S Kushwaha, P Chauhan
docking, drug target, ligand designing, virtual screening
S Kushwaha, P Chauhan. Rational Drug Designing for Drug Target Alanine Racemase (Alr) of Mycobacterium tuberculosis . The Internet Journal of Infectious Diseases. 2009 Volume 8 Number 1.
The emergence of multidrug resistant strains and persistence nature of
Re-emergence of multidrug resistant strains of
Computer-aided drug design (CADD)
Computer-aided drug design, often called structure based design involves using the biochemical information of ligand-receptor interaction in order to postulate ligand refinements i.e. improvement in binding affinity to receptor. Identification of new lead compounds for new target depends on the information of the target-ligand system, like target and ligand are well known or Target is known but ligand is not known, or ligand is known etc. A large no. of software’s is available on different information and different strategy for new lead compounds, like Ligbuilder (Wang et al., 2000), ligand scout 2.0. Compatibility of target and ligand could be performed through docking. Docking is a method which predicts the preferred orientation of target to ligand when bound to each other to form a stable complex (Lengauer et. al, 1996). Molecular-docking-based virtual screening is an important tool in drug discovery that is used to significantly reduce the number of possible chemical compounds to be investigated. In addition to the selection of a sound docking strategy with appropriate scoring functions, another technical challenge is to in silico screen millions of compounds in a reasonable time. To meet this challenge, it is necessary to use high performance computing (HPC) platforms and techniques. Several commercial as well as Academics docking programs, Glide (Friesner et. Al., 2004), LigandFit, GLOD, M-ZDOCK (G. Costakes) and Autodock (Vaque M, 2006) are available.
Material and Methods
Identification of unique pathways of by the comparative study of
Metabolic pathway of the host
Identification of non-homologous proteins by performing the BLAST search
Enzymes of unique pathways as well as enzymes involved in other metabolic pathways under carbohydrate metabolism, amino acid metabolism, lipid metabolism, energy metabolism, vitamin and cofactor biosynthesis and nucleotide metabolism have been identified from the KEGG database. All the proteins of the pathways have been subjected to a BLASTp search against the non-redundant database (Altschul et al., 1997). Though sequence similarity less than 25% implies for low similarity, we adopted a stringent measurement of no similarity for non-homologues proteins (Anishetty et al., 2005).
Target characterization and ligand library generation
Selected target were structurally characterized (Active site) through online tools (Pocket finder, p-cats) and offline software (Surface racer and Ligplot) and active site prediction has been done on the basis of comparative analysis of results. Ligand Scout software which automatically calculates a potential pharmacophore by considering the distances and angles between the corresponding chemical functions of the ligand and of the target-protein, were used for ligand generation(G. Wolber, 2005).
Molecular-docking-based virtual screening is an important tool in drug discovery that is used to significantly reduce the number of possible chemical compounds to be investigated. Screenings of best compatible ligand to target were performed through docking.
Results and Discussion
In present study, fourteen unique pathways with 24 new non-homologous targets were identified through
Non-homologous proteins are first preference for effective drug designing to avoid the deceptive targeting and side-effect. Alanine Racemase (Rv3423c) has been considered for drug designing due its role in cell wall synthesis, cell wall organization, alanine metabolic process, alanine racemase activity, and pyridoxal phosphate binding etc. and its structure is available in Protein Data Bank (1XFC). Characterization of structure is very important for rational drug designing.PDB structure of ALR protein is shown in Figure1.
Prediction of active site residues (ALA39, LYS42) of target protein were done through comparative analysis of POCKET FINDER, SURFACE RACER-4.0 and LIGPLOT software results (Figure-2). The comparative results of softwares are shown in table-2.
Ligand library were designed through Ligand Scout 2.0 and ACDLABS 10.0 ChemSketch. Total 50 ligand molecules were generated including Ligand scout generated ligands. Docking was performed by the AutoDock4.0. On the basis of docking energies, a list of top 6 molecules has been proposed which has good compatibility binding affinity with target in table-3.
Best confirmations of these results are shown in table-4. Each of these confirmation results calculated from the ligand with the help of Autodock are shown below. Lowest negative energies of these confirmations have shown best binding of ligands to target proteins shown in table-3.
In the present study, comparative metabolic pathway analysis of the host
Potential target identification of mycobacterium is on high demand due to re-emergence of drug resistance mycobacterium strains. Comparative study of metabolic pathways is a good approach for the identification of mycobacterium tuberculosis but it still need refining with more high level and number of cutoffs. Proposed ligand molecules need further studies like- molecular interaction of ligand with targets, toxicity prediction, drug likeness, etc.
We are grateful to Department of Bioinformatics, MANIT, and Bhopal, India for support and cooperation.