Mass spectrometry combined with database search utilities is a valuable protein identification tool. The success of database mining is dependent upon mass accuracy, protein purity, peptide yield, and the genomic complexity of the target organism. Three proteins were selected to investigate the dynamic interaction of these variables and their effect on database mining. With variables of interest controlled, simulated spectra were searched using two searching programs. Results suggest that high mass accuracy improves database searching confidence in the protein identification. With the addition of random noise peaks, some searching programs require a significant increase in the number of peptide ions and the mass accuracy required. Placing limits on database searches usually improves searching efficiency by allowing fewer peptide ions for a successful identification.