OxaBIND: A tool for identifying oxalate-binding domain(s)/motif(s) in protein(s)

Defining physicochemical properties of urinary proteins that determine their inhibitory activities against calcium oxalate kidney stone formation

We have recently reported a set of urinary proteins that inhibited calcium oxalate (CaOx) stone development. However, physicochemical properties that determine their inhibitory activities remained unknown. Herein, human urinary proteins were chromatographically fractionated into 15 fractions and subjected to various CaOx crystal assays and identification by nanoLC-ESI-Qq-TOF MS/MS. Their physicochemical properties and crystal inhibitory activities were subjected to Pearson correlation analysis. The data showed that almost all urinary protein fractions had crystal inhibitory activities. Up to 128 proteins were identified from each fraction. Crystallization inhibitory activity correlated with percentages of Ca2+-binding proteins, stable proteins, polar amino acids, alpha helix, beta turn, and random coil, but inversely correlated with number of Ox2--binding motifs/protein and percentage of unstable proteins. Crystal aggregation inhibitory activity correlated with percentage of stable proteins but inversely correlated with percentage of unstable proteins. Crystal adhesion inhibitory activity correlated with percentage of stable proteins and GRAVY, but inversely correlated with pI, instability index and percentages of unstable proteins and positively charged amino acids. However, there was no correlation between crystal growth inhibitory activity and any physicochemical properties. In summary, some physicochemical properties of urinary proteins can determine and may be able to predict their CaOx stone inhibitory activities.

StoneMod 2.0: Database and prediction of kidney stone modulatory proteins

Stone modulators are various kinds of molecules that play crucial roles in promoting/inhibiting kidney stone formation. Several recent studies have extensively characterized the stone modulatory proteins with the ultimate goal of preventing kidney stone formation. Herein, we introduce the StoneMod 2.0 database (https://www.stonemod.org), which has been dramatically improved from the previous version by expanding the number of the modulatory proteins in the list (from 32 in the initial version to 17,130 in this updated version). The stone modulatory proteins were recruited from solid experimental evidence (via PubMed) and/or predicted evidence (via UniProtKB, QuickGO, ProRule, STITCH and OxaBIND to retrieve calcium-binding and oxalate-binding proteins). Additionally, StoneMod 2.0 has implemented a scoring system that can be used to determine the likelihood and to classify the potential stone modulatory proteins as either "solid" (modulator score ≥ 50) or "weak" (modulator score < 50) modulators. Furthermore, the updated version has been designed with more user-friendly interfaces and advanced visualization tools. In addition to the monthly scheduled update, the users can directly submit their experimental evidence online anytime. Therefore, StoneMod 2.0 is a powerful database with prediction scores that will be very useful for many future studies on the stone modulatory proteins.