The reason CERN has built a 27km, 14TeV, super-cooled, superconducting magnetic particle collider is because we know so much about fundamental Physics that it takes something really crazy, like the LHC, running billions of collisions, in order to find something which we might find surprising. So far, it's not surprised us; although it has confirmed the ideas Peter Higgs developed 50 years ago.
Of course, there is still debate and surprise to be had in other, non-fundamental areas; yet these are studying the consequences of the fundamental laws (they're debating the output of a simulation, not its code).
You can stop higher than atoms anytime you think the result satisfies your experimental measurements.
It seemed to me that your argument was "There are details of how an atom works that we currently don't know how to simulate. A brain's behaviour is a result of the behaviour of the atoms it consists of. Therefore, it's impossible to simulate a brain to any degree of accuracy at all."
Using the same logic, and given that most everything we interact with is made of atoms, one could deduce that it's impossible to simulate anything at all, except for electron beams, maybe. That seems to me to be obviously in contradiction to how well we can navigate and manipulate the world in our day-to-day lives (let alone in engineering), which depends on us simulating the world all the time, at least to some degree.
Now, I'd be interested in understanding how you reconcile that.
People use that to extrapolate in the other direction, and assume that because Newton's laws can be simulated, you can simulate an atom, thus everything. We don't have a view of reality at subatomic levels that says: "this is it and there's nothing beyond it". You don't know if your simulation of a brain will show an emergent intelligence if simulated with 'float', 'double' or 'infinite'.
They can't run simulations instead of their experiments, since they're looking for new fundamental Physics; in other words, they're trying to find out which of their simulations describes the world best.
AI research isn't looking for fundamental results; we have a good theory of computation, and a good-enough theory of Physics to describe our brains. We know which simulation to run. The remaining problems are 'only' to do with resource usage: which computations/arrangements-of-atoms can give us good-enough results in short-enough time?
If we could efficiently run O(2^n) algorithms, AI would be unnecessary; we could just brute-force everything (including brain emulation).