Ultraviolet photodissociation (UVPD) mass spectrometry
unlocks
insights into the protein structure and sequence through fragmentation
patterns. While N- and C-terminal fragments are traditionally relied
upon, this work highlights the critical role of internal fragments
in achieving near-complete sequencing of protein. Previous limitations
of internal fragment utilization, owing to their abundance and potential
for random matching, are addressed here with the development of Panda-UV,
a novel software tool combining spectral calibration, and Pearson
correlation coefficient scoring for confident fragment assignment.
Panda-UV showcases its power through comprehensive benchmarks on three
model proteins. The inclusion of internal fragments boosts identified
fragment numbers by 26% and enhances average protein sequence coverage
to a remarkable 93% for intact proteins, unlocking the hidden region
of the largest protein carbonic anhydrase II in model proteins. Notably,
an average of 65% of internal fragments can be identified in multiple
replicates, demonstrating the high confidence of the fragments Panda-UV
provided. Finally, the sequence coverages of mAb subunits can be increased
up to 86% and the complementary determining regions (CDRs) are nearly
completely sequenced in a single experiment. The source codes of Panda-UV
are available at .