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Understanding the Exacerbating Role of the Metalloproteinase Meprin during AKI, an In Silico Approach

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Abstract:

Acute kidney injury (AKI) is a syndrome characterised by the rapid loss of the kidney’s excretory function and is typically diagnosed by the accumulation of end products of nitrogen metabolism (urea and creatinine) or decreased urine output, or both. It is the clinical manifestation of several disorders that affect the kidney acutely. No specific therapies have yet emerged that can attenuate AKI or expedite recovery; thus, the only treatment is supportive therapies and intensive care. The present study was aimed to provide an insight into the importance of a metalloproteinase involved in the pathological conditions of AKI and potentially is a unique target for therapeutic intervention during the disease; Meprin. The data obtained using literature search from PubMed and interaction networks analysis software STRING strongly support the concept that meprin acts as a major matrix degrading enzyme in the kidney, and thus creating an environment that leads to impairment in cellular function rather than cellular stability in response to AKI. The present study discerns the structure of meprin alpha subunit using in silico tools SWISS-MODE, Phyre2 web server and identify the active site and critical amino acid residues in the active site using AADS (IIT Delhi), 3DLigandSite and DoGSiteScorer. Further it is documented that actinonin, a naturally occurring antibacterial agent as a pharmacologically active intervention for the metalloproteinase’s α subunit by blocking its active sites from the environment which was validated using molecular docking algorithms of SWISS-DOCK and FlexX.

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Periodical:

International Letters of Natural Sciences (Volume 57)

Pages:

18-25

DOI:

https://doi.org/10.56431/p-y4cbe4

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Cite this paper

Online since:

August 2016

Authors:

Deepyan Chatterjee*

Keywords:

Actinonin, AKI, Bioinformatics, In Silico Studies, Interaction Networks, Meprin, Metalloproteinase, Molecular Docking, Protein Tertiary Structure Prediction

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Creative Commons CC BY 4.0

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* - Corresponding Author

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