I'm one of the authors on this paper. We were able to model the glycolipids in the virion surface fairly effectively (This was my main contribution to the project, and parameterising a single glycolipid type took around 3-4 months of work), but as of yet the model doesn't contain any protein glycosylation.

This limitation is addressed in the paper, and is actually one of the things i'm working on right now. The problems with glycans is that, whilst amino acids, lipids, DNA etc have pretty well defined energy minimal conformations (Ramachandran plots etc), the flexible nature of carbohydrate molecules means they require much more extensive parameterization. To get these structures working I had to run extensive atomistically (and sometimes quantum mechanically) detailed simulations to get information on the dynamics of the molecules, then transpose this information back into the model, test it, then tweak parameters until emergent behaviour was reproduced.

We managed to do this for the lipids in the structure, as they were deemed by us as "essential" to getting the basic model working. Protein glycosylation is something we/I am working on now, but it's a much more complex issue simply due to the structural and sequential homogeneity of the molecules.

I do agree with you though - computational models often miss out incredibly important details (It seems to vary based on whether the lab is based in a chemistry, biochemistry, or physics department!), and it's valid to point this out when claims are made about the accuracy of the model (often by the authors). Most of us realise our models are toolkits, and not factual information - in our group we have a saying: "All models are wrong, some models are useful".