Workflows in bottom-up proteomics have traditionally implemented the use of 
proteolysis during sample preparation; enzymatic digestion is most commonly 
performed using trypsin. This results in the hydrolysis of peptide bonds forming 
tryptic peptides, which can then be subjected to LC-MS/MS analysis. While the 
structure, specificity, and kinetics of trypsin are well characterized, a lack 
of consensus and understanding has remained regarding fundamental parameters 
critical to obtaining optimal data from a proteomics experiment. These include 
the type of trypsin used, pH during digestion, incubation temperature as well as 
enzyme-to-substrate ratio. Through the use of design of experiments (DOE), we 
optimized these parameters, resulting in deeper proteome coverage and a greater 
dynamic range of measurement. The knowledge gained from optimization of a 
discovery-based proteomics experiment was applied to targeted LC-MS/MS 
experiments using protein cleavage-isotope dilution mass spectrometry for 
absolute quantification. We demonstrated the importance of these digest 
parameters with respect to our limit of detection as well as our ability to 
acquire more accurate quantitative measurements. Additionally, we were able to 
quantitatively account for peptide decay observed in previous studies, caused by 
nonspecific activity of trypsin. The tryptic digest optimization described here 
has eliminated this previously observed peptide decay as well as provided a 
greater understanding and standardization for a common but critical sample 
treatment used across the field of proteomics.