Steroids-specific target library for steroids target prediction

Abstract

Steroids exist universally and play critical roles in various biological processes. Identifying potential targets of steroids is of great significance in studying their physiological and biochemical activities, the side effects and for drug repurposing. Herein, aiming at more precise steroids targets prediction, a steroids-specific target library integrating 3325 PDB or homology modeling structures categorized into 196 proteins was built by considering chemical similarity from DrugBank and biological processes from KEGG. The main properties of this library include: (1) It was manually prepared and checked to eliminate mistakes. (2) The library enriched the possible steroids targets and could decrease the false positives of structure-based target screening for steroids. (3) The ranking by protein name instead of PDB ID could make the screening more efficiency and precise. (4) Protein flexibility was taken into account partially by the different active conformations through the structural redundancy of each category of protein, which leads to more accurate prediction. The case studies of glycocholic acid and 24-epibrassinolide proved its powerful predictive accuracy. In summary, our strategy to build the steroids-specific protein library for steroids target prediction is a promising approach and it provides a novel idea for the target prediction of small molecules.