Inhibition Studies of Pyrimidine Class of Compounds on Enoyl-Acp Reductase Enzyme

Leprosy is a chronic disease caused by the bacteria Mycobacterium leprae and Mycobacterium lepromatosis. The disease also known as Hansen’s disease (HD) [1,2]. The World health organization (WHO) reported that it is one of the major diseases in developing countries [3]. The disease has its presence in developing countries due to age old social stigma [4]. Patient generally report late and by that time it has already spread at critical level. The effective treatment for the disease appeared in the year 1930s with the introduction of new drug Dapsone and its derivatives. Soon the bacteria develop resistance for the Dapsone and the treatment of Dapsone was turmoil. The medicine problems remained until the introduction of multi drug therapy (MDT) from 1980s. Though this treatment is effective but it is quite expensive. There is urgent need to find new anti-leprosy agents.


Introduction
Leprosy is a chronic disease caused by the bacteria Mycobacterium leprae and Mycobacterium lepromatosis. The disease also known as Hansen's disease (HD) [1,2]. The World health organization (WHO) reported that it is one of the major diseases in developing countries [3]. The disease has its presence in developing countries due to age old social stigma [4]. Patient generally report late and by that time it has already spread at critical level. The effective treatment for the disease appeared in the year 1930s with the introduction of new drug Dapsone and its derivatives. Soon the bacteria develop resistance for the Dapsone and the treatment of Dapsone was turmoil. The medicine problems remained until the introduction of multi drug therapy (MDT) from 1980s. Though this treatment is effective but it is quite expensive. There is urgent need to find new anti-leprosy agents.
Recently Wang et al. [5] reported that Thioamide, Ethionamide The crystal structure provided by Wang et al. [5] can be utilized to try and test new possible inhibitors using molecular modeling techniques. Recent advances in computation chemistry and biological sciences allow the researchers to model and understand drug targets and to discover drugs that are cheaper and safer. The availability of three-dimensional coordinates for target protein enables the use of structure-based drug design techniques. These technologies include virtual screening, pharmacophore development and structure based optimization [6].
Structure-based drug design (SBDD) is one of several methods available with rational drug design. The inhibition of core enzymes result in cessation of diseases symptoms. These enzymes are treated as drug targets. Using various computational tools it is possible to design new chemical entity before it synthesize in the laboratory. This helps in reducing research cost and saves environment by not wasting huge chemicals in finding new molecules in synthesis chemistry laboratory [6,7]. SBDD uses crystal structure of target enzymes in electronic format and virtual drug molecules to understand the inhibition possibilities of designed molecules. The 3D structure of enzyme target is most often derived from x-ray crystallography or nuclear magnetic resonance (NMR) techniques [7][8][9]. X-ray and NMR methods can resolve the structure of proteins to a resolution of a few angstroms. At this level of resolution, researchers can precisely examine the interactions between atoms in protein targets and atoms in potential drug compounds that bind to the proteins. This ability to work at high resolution with both proteins and drug compounds makes SBDD one of the most powerful methods in drug design [10,11].

Targeting the Enoyl-ACP reductase enzyme
Enoyl-acyl carrier protein reductase is a key enzyme of the type II fatty acid synthesis (FAS) system. It is an attractive target for narrowspectrum antibacterial drug discovery because of its essential role in metabolism and its sequence conservation across many bacterial species [12].
An enoyl-[acyl-carrier-protein] reductase (NADPH, A-specific) is an enzyme that catalyzes the chemical reaction as depicted in equation 1. This enzyme belongs to the family of oxidoreductases, those enzymes which act on the CH-CH group of donor with NAD + or NADP + as an acceptor [13]. The systematic name of this enzyme class is acyl-[acylcarrier-protein]: NADP + oxidoreductase (A-specific). The aim of the present study is to understand the inhibition possibilities and interaction details between Pyrimidine class of compounds and Enoyl-ACP reductase enzyme using molecular modeling techniques. Also utilizing the structure based drug design techniques, evaluate the possible conformations of small molecules and their binding energies with Enoyl-ACP Reductase enzyme (Crystal structure having PDF reference number 2NTV). Also to rank the best three molecules are evaluated on the basis of binding energy, cluster size and possibilities of hydrogen bond.

Preparation of receptor enzyme
The selected enzyme is Enoyl-ACP reductase whose crystal structures are available online and one of them has PDBREF. NO. 2NTV. The structure was downloaded from online protein data bank [14,15]. The enzyme is the product of inhA gene which plays important role in Mycolic acid biosynthesis. The selected 3D structure of enzyme was having natural inhibitor 2-propyl-isonicotinic-acyl-nicotinamideadenine dinucleotide. It is also reffered as PTH-NAD adduct [5].
The 3-D structure of enzyme is generally not complete. It needs the exhaustive checking for the missing bonds and atoms. Using the computer based Autodock tools these anomalies were removed and corrected for 2NTV. This is done only in binding site, as it is the place under investigation for the interactions with ligand.
The solvation process was performed followed by preparation of enzyme grid for docking process using AutoDock [16].

Selection of binding site
To understand the inhibition possibilities, the designed small molecule should be placed in the selected active site of the enzyme. The place is also called as Motif. The motif is the active site consisting of enzyme folding where the drug actually interacts with the amino acids of enzyme. Figure 1 depicts the selected active site and also list amino acids involves in active sites whereas figure 2 shows the 2-D and 3-D structure of natural inhibitor in enzyme.

Small molecule preparation and verification (Ligand preparation)
Library of compounds (also known as Small molecule or Ligand) belongs to Pyrimidine class which were designed using computational tools. Chem Office software provides varieties of tools to design valid 2-D and 3-D structures [17]. Computational methods like molecular mechanics and energy minimizations are employed for generating 2-    [5]. and 3-D structures of small molecules [18,19]. All designed structures initiated from Substituted Pyrimidine which is the basic structure of lead compound. Its general structure is depicted in figure 3. All the designed molecules are Pyrimidine based on the difference in their pharmacophore attached at various substation positions in the lead compound.

2-D Structure 3-D Structure
The designed molecules were sterically modified to confirm the global minima of the same. The 3-D geometry optimizations were done using semi-empirical QM/MM techniques [18,19].The energy minimization process performed until the geometry of the molecules reaches to the global minimum energies. This is done by distorting the 3-D structure prepared by QM.MM until same minimum energy was reported. The list of compounds designed along with various substitutions and their 2-D structures is reported in table 1.
2-D and 3-D properties of designed compounds are calculated and listed in tables 2 and 3 respectively. These are computational properties and calculated using Chem Office Software. The 2-D properties of designed molecules indicate the probabilities of drug-likeness in designed compound. The 3-D properties are the various energies reported while finalizing the geometry of the compound. Minimum total energies of the compounds support the stability of compound in the selected conformation [17].

Docking process
AUTODOCK [16] is widely used computer based tools to process virtual docking of small molecules (ligand) with enzyme. This program has number of tools to perform the docking process. The detailed  docking method is explained in AUTODOCK user guide [20]. Table  4 depicts the detail of hardware and software used for executing AUTODOCK. The working of installed system and software were tested with the known ligand+protein interactions as described in Autodock user manual [20].
In present study two types of docking were performed: i) Docking process using Non-genetic algorithm (NON-GA) ii) Docking process using Genetic algorithm (GA) Nowdays, various artificial intelligence algorithms are used for docking to bring the best results. Genetic algorithm (GA) is one of the intelligence search algorithms used with docking software. It searches    In present study, both types of docking were performed. To use the docking software various parameters needs to be adjusted and tuned. Table 5 depicts the various parameters used for Non-Genetic and Genetic algorithms used for docking. The docking procedure is explained in Autodock manual [20] and used as it is.

Validating the docking model by known drugs
Before docking the prepared set of molecules the model needs validation and hence, the known drugs Dapson, Clofazimine and Rifampicin were docked with the selected enzyme. The docking results for these known drugs are depicted in table 6.
The known drugs interact with enzyme and successfully docked. The reported binding energies are negative and the ligand-enzyme complexes are stable. The results of known drugs are validating the docking methodology as the drugs are already interacting with selected binding site in vitro. The higher negative value of free energy is also supporting the validity of docking methodology. Though docking procedure does have ± 1.0 kcal molprecision, still the results are supporting our model to be used for the unknown molecules.

Docking experiment
Binding energy calculation: Docking algorithm makes use of force field equations and parameters to calculate the binding energy. The binding free energy is the sum of intermolecular interactions between ligand and enzyme. The interactions include van der Waals, H-bond, electrostatic and steric energy of the ligand-enzyme complex. It can be represented by the equation 2 [21][22][23]. Cluster study: The GA docking method also provides the cluster size. It shows how many conformations have the same binding energy value. More the cluster size is, it betters the selected binding pose. Though software provides number of poses (conformations), but in present study only first 3 best poses selected and reported. Table 7 shows the observed cluster values along with the binding energies in kcal mol -1 .

Results
The two types of docking methods reports nearly same binding energies but genetic algorithm method provides higher conformations

Conclusion
The docking results clearly indicate that molecule number 8, 15 and 18 are the best docked molecules and can be further processed as anti-leprosy agents. The selected molecules show better hydrophobic, electrostatic and steric interactions with Enoyl-ACP reductase. The presence of -CH 2 OH at R 1, -C 6 H 5 at R 2 and R 3 positions enhance the negative binding energy (∆G kcal mol -1 ) values. Particularly -OC 6 H 5 at R 1 helps in increasing the interactions, electrostatic groups -OH at R 2 position also helps in LogP values. Table 2 provides the LogP values for all studied molecules using three methods. It is reported that molecule number 8, 15 and 18 are having LogP values less than 5 as per Broto's fragmentation method which supports the probable property of anti-leprosy agents in selected molecules.