Affiliation:
1. Department of Biotechnology, Jaypee Institute of Information Technology, Noida, India
Abstract
Urolithiasis, which is the presence of stones in the urinary tract, has long been linked with a
higher risk of causing chronic kidney diseases and associated illnesses, such as diabetes-affecting 12%
of the world population. This clinical condition arises due to the supersaturation of urine and alterations
in the expression of cellular and urinary proteins. The renal stone mineral composition has been
well understood and incorporated as a routine part of stone removal, however, the protein composition,
an essential fraction of the stone matrix has been inadequately understood and not adeptly established.
Stone proteomics consists of a number of techniques including crystal analysis using X-ray diffractometry
and IR spectroscopy, sample purification, identification and characterization of proteins using
high throughput mass spectrometric methods. However, not many studies have utilized the data obtained
from these experiments to assign functional significance to associated identified proteins. Protein
network analysis using bioinformatic tools such as STRING to study protein-protein interactions
will enable researchers to get better insight into stone formation mechanics. Hence, a comprehensive
proteomic study of kidney stone matrix will help in deciphering protein-crystal pathways generating
novel information useful for clinical application.
Publisher
Bentham Science Publishers Ltd.
Subject
Molecular Biology,Biochemistry
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