Protein asymmetry, while crucial for life, can arise from subtle stereoisomerization. However, a comprehensive understanding of the breadth and specificity of the whole stereoproteome (STEP) has been hindered by insufficient stereoisomeric resolution. Here, we introduce an untargeted, de novo STEP discovery protocol for comprehensive STEP profiling and relative quantification. This method employs multidimensional isomeric separation, advanced algorithms, and stereoisomer-specific retention time shifts. STEP mapping identifies 182 neurodegenerative disease-linked, putative stereoisomeric proteins with stereoisomeric ratios of up to 70% in a cell model. A machine learning-derived scoring model achieves high confidence in endogenous stereoisomeric data assessment, achieving an average score of over 0.97 and a modeling accuracy exceeding 98%, with a false discovery rate of less than 5%. Validation experiments using synthetic STEP peptide standards and additional enzymatic localization of D-sites with aminopeptidase M confirm the putative STEP list and their relative abundances. This work advances protein stereoisomer analysis to a proteome scale, connecting protein molecular asymmetry with potential cellular functions and disease mechanisms.