Subtractive genomics approach to identify putative drug targets and identification of drug-like molecules for beta subunit of DNA polymerase III in Streptococcus species.
ABSTRACT The prolonged use of the antibiotics over the years has transformed many organisms resistant to multiple drugs. This has made the field of drug discovery of vital importance in curing various infections and diseases. The drugs act by binding to a specific target protein of prime importance for the cell's survival. Streptococcus agalactiae, Streptococcus pneumoniae, and Streptococcus pyogenes are the few gram positive organisms that have developed resistance to drugs. It causes pneumonia, meningitis, pharyngitis, otitis media, sinusitis, bacteremia, pericarditis, and arthritis infections. The present study was carried out to identify potential drug targets and inhibitors for beta subunit of DNA polymerase III in these three Streptococcus species that might facilitate the discovery of novel drugs in near future. Various steps were adopted to find out novel drug targets. And finally 3D structure of DNA polymerase III subunit beta was modeled. The ligand library was generated from various databases to find the most suitable ligands. All the ligands were docked using Molegro Virtual Docker and the lead molecules were investigated for ADME and toxicity.
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ABSTRACT: Emergence of the multidrug-resistant pathogens has rendered the current therapies ineffective thereby, resulting in the need for new drugs and drug targets. The accumulating protein sequence data has initiated a drift from classical drug discovery protocols to structure-based drug designing. In the present study, in silico subtractive genomics approach was implemented to find a set of potential drug targets present in an opportunist bacterial pathogen, Acinetobacter baumannii (A. baumannii). Out of the 43 targets identified, further studies for protein model building and lead-inhibitor identification were carried out on two cell-essential targets, MurA and MurB enzymes (of A. baumannii designated as MurAAb and MurBAb) involved in the peptidoglycan biosynthesis pathway of bacteria. The homology model built for each of them was further refined and validated using various available programs like PROCHECK, Errat, ProSA energy plots, etc. Compounds showing activity against MurA and MurB enzymes of other organisms were collected from the literature and were docked into the active site of MurAAb and MurBAb enzymes. Three inhibitors namely, T6361, carbidopa, and aesculin, showed maximum Glide score, hydrogen bonding interactions with the key amino acid residues of both the enzymes and acceptable ADME properties. Furthermore, molecular dynamics simulation studies on MurAAb-T6361 and MurBAb-T6361 complexes suggested that the ligand has a high binding affinity with both the enzymes and the hydrogen bonding with the key residues were stable in the dynamic condition also. Therefore, these ligands have been propsed as dual inhibitors and promising lead compounds for the drug design against MurAAb and MurBAb enzymes.Applied biochemistry and biotechnology 07/2013; · 1.94 Impact Factor