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.

尿路结石是尿路结石，长期以来一直与引起慢性肾脏疾病和相关疾病（例如影响全球12％的糖尿病）的较高风险相关。由于尿液过饱和以及细胞和尿蛋白表达的改变，导致出现这种临床状况。肾结石矿物成分已被很好地理解，并作为结石清除的常规部分而被纳入，但是，对蛋白质成分，结石基质的基本组成部分的理解还不够充分，没有被很好地建立起来。石头蛋白质组学由多种技术组成，包括使用X射线衍射仪和IR光谱仪进行晶体分析，样品纯化，使用高通量质谱法对蛋白质进行鉴定和表征。但是，很少有研究利用从这些实验中获得的数据来为相关的鉴定蛋白质赋予功能意义。使用生物信息学工具（例如STRING）进行蛋白质网络分析，以研究蛋白质与蛋白质之间的相互作用，将使研究人员能够更好地了解结石形成机理。因此，对肾结石基质进行全面的蛋白质组学研究将有助于破译蛋白质-晶体途径，从而产生可用于临床的新信息。