Bioinformatics and computational analyses of kidney stone modulatory proteins lead to solid experimental evidence and therapeutic potential

Abstract

In recent biomedical research, bioinformatics and computational analyses have played essential roles for examining experimental findings and database information. Several bioinformatic tools have been developed and made publicly available for analyzing protein sequence, structure, functional motif/domain, and interactions network. Such properties are very helpful to define biochemical and functional roles of the protein(s) of interest. During the past few decades, bioinformatics and computational biotechnology have been widely applied to kidney stone research. This review summarizes commonly used tools and evidence of bioinformatics and computational biotechnology applied to kidney stone disease (KSD) with special emphasis on analyses of the stone modulatory proteins that play critical roles in kidney stone formation. Such analyses lead to solid experimental evidence to demonstrate mechanisms underlying their stone modulatory activities. The findings obtained from such analyses may also lead to better understanding of KSD pathogenesis and to further development of new therapeutic and preventive strategies.