the issue is that there are too many variables (atomic forces) to
consider when simulating how an amino acid chain would fold, in which
case only a quantum computer can be used to simulate it.
These many variables, taking as an example the ones you mentioned, the atomic forces, are somehow grouped in order to facilitate the calculations; thus, it is not necessary for absolutely everything to be simulated simultaneously.
A notable example of this is when the K computer (one of the most powerful supercomputers in Japan, but far from being an optimized quantum computer) calculated the force needed to untie the DNA strands of histones (without taking into account the interactions between each nucleotide).
Multi Scale Modeling of Chromatin and Nucleosomes
By treating multiple atoms as one single particle we can increase the
number of phenomena in our simulation
Basically, they start from the following question: "What is the maximum number of elements and interactions that we can exclude from an analysis object in a simulation in order to still preserve its properties without too much loss and with good accuracy?"
Another example of how this is done is when they apply the Finite Element Method to study hemodynamics in the heart.
They simply transform the heart into a set of regular tetrahedrons, yet still manage to simulate a very wide range of phenomena - such as the rate of consumption of ATP in each part of the heart and the variation in thickness of cardiac muscles during functioning.
Multi-scale Multi-physics Heart Simulator UT-Heart
In other words, they are far from wanting to simulate the heart in all its tissue details. On the contrary, they simplify as much as possible so that simulations are workable on our current supercomputers.