Design, synthesis, and evaluation of pyrazolo-pyrazole derivatives on Methylisocitratelyase of Pseudomonas aeruginosa: in silico and in vitro study
Autor: | Anuradha C M, Chitta Suresh Kumar, Madhusudana Pulaganti |
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Rok vydání: | 2017 |
Předmět: |
0301 basic medicine
In silico Microbial Sensitivity Tests 02 engineering and technology Drug resistance Biology medicine.disease_cause Microbiology 03 medical and health sciences Bacterial Proteins Protein Domains Structural Biology Drug Resistance Multiple Bacterial Intensive care medicine Animals Humans Computer Simulation Amino Acid Sequence Carbon-Carbon Lyases Molecular Biology Virtual screening Sequence Homology Amino Acid Pseudomonas aeruginosa Drug discovery General Medicine 021001 nanoscience & nanotechnology Antimicrobial Anti-Bacterial Agents Molecular Docking Simulation Multiple drug resistance 030104 developmental biology Drug Design Pyrazoles 0210 nano-technology Protein Binding |
Zdroj: | Journal of Biomolecular Structure and Dynamics. 35:2509-2529 |
ISSN: | 1538-0254 0739-1102 |
Popis: | Pseudomonas aeruginosa is an opportunistic micro-organism causing diseases both in animals and humans. In case of human pathology, the role of P. aeruginosa is one of the major concerns in intensive care septicemia. Presently, the drug resistance strains of P. aeruginosa are arising mainly by developing multiple mechanisms due to its natural and acquired resistance to many of the antimicrobial agents commonly used in clinical practice. As a result, there is a direct need to invent new drugs so that they may restrict the outbreak of multidrug resistant strains. Virtual high-throughput insilico screening, which helps to identify the chemical ligands that bind to the enzymes, is an important tool in drug discovery and the drugs discovered in this way are clinically tested. In this study, Methylisocitratelyase (MICL), which is essential for the survival of the bacterium and which doesn't show any similarity with the humans, was selected to evaluate the functions of high-affinity inhibitors (PPI-analogs) that are identified using the virtual screening approach. By adopting the computational analysis tools, structural, functional, and inhibitor interactions of MICL against P. aeruginosa were identified. The PPIA-32 is found to be the best binding interactions with MICL. PPIA-32 reduces the binding affinity for substrate to residues required for MICL enzyme activity and also Root Mean Square Deviation simulations show the most stable nature of PPA32-MICL(complex) than that of MICL alone, thereby effectively inhibiting the growth of virulent P. aeruginosa. To our surprise, the same phenomenon is also identified with other gram-negative bacteria like Escherichia coli, Klebsiella pneumoniae, and Salmonella typhi. |
Databáze: | OpenAIRE |
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