ABSTRACT
Objective To investigate the binding capacities of two variants of quinolone resistance-determining region in the DNA gyrase subunit A to substrates in Klebsiella pneumonia (K.pneumonia).Methods Tertiary structures of two variants (type Ⅰ and type FH) of quinolone resistance-determining region in the DNA gyrase subunit A in K.pneumonia were predicted by homology modeling referring to that of wild type.Then,DOCK module in ArgusLab 4.1 software was used to perform molecular docking of two variants and wild type to seven kinds of quinolones substrates,and calculate binding free energies (△G).Moreover,numbers and distances of interaction between amino acid residues of DNA gyrase subunit A and ciprofloxacin were calculated.Results Molecular docking showed that binding free energies of type Ⅰ and type FH to pipemidic acid,ciprofloxacin,gatifloxacin were-26.607 50,-29.530 39,-29.493 09 kJ/mol and-26.696 44,-28.972 83,-29.590 50 kJ/mol,respectively,which declined greater than those of wild type (-27.188 82,-30.872 00 and-30.244 04 kJ/mol,respectively) and showed drug resistance.While binding free energies of type Ⅰ and type FH to levofloxacin were-29.013 81 and-29.497 57kJ/mol,respectively,and that of wild type was-28.016 20 kJ/mol.The binding free energies of type Ⅰ and type FH to nalidixic acid,norfloxacin,ofloxacin increased or declined.Moreover,if distance was less than 5 angstroms,atom pairs formed between wild type of DNA gyrase subunit A and ciprofloxacin had 16 pairs,while type Ⅰ and type FH had 2 pairs and 4 pairs,respectively.If distance was less than 4 angstroms,atom pairs formed between wild type and ciprofloxacin had 8 pairs,while type Ⅰ and type FH had no atom pairs.Conclusion Decline of binding capacities of two variants of DNA gyrase subunit A in K.pneumonia to ciprofloxacin played a role in drug resistance.
ABSTRACT
BioNetSim, a Petri net-based software for modeling and simulating biochemistry processes, is developed, whose design and implement are presented in this paper, including logic construction, real-time access to KEGG (Kyoto Encyclopedia of Genes and Genomes), and BioModel database. Furthermore, glycolysis is simulated as an example of its application. BioNetSim is a helpful tool for researchers to download data, model biological network, and simulate complicated biochemistry processes. Gene regulatory networks, metabolic pathways, signaling pathways, and kinetics of cell interaction are all available in BioNetSim, which makes modeling more efficient and effective. Similar to other Petri net-based softwares, BioNetSim does well in graphic application and mathematic construction. Moreover, it shows several powerful predominances. (1) It creates models in database. (2) It realizes the real-time access to KEGG and BioModel and transfers data to Petri net. (3) It provides qualitative analysis, such as computation of constants. (4) It generates graphs for tracing the concentration of every molecule during the simulation processes.