Structure-based lead optimization approaches are increasingly playing a role in the drug-discovery process. Virtual screening by molecular docking has become a largely used approach to lead discovery in the pharmaceutical industry when a high-resolution structure of the biological target of interest is available. The performance of two docking programs (Arguslab and Surflex), for virtual database screening, is studied. Surflex is well recognized commercial package while Arguslab is distributed freely for Windows platforms by Planaria Software. Comparisons of these docking programs and scoring functions using a large and diverse data set of pharmaceutically interesting targets and active compounds are carried out. We focus on the problem of docking and scoring flexible compounds which are sterically capable of docking into a rigid conformation of the receptor. The three dimensional structures of a carefully chosen set of 300 pharmaceutically relevant protein-ligand complexes were used for the comparative study. The results show that Surflex outperforms largely Arguslab in all tests studied.
Structure-based lead optimization approaches are increasingly playing a role in the drug-discovery process. Virtual screening by molecular docking has become a largely used approach to lead discovery in the pharmaceutical industry when a high-resolution structure of the biological target of interest is available. The performance of three docking programs (Arguslab, Autodock and FlexX), for virtual database screening, is studied. Autodock and FlexX are well established commercial packages while Arguslab is distributed freely for Windows platforms by Planaria Software. Comparisons of these docking programs and scoring functions using a large and diverse data set of pharmaceutically interesting targets and active compounds are carried out. We focus on the problem of docking and scoring flexible compounds which are sterically capable of docking into a rigid conformation of the receptor. The three dimensional structures of a carefully chosen set of 126 pharmaceutically relevant protein-ligand complexes were used for the comparative study. The Autodock methodology is shown to consistently yield enrichments superior to the two alternative methods, while FlexX outperforms largely Arguslab.
Background: View to its interesting role in the peptidoglycan biosynthesis pathway the enzyme UDP-N- acetylglucosamine enolpyruvyl transferase is an attractive target to develop new antibacterial agents, it catalyzes the first key step of this pathway and its inhibition leads to the bacterial cell death. Fosfomycin is known as the natural inhibitor of MurA. Objective: Call new inhibitors of MurA by virtual screening of different chemical compounds libraries, and test the best scored “virtual hits” against three pathogenic bacteria: Escherichia coli, Bacillus subtilis, and Staphylococcus aureus. Methods: A Virtual screening of the structural analogues of fosfomycin downloaded from PubChem database was performed on one side and of the French National Chemical Library as well as using ZINC database to identify new structures different from fosfomycin on the other, FlexX was the software used for this study. The antibacterial testing was divided into methods: disk diffusion and broth dilution. Results: A set of virtual hits was found with better energy score than that of fosfomycin, seven between them were tested in vitro. Therefore, disk diffusion method explored four compounds exhibited antibacterial activity: CID-21680357 (fosfomycin analogue), AB-00005001, ZINC04658565, and ZINC901335. The testing was continued by broth dilution method for both compounds CID-21680357 and ZINC901335 to determine their minimum inhibitory concentrations, and ZINC901335 had the best value with 457µg/ml against Staphylococcus aureus. Conclusion: Four compounds were found and proven in silico and in vitro to have antibacterial activity: CID-21680357, AB-00005001, ZINC04658565, and ZINC901335.
The increasing resistance of bacteria to antibacterial therapy poses an enormous health problem, it renders the development of new antibacterial agents with novel mechanism of action an urgent need. Peptide deformylase, a metalloenzyme which catalytically removes N-formyl group from N-terminal methionine of newly synthesized polypeptides, is an important target in antibacterial drug discovery. In this study, we report the structure-based virtual screening of ZINC database in order to discover potential hits as bacterial peptide deformylase enzyme inhibitors with more affinity as compared to GSK1322322, previously known inhibitor. After virtual screening, fifteen compounds of the top hits predicted were purchased and evaluated in vitro for their antibacterial activities against one Gram positive (Staphylococcus aureus) and three Gram negative (Escherichia coli, Pseudomonas aeruginosa and Klebsiella. pneumoniae) bacteria in different concentrations by disc diffusion method. Out of these, three compounds, ZINC00039650, ZINC03872971 and ZINC00126407, exhibited significant zone of inhibition. The results obtained were confirmed using the dilution method. Thus, these proposed compounds may aid the development of more efficient antibacterial agents.
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