• DocumentCode
    3529099
  • Title

    Ligand-Based Pharmacophore Modeling, Virtual Screening and Molecular Docking Studies for Discovery of Novel Inhibitors against Staphylococcal Infections

  • Author

    Johari, S. ; Basumatary, Panchamita ; Narain, Kanwar ; Parida, Priyabrata ; Barua, N.C.

  • Author_Institution
    Centre for Studies in Biotechnol., Dibrugarh Univ., Dibrugarh, India
  • fYear
    2013
  • fDate
    21-23 Dec. 2013
  • Firstpage
    628
  • Lastpage
    634
  • Abstract
    Staphylococcus aureus is a major pathogen which causes severe staphylococcal infections. It has acquired resistance against most of the beta-lactam antibiotics. Thus there is a need to identify new potent inhibitors for treating staphylococcal infections. It has been observed that the Penicillin binding protein, PBP4 is essential for beta-lactam resistance in Methicillin resistance strains (MRSA) and it is also responsible for peptidoglycan cell wall biosynthesis of S aureus. Thus, it represents a major target for drug rediscovery for staphylococcal infections. In order to obtain the new more potent inhibitors, we performed different computer-aided drug design technologies like pharmacophore modeling, virtual screening and molecular docking studies. It was found that Hamamelitannin (2´, 5-di-O-galloyl-D-hamamelose), a natural plant component can be used as a suppressor of staphylococcal infections. So in our study, we used Hamamelitannin derivatives to identify new inhibitors for treating staphylococcal infections. To identify the chemical features of Hamamelitannin derivatives, pharmacophore models were generated using LigandScout3.1. Among the ten generated models, the first model (Model-1) was selected as best one. The best pharmacophore model (Model-1) characterized by one hydrophobic(H), one aromatic ring(AR), five hydrogen bond acceptor(HBA) features and also had high score(0.7760). From this best model, 5 Hamamelitannin derivative compounds showing maximum essential binding features were obtained. To retrieve new more compounds, the Model-1 was used as query to screen a compound database downloaded from PubChem. The screened compounds were then filtered by applying Lipinski rule of five. Finally to validate our results, we performed docking studies using the CDOCKER program of Discovery Studio3.1 package. The pharmacophore model thus generated may provide guidance to discover new novel inhibitors against staphylococcal infections by highlighting the importa- t binding features of Hamamelitannin derivatives.
  • Keywords
    biochemistry; biomedical materials; diseases; drugs; hydrogen bonds; hydrophobicity; inhibitors; microorganisms; molecular biophysics; proteins; Staphylococcus aureus; aromatic ring features; beta-lactam antibiotics; chemical features; computer-aided drug design technologies; hamamelitannin (2´, 5-di-O-galloyl-D-hamamelose); hydrogen bond acceptor features; hydrophobic features; inhibitors; ligand-based pharmacophore modeling; methicillin resistance strains; molecular docking studies; penicillin binding protein; peptidoglycan cell wall biosynthesis; staphylococcal infection treatment; virtual screening studies; Compounds; Data models; Databases; Immune system; Inhibitors; Machine intelligence; Solid modeling; Docking; Hamamelitannin; Inhibitor; PBP4; Pharmacophore; Staphylococcus aureus; Virtual screening;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Intelligence and Research Advancement (ICMIRA), 2013 International Conference on
  • Conference_Location
    Katra
  • Type

    conf

  • DOI
    10.1109/ICMIRA.2013.131
  • Filename
    6918908