The error of a MD simulation can be roughly partitioned into four contributions:
- Error due to short-period statistical fluctuations;
- Error due to poor- or non-ergodicity (in other words, extremely long-period statistical fluctuations);
- Error due to numerical round-off and the use of a finite time step;
- Error due to the force field itself.
Quantification of 1 is trivial, for example you can compute your desired property using a series of short MD trajectories, and compute the standard deviation of their mean. 2 is very hard and basically impossible to reliably estimate, because it requires one to sample all low-barrier paths that leads the simulation to a basin with low free energy, which should be NP-hard. 3 is probably predominantly reflected in the conservation of energy, and if in doubt, you can always estimate it by using higher numerical precision (double precision instead of single precision) and a smaller time step.
4 is the most interesting (and arguably the most underrated) contribution. There are some methods for estimating it, for example https://aip.scitation.org/doi/10.1063/1.3545069. However this requires that you go into the training set of the force field, and also have knowledge of the experimental uncertainties of the training data, which can be a non-trivial amount of work. You may search for articles that cite this paper for more examples of error quantification of the force field itself.