Effect of natural polymorphism on structure and function of the Yersinia pestis outer membrane porin F (OmpF protein): a computational study

Development of IMBs-qPCR detection method for Yersinia enterocolitica based on the foxA gene

Yersinia enterocolitica is an important zoonotic pathogen, which seriously endangers food-safety risk. In this study, the recombinant outer membrane protein OmpF and its antibody were prepared and coupled with immunomagnetic beads (IMBs) to capture Y. enterocolitica in food samples, combining the quantitative PCR detection with primers of virulence factor gene foxA for Yersinia enterocolitica contamination. The results showed that the capture efficiency of approximately 80% using anti-OmpF antibody-immunomagnetic beads and linearly dependent capture under 10¹-10⁵ CFU/mL Y. enterocolitica compared with less than 10% capture of other bacteria. The detection limit of 64 CFU/mL was obtained based on foxA gene PCR detection combined with capture of the anti-OmpF antibody-immunomagnetic beads to detect Yersinia enterocolitica in artificially contaminated milk and pork samples. Compared to the culture method, the developed IMBs-qPCR method has higher consistency, was less time consuming, which taken together provides an effective alternative method for rapid detection of Y. enterocolitica in food.

Comparative subtractive proteomics based ranking for antibiotic targets against the dirtiest superbug: Acinetobacter baumannii

Multidrug-resistant Acinetobacter baumannii is indeed to be the most successful nosocomial pathogen responsible for myriad infections in modern health care system. Computational methodologies based on genomics and proteomics proved to be powerful tools for providing substantial information about different aspects of A. baumannii biology that made it possible to design new approaches for treating multi, extensive and total drug resistant isolates of A. baumannii. In this current approach, 35 completely annotated proteomes of A. bauamnnii were filtered through a comprehensive subtractive proteomics pipeline for broad-spectrum drug candidates. In total, 10 proteins (KdsA, KdsB, LpxA, LpxC, LpxD, GpsE, PhoB, UvrY, KdpE and OmpR) could serve as ideal candidates for designing novel antibiotics. The work was extended with KdsA enzyme for structure information, prediction of intrinsic disorders, active site details, and structure based virtual screening of library containing natural product-like scaffolds. Most of the enzyme structure has fixed three-dimensional conformation. The selection of inhibitor for KdsA enzyme was based on druglikeness, pharmacokinetics and docking scores. Compound-4636 (5-((3-chloro-5-methyl-2-phenyl-2,3-dihydro-1H-pyrazol-4-yl)methoxy)-2-(((1-hydroxy-4-methylpentan-2-yl)amino)methyl)phenol) was revealed as the most potent inhibitor against A. baumannii KdsA enzyme having Gold fitness score of 77.68 and Autodock binding energy of -6.2 kcal/mol. The inhibitor completely follows Lipinski rule of five, Ghose rule, and Egan rule. Molecular dynamics simulation for KdsA and KdsA-4636 complex was performed for 100 ns to unveil what conformational changes the enzyme underwent in the absence and presence of the inhibitor, respectively. The average root means square deviation (RMSD) for both systems was found 3.5 Å, which signifies stable structure of the enzyme in both bounded and unbounded states. Absolute binding energy using Molecular Mechanics-Generalized Born Surface Area (MM-GBSA) reflected high affinity and vigorous interactions of the inhibitor with enzyme active residues. Findings of the current study could open up new avenues for experimentalists to design new potent antibiotics by targeting the targets screened in this study.