CoMPaseD: advanced planning of proteomic experiments aiming to identify small proteins.

Abstract

In proteome studies, the application of alternative proteases, exclusively or in addition to trypsin, often increases protein sequence or proteome coverage. It has recently been shown that, in particular, the analysis of small proteins benefits from such multi-protease approaches. However, selecting the most optimal combination of proteases either requires laboursome experiments or the decision of an experienced user, which might be biased. In this manuscript, we present a protease score that enables the objective comparison of multiple-protease digestions and a Python-based tool named CoMPaseD (Comparison of Multiple Protease  Digestions), which utilizes Monte-Carlo simulations to predict this score for a user-defined set of proteases and any combination of these. By analysis of the small proteomes of the two model organisms Bacillus subtilis and Methanosarcina mazei with five proteases and different experimental setups, we demonstrate a good correlation between experimentally derived and predicted scores. This highlights the broad applicability of CoMPaseD, which can effectively guide the selection of proteases to enhance the characterization of specific subsets of the proteome, e.g. based on factors such as protein size, localization or isoelectric point. CoMPaseD is freely available at https://github.com/MicrobialProteomics/CoMPaseD.