Optimal Collision Energies and Bioinformatics Tools for Efficient Bottom-up Sequence Validation of Monoclonal Antibodies.

ABSTRACT

Rigorous validation of amino acid sequence is fundamental in the characterization of original and biosimilar protein biopharmaceuticals. Widely accepted workflows are based on bottom-up mass spectrometry, and they often require multiple techniques and significant manual work. Here, we demonstrate that optimization of a set of tandem mass spectroscopy (MS/MS) collision energies and automated combination of all available information in the measurements can increase the sequence validated by one technique close to the inherent limits. We created a software (called "Serac") that consumes results of the Mascot database search engine and identifies the amino acids validated by bottom-up MS/MS experiments using the most rigorous, industrially acceptable definition of sequence coverage (we term this "confirmed sequence coverage"). The software can combine spectra at the level of amino acids or fragment ions to exploit complementarity, provides full transparency to justify validation, and reduces manual effort. With its help, we investigated collision energy dependence of confirmed sequence coverage of individual peptides and full proteins on trypsin-digested monoclonal antibody samples (rituximab and trastuzumab). We found the energy dependence to be modest, but we demonstrated the benefit of using spectra taken at multiple energies. We describe a workflow based on 2-3 LC-MS/MS runs, carefully selected collision energies, and a fragment ion level combination, which yields ∼85% confirmed sequence coverage, 25%-30% above that from a basic proteomics protocol. Further increase can mainly be expected from alternative digestion enzymes or fragmentation techniques, which can be seamlessly integrated to the processing, thereby allowing effortless validation of full sequences.