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2016 | 57 |

Tytuł artykułu

Understanding the exacerbating role of the metalloproteinase meprin during AKI, an in silico approach

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Treść / Zawartość

Warianty tytułu

Języki publikacji

EN

Abstrakty

EN
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 SWISSMODE, 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.

Wydawca

-

Rocznik

Tom

57

Opis fizyczny

p.18-25,fig.,ref.

Twórcy

  • Centre for Systems Biology and Bioinformatics, UIEAST, Panjab University, Chandigarh, India

Bibliografia

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  • [21] Volkamer A, Kuhn D, Rippmann F, Rarey M, DoGSiteScorer: a web server for automatic binding site prediction, analysis and druggability assessment, Bioinformatics, 28 (15), (2012), 2074-2075.
  • [22] Greg PB, Benjamin E, Turk J, Simon JH, Gail LM, John EB, jacqueline MC, Lewis C, Judith SB, Marked difference between metalloproteases Meprin A and B in substrate and peptide bond specificity, JBC, 276 (16), (2001), 248-255.
  • [23] Stocker W, Bode W, Structural features of a superfamily of zinc- endopeptidases: the metzincins, Curr Opin Struct Biol, 5, (1995) 383-390.
  • [24] LALIGN, Pairwise Sequence Alignment, EMBL-EBI, http://www.ebi.ac.uk/Tools/psa/lalign/,March 21, 2016.
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  • DOI References
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  • [5] Bond JS, Beynon RJ, Reckelhoff JF, David CS, Mep-1 gene controlling a kidney metalloendopeptidas is linked to the major histocompatibility complex in mice, Natural academy of science, 81, (1984), 5542-5545. 10.1073/pnas.81.17.5542
  • [7] Bond, J. S., Rojas, K., Overhauser, J., Zoghbi, H. Y., Jiang, W. The structural genes, MEP1A and MEP1B, for the alpha and beta subunits of the metalloendopeptidase meprin map to human chromosomes 6p and 18q, respectively. Genomics, 25, (1995). 10.1016/0888-7543(95)80142-9
  • [9] Carmago S, Shaw SV, Walker PD, Meprin, a brush-border enzyme, plays an important role in hypoxic/ischemic acute renal tubular injury in rat, Kidney Int, 61, (2002), 959-966. 10.1046/j.1523-1755.2002.00209.x
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  • [11] Dawn ZC, Dinesh VP, Corinne JH, Wen W, Geoffrey D, Dennis CY, Peter SM, Charlotte W, Joaquim T, Richard JW, Zhengyu Y, Actinonin a naturally occurring antibacterial agent, is a potent defromylase inhibitor, Biochemistry, 39, (2000) 1256-1262. 10.1021/bi992245y
  • [12] Bauvois B, Dauzonne D, Aminopeptidase-N/CD13 (EC 3. 4. 11. 2) inhibitors: chemistry, biological evolution, and therapeutic prospects, Med. Res, 26, (2006), 88-130. 10.1002/med.20044
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  • [16] Torsten Schwede, Jurgen Kopp, Nicolas Guex, Manuel C. Peitsch, SWISS-MODEL: an automated protein homology-modeling server, Nucleic Acids Res, 31 (13), (2003), 3381-3385. 10.1093/nar/gkg520
  • [17] Kelley LA, Mezulis S, Yates CM, Wass MN, Sternberg MJ, The Phyre2 web portal for protein modeling, prediction and analysis, Nat Protoc, 10 (6), (2015), 845-858. 10.1038/nprot.2015.053
  • [18] Pettersen EF, Goddard TD, Huang CC, Couch GS, Greenblatt DM, Meng EC, Ferrin TE, UCSF Chimera-a visualization system for exploratory research and analysis, J Comput Chem, 25 (13), (2004), 1605-1612. 10.1002/jcc.20084
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  • [20] Mark NW, Lawrence AK, and Michael JE, 3DLigandSite: predicting ligand-binding sites using similar structures, Nucleic Acids Res, 38, (2010), 469-473. 10.1093/nar/gkq406
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Typ dokumentu

Bibliografia

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