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Research Articles

Biochemical characterization and structure-based in silico screening of potent inhibitor molecules against the 1 cys peroxiredoxin of bacterioferritin comigratory protein family from Candidatus Liberibacter asiaticus

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Pages 5776-5788 | Received 27 Apr 2022, Accepted 26 Jun 2022, Published online: 09 Jul 2022
 

Abstract

Bacterioferritin comigratory protein family 1 Cys peroxiredoxin from Candidatus Liberibacter asiaticus (CLaBCP) is an important antioxidant defense protein that participates in the reduction of ROS, free radicals, and peroxides. In the present study, we report the biochemical studies and in silico screening of potent antibacterial molecules against CLaBCP. The CLaBCP showed enzymatic activity with the Km value 54.43, 94.34, 120.6 µM, and Vmax of 59.37, 69.37, 70.0 µM min−1 for H2O2, TBHP, CHP respectively. The residual peroxidase activity of CLaBCP was analyzed at different ranges of pH and temperatures. The CLaBCP showed structural changes and unfolding in the presence of its substrates and guanidinium chloride by CD and fluorescence. The structure-based drug design method was employed to screen and identify the more efficient molecule against CLaBCP. The validated CLaBCP model was used for the virtual screening of potent antibacterial molecules. The docking was performed at CLaBCP active site to evaluate the binding energy of the top five molecules (LAS 34150849, BDE 33184869, LAS 51497689, BDE 33672484, and LAS 34150966). All identified molecule has a higher binding affinity than adenanthin analyzed by molecular docking. Molecular dynamics studies such as RMSD, Rg, SASA, and PCA results showed that the CLaBCP inhibitor(s) complex is more stable than the CLaBCP-adenanthin complex. MMPBSA results suggested that the identified molecule could form a lower energy CLaBCP-inhibiter(s) complex than the CLaBCP-adenanthin complex. The screened molecules may pave the route for the development of potent antibacterial molecules against CLa.

Communicated by Ramaswamy H. Sarma

Acknowledgment

We are thankful to the Department of chemistry, IIT Roorkee, to provide the Gaussian software. The authors thank Macromolecular Crystallographic Unit (MCU), a Central Facility at Institute Instrumentation Centre (IIC), IIT Roorkee, for computational work.

Disclosure statement

The authors declare that there is no any conflict of interest.

Additional information

Funding

This work was supported by grant No. BT/PR9877/BRB/10/1274/2014 from Department of Biotechnology, Ministry of Science and Technology, Government of India. DNG, VD, BKS, and MSA thank the University Grant Commission (UGC), Department of Biotechnology [DBT/2015/IIT-R/349], Council of Scientific & Industrial Research (CSIR), and Ministry of Human Resource Development (MHRD) for financial support.

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