StoneMod 2.0: Database and prediction of kidney stone modulatory proteins

Abstract

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.