A new descriptor of amino acids-SVREW was derived from principal components analysis of the matrix of 47 walk and path counts descriptors, 44 eigenvalue-based indices descriptors and 41 randic molecular profiles descriptors of amino acids. The structure of ACE Inhibition Peptides was characterized with SVREW, using multiple linear regression (MLR) to establish a quantitative structure-activity relationship, at the same time, adopt the method of internal and external double verify the stability of the model. The relevant statistical parameters as follows: the correlation coefficient (Rcum2), leava-one-out(LOO) cross-validation correlation coefficient (Rcv2) and external validation correlation coefficient (Qext2) were 0.907, 0.791, 0.633 for dipeptides model; 0.831, 0.603, 0.723 for tripeptides model; 0.834,0.668,0.718 for tripeptides model 0.964, 0.853, 0.948 for nonapeptides model; Studies show that the MLR models constructed by SVREW descriptor had good fitting and predictive abilities,to become an effective structure characterization methods in peptide drugs QSAR study and provide guidance for new drug discovery and research.