S Kushwaha, P Chauhan, M jha, S Shrivastava
docking, drug target, ligand designing, virtual screening
S Kushwaha, P Chauhan, M jha, S Shrivastava. Rational Drug Designing for Drug Target Alanine Racemase (Alr) of Mycobacterium tuberculosis. The Internet Journal of Laboratory Medicine. 2008 Volume 3 Number 2.
The emergence of multidrug resistant strains and persistence nature of
Re-emergence of multidrug resistant strains of
Computer-aided drug design (CADD)
Drug discovery and development is an intense, lengthy and an interdisciplinary endeavor. Drug discovery is started with target identification and lead discovery, followed by lead optimization and pre-clinical
Material and Methods
Identification of unique pathways of by the comparative study of
Metabolic pathway of the host
KEGG database (Kanehisa et al., 2002). Pathways which do not appear in the host but present in the pathogen have been identified as unique pathways. unique pathways were identified in order to design drug candidates for proteins that were present in
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). Pocket-Finder finds the active site by scanning a probe radius 1.6 angstoms along all gridlines of grid resolution 0.9 angstroms surrounding the protein. Surface Racer calculates exact accessible surface area, molecular surface area and average curvature of molecular surface for macromolecules. The program also analyzes cavities in the protein interior inaccessible to solvent from outside. Each tool has its unique way of identifying the active site. To obtain more accurate results active site prediction was 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, was used for ligand generation(G. Wolber, 2005). Further to validate the interaction between the protein and the ligand Ligplot was used. It automatically generates schematic diagrams of protein-ligand interactions for a given PDB file. The interactions shown are those mediated by hydrogen bonds and by hydrophobic contacts.
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 by AutoDock. AutoDock is a suite of automated docking tools. It is designed to predict how small molecules, such as substrates or drug candidates, bind to a receptor of known 3D structure. It provides results that are more accurate and reliable.
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.