical manner so that necessary information can be encoded and extracted in a form that lends itself to modeling. In this process, it is expected that the significant structural features are encoded in the structure representation and then identified in the modeling process. In this manner, the synthesis of new candidates may be guided towards the desired goal.
The structure-based approach is a coherent approach to the QSAR problem that has been developed over the past 25 years, and is part of a broader approach, the so-called Quantitative Information Analysis (QIA) [3].
In the QIA approach, emphasis is placed on the two aspects of the data that are known directly, the measured activity and/or property values on the one hand, and the molecular structures in the data set on the other. The required information is related to the manner in which molecules present themselves to each other in non-covalent interactions. It now appears clear that this approach can be accomplished without the need for explicit three-dimensional (3D) structure information. The necessary information is implicit in the encoded descriptors. It should be pointed out that topological structure descriptors are used to produce good predictive models for logP. [4] [5] [6] [7] Pyrimidine is an important precursor for the synthesis of a wide variety of heterocyclic compounds. The variety of compounds synthesized reported to have various biological anticancer, antiviral, antibacterial, antioxidant, antituberculosis and antidepressant. [8] such as vitamins, hormones, and antibiotics and hence they are used in the design of biologically active molecules. Some substituted pyrimidine derivatives were also found to show antibacterial and antifungal activity. [9] [10] Datawarrior version 4.6.1 package [11] is able to calculate certain physico-chemical properties, lead-or drug-likeness related parameters, ligand efficiencies, various atom and ring counts, molecular shape, flexibility and complexity as well as indications for potential structure activity.
In current study, the experimental work consist initially the equation (model) building for regression analysis by using known set of molecules. By using this equation, the biological activities for newly designed (unknown) molecules are determined. These newly designed molecules are also subjected to inhibition studies against Quinolinic acid phosphoribosyl transferase (QAPRTase) enzyme (PDB code: 1QPQ), an important target for designing novel potential inhibitor for tuberculosis.

II. EXPERIMENTAL
The activity parameter used in this study is substituted pyrimidine inhibitory activity. The studied compounds are Tuberculosis inhibitors which inhibit Mycobacterium Tuberculosis. Interestingly, all these compounds were active and showed M. Tuberculosis inhibition with biological activities values ranged between 374 and 16 μM. [12] [13] IIa. Descriptors generation Firstly, the forty two investigated molecules were preoptimized by means of the Molecular Mechanics. After that, the resulted minimized structures were further refined using the semi-empirical techniques. Then, these substituted pyrimidines were re-optimized by using Gaussian program package.

IIb. Regression analysis
Multiple linear regression analysis of molecular descriptors was carried out using the stepwise strategy in SPSS version 19 for Windows.  [14] Therefore the Quinolinic acid phosphoribosyl transferase (QAPRTase) enzyme provides an attractive target for designing novel potential inhibitor for tuberculosis. [15].
iGEMDOCK is an integrated tool that creates virtual screening environment from preparations through postscreening analysis with pharmacological interactions. First, iGEMDOCK provides interactive interfaces to prepare both the binding site of the target protein and the screening compound library. Then, each compound in the library is docked into the binding site by using the docking tool iGEMDOCK. Subsequently, iGEMDOCK generates proteincompound interaction profiles of electrostatic, hydrogenbonding, and van der Waals interactions. Finally, iGEMDOCK ranks and visualizes the screening compounds by combining the pharmacological interactions and energybased scoring function of iGEMDOCK. [16] The selected set of three ligands were subjected to accurate docking (very slow docking) by setting population size of 700 is set with 70 generation and 10 solutions. After the completion of the docking, the post docking analysis was performed to find the docking pose and its energy values.

IIIa. Structure activity relationships (SAR)
We have studied eight physical chemical proprieties of series of substituted pyrimidine derivatives in which various degrees of substituents on aromatic ring have been introduced, these substituents include electron donating group such as methoxy and electron withdrawing group like nitro, using HyperChem software. The structure for substituted pyrimidine given as: UK pyrs9 2,6-dichloro-N-(2iodophenyl)pyrimidin-4-amine 20 UK pyrs20 2,6-dichloro-N-(2,4,6triiodophenyl)pyrimidin-4-amine 10 UK pyrs10 2,6-dichloro-N-(4iodophenyl)pyrimidin-4-amine 21 UK pyrs21 2,6-dichloro-N-(naphthalen-1yl)pyrimidin-4-amine 11 UK pyrs11 1-(2-((2,6-dichloropyrimidin-4yl)amino)phenyl)ethanone The values of fraction variance may vary between 0 and 1. QSAR model having r 2 ˃ 0.173 will only be considered for validation. For example, the value r = 0.416 and r 2 = 0.173 allowed us to indicate firmly the correlation between different parameters (independent variables) with biological activity of the compounds. In equation of biological activity, the negative coefficients of molecular volume (MV) and molecular weight (MW) explain that any increase in molecular volume or molecular weight of the compounds causes a decrease in the biological activity. can be useful for predicting the activity of new substituted pyrimidine derivatives prior to their synthesis. Structure activity model indicates that these descriptors have significant relationships with observed bioactivity. We have observed a high relationship between experimental and predicted activity values, indicating the validation and the excellent quality of the derived model. In equation of biological activity, the negative coefficients of surface area that any increase in surface area of the molecules causes a decrease in the biological activity. As well as, the inhibition of Quinolinic acid Phosphoribosyltransferase (QAPRTase) having PDB code 1QPQ proteins can be an effective drug in the prevention and treatment of tuberculosis. In the present study, the ligands were generated and were studied for its ability to inhibit the 1QPQ by molecular docking method. The ligands with good inhibitory properties were generated among which UK pyr 46, UK pyr 49, UK pyr 37, UK pyrs3 and UK pyrs4 are found to be excellent drug candidate based on the molecular docking studies and its regression studies. Thus on the basis of regression analysis study and docking study of substituted pyrimidine derivatives, it can be concluded that these compounds on further studies may prove to be therapeutic agent against mycobacterium tuberculosis.