It's no surprise that your coverage improves if you use more than one enzyme for shotgun proteomics. However, on the data processing side of things it can be a serious pain. Workflow set up for each one separately and then go back and combine the data, for most things, right? What if a data processing pipeline was ready to go that was ready to combine loads of different enzymes?
Oh -- here is the paper link.
There are all sorts of smart software to do protein inference (you've got multiple peptides that can be assigned to multiple different proteins, but you don't know which is which) -- NOTHING beats having higher sequence coverage (...well...except for top-down, obviously. but that's another topic for later....nothing beats having higher sequence coverage for shotgun proteomics, is that better?) But you, for real, might get so bummed out about setting up digestions with 10 different enzymes (none of which work as well as trypsin!) and then the pain in the neck the data processing is going to be that you'll just give up and go back to using your LysC/Trysin digestion and not use the others.
The pic at the very top shows the issue and demonstrates how much cooler it is to work with multiple proteases if your software is designed up front for it.
Minor criticism: The authors didn't put the ProteomeXchange ID in, just the MASSIVE ID, so you have to spend 30, seriously, maybe 45 seconds finding the files. Or you can go to this link right to the FTP download site.
THIS IS ALL YOU HAVE TO DO! Your file specific parameters are just swapped to a different enzyme from the front page.
Want a walkthrough like the one I stole this screenshot from? Here is a link to the YouTube video.