ABSTRACT
Alzheimer's disease is a progressive neurodegenerative disorder, which is characterized by amyloid ß peptide deposition in the brain. Aß peptide, the major component of amyloid plaques is generated by the sequential processing of a larger protein called amyloid Precursor Protein by ß-amyloid cleaving enzyme (BACE-1). In this study, we appllied computer assisted methodology unifying molecular docking and pharmacophore filtering to identify potent inhibitors against BACE-1. In order to inspect the pharmacophore region and binding mode of BACE-1 135 reported co-crystallized ligands of BACE-1 were docked into the active site using Glide XP. The present molecular docking studies provided critical information on protein ligand interactions that revealed imminent information on chemical features essential to inhibiting BACE-1. Based on the docking results we proposed structure based pharmacophore features that hold well as potent BACE-1 inhibitors. A huge set of compounds was docked into the active site of BACE-1 and the hits from the docking were filtered to match the chemical features of the pharmacophore model. The compounds resulting from the pharmacophore filtering were again re-docked into the active site of BACE-1 and the three hits bound well into the active sites and matched the pharmacophore models which were identified as possible potential inhibitors of BACE-1. Molecular dynamics simulation reveals that lead 3 shows constant RMSD and the number of hydrogen bonding with the protein among the identified three lead molecules.
Subject(s)
Aspartic Acid Endopeptidases/antagonists & inhibitors , Drug Evaluation, Preclinical/methods , Enzyme Inhibitors/analysis , Enzyme Inhibitors/pharmacology , High-Throughput Screening Assays/methods , User-Computer Interface , Aspartic Acid Endopeptidases/metabolism , Binding Sites , Databases, Chemical , Humans , Ligands , Molecular Docking Simulation , Protein Binding/drug effects , ThermodynamicsABSTRACT
In spite of availability of moderately protective vaccine and antibiotics, new antibacterial agents are urgently needed to decrease the global incidence of Klebsiella pneumonia infections. MurF ligase, a key enzyme, which participates in the bacterial cell wall assembly, is indispensable to existence of K. pneumonia. MurF ligase lack mammalian vis-à-vis and have high specificity, uniqueness, and occurrence only in eubacteria, epitomizing them as promising therapeutic targets for intervention. In this study, we present a unified approach involving homology modeling and molecular docking studies on MurF ligase enzyme. As part of this study, a homology model of K. pneumonia (MurF ligase) enzyme was predicted for the first time in order to carry out structurebased drug design. The accuracy of the model was further validated using different computational approaches. The comparative molecular docking study on this enzyme was undertaken using different phyto-ligands from Desmodium sp. and a known antibiotic Ciprofloxacin. The docking analysis indicated the importance of hotspots (HIS 281 and ASN 282) within the MurF binding pocket. The Lipinski's rule of five was analyzed for all ligands considered for this study by calculating the ADME/Tox, drug likeliness using Qikprop simulation. Only ten ligands were found to comply with the Lipinski rule of five. Based on the molecular docking results and Lipinki values 6-Methyltetrapterol A was confirmed as a promising lead compound. The present study should therefore play a guiding role in the experimental design and development of 6-Methyltetrapterol A as a bactericidal agent.
