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Design of inhibitors of the MurF enzyme of Streptococcus pneumoniae using docking, 3D-QSAR, and de Novo design.
- Source :
-
Journal of chemical information and modeling [J Chem Inf Model] 2007 Sep-Oct; Vol. 47 (5), pp. 1839-46. Date of Electronic Publication: 2007 Jul 31. - Publication Year :
- 2007
-
Abstract
- The biosynthetic pathway for formation of the bacterial cell wall (peptidoglycan) presents an attractive target for intervention. This is exploited by many of the clinically useful antibiotics, which inhibit enzymes involved in the later stages of peptidoglycan synthesis. MurF is one of the four amide bond-forming enzymes (d-alanyl-d-alanine ligating enzyme) that catalyzes the ATP-dependent formation of UDP-MurNAc-tripeptide. In the present study, several MurF inhibitors were docked into the active site of MurF to explore their binding modes and also to gain an insight into the crucial ligand-receptor interactions at the molecular level. The final selection of the "bioactive" conformation of every ligand was influenced by consensus scoring in which various independent scoring functions such as GoldScore, ChemScore, HINT score and X-CScore were employed. Subsequently, 3D-QSAR studies using comparative molecular field analysis (CoMFA) and the new approach comparative residue interaction analysis (CoRIA) have been carried out on the enzyme-inhibitor complexes obtained by docking and postscoring analysis. Finally, new inhibitors have been designed using the de novo approach of Ludi, and the activities of the most promising hits have been predicted with the CoMFA and CoRIA models.
- Subjects :
- Binding Sites
Crystallography, X-Ray
Drug Design
Ligands
Models, Biological
Quantitative Structure-Activity Relationship
Receptors, Drug drug effects
Software
Streptococcus pneumoniae drug effects
Thermodynamics
Enzyme Inhibitors chemistry
Peptide Synthases antagonists & inhibitors
Streptococcus pneumoniae enzymology
Subjects
Details
- Language :
- English
- ISSN :
- 1549-9596
- Volume :
- 47
- Issue :
- 5
- Database :
- MEDLINE
- Journal :
- Journal of chemical information and modeling
- Publication Type :
- Academic Journal
- Accession number :
- 17663541
- Full Text :
- https://doi.org/10.1021/ci600568u