Designing better ALACATs and QconCATs

Rusilowicz M, Newman DW, Creamer DR, Johnson J, Adair K, Harman VM, Grant CM, Beynon RJ, Hubbard SJ. (2023) AlacatDesigner─Computational Design of Peptide Concatamers for Protein Quantitation. J Proteome Res. 2023 Jan 23. doi: 10.1021/acs.jproteome.2c00608.

Protein quantitation via mass spectrometry relies on peptide proxies for the
parent protein from which abundances are estimated. Owing to the variability in
signal from individual peptides, accurate absolute quantitation usually relies
on the addition of an external standard. Typically, this involves stable
isotope-labeled peptides, delivered singly or as a concatenated recombinant
protein. Consequently, the selection of the most appropriate surrogate peptides
and the attendant design in recombinant proteins termed QconCATs are challenges
for proteome science. QconCATs can now be built in a "a-la-carte" assembly
method using synthetic biology: ALACATs. To assist their design, we present
"AlacatDesigner", a tool that supports the peptide selection for recombinant
protein standards based on the user's target protein. The user-customizable tool
considers existing databases, occurrence in the literature, potential
post-translational modifications, predicted miscleavage, predicted divergence of
the peptide and protein quantifications, and ionization potential within the
mass spectrometer. We show that peptide selections are enriched for good
proteotypic and quantotypic candidates compared to empirical data. The software
is freely available to use either via a web interface AlacatDesigner, downloaded
as a Desktop application or imported as a Python package for the command line
interface or in scripts.