I'm not sure I understand. These answers are based on my guessing at what you meant.
1) No, you can't break up a large protein into two smaller jobs. Assuming you did, atoms in this "half" of the protein would no longer feel the influence of bonds to atoms in the other "half" or the attraction effects of the charge of those atoms. As the atoms move, the forces change, including changes to the positions of atoms in the other half. You'd calculate the motions of one half and then suspend processing while the positions in each half are shared with the other half. Throughput would go way down because You'd be spending most of the time transferring data rather than computing new data.
2) A protein aimed at a GPU with, say, 800 shaders can be processed on a GPU with 200 shaders or 2000 shaders It's difficult to assign that same job to a system with 8 CPUs or a GPU with 50 shaders without terribly distorting the deadlines and/or the effects of that trajectory wasting large blocks of time because it happened to be assigned to someone with limited resources. The same is true for CPU jobs ... which have to work on a system with a single threaded CPU up to some number .. typically a max of 16 or 24 ... because those same WUs break if assigned to a 48-core system. Folding proceeds most effectively if the protein can be assigned to donors with a range of resources within a few standard deviations surrounding some average turn-around time.
You seem to be concerned about CPU tasks, too, and this is a topic about GPUs. Nevertheless CPU priority is an important consideration.
3) FAH assigns the lowest priority to CPU jobs so it doesn't interfere with foreground processing (whatever you bought your computer to do). If you're system is running a lot of medium-low priority tasks, consider suspending them or lowering their priority. If FAH is the only thing running, the priority setting is meaningless High priority is NOT faster that low priority (except when something else more important needs to run.)
1b) There are lots interesting proteins that are too big to study, even with today's biggest/fastest GPUs (but as technology moves forward, so will FAH's science). Often a local study will provide sufficient information to be useful, such as the C-terminal region of P53