That is a beautiful Coupon Collector's Problem, with a little twist introduced by the fact that stickers come in packs of 5.
If the stickers were bought individually the result are known, as you can see here.
All the estimates for a 90% upper bound for individually-bought stickers are also upper bounds for the problem with a pack of 5, but a less close upper bound.
I think that getting a better 90%-probability upper bound, using the pack of 5 dependence, would get a lot more difficult and would not give you a far better result.
So, using the tail estimate $ P[T>\beta n \log n] \leq n^{-\beta+1}$ with $n=424$ and $n^{-\beta+1} = 0.1$, you'll get to a good answer.
EDIT:
The article "The collector’s problem with group drawings" (Wolfgang Stadje), a reference of the article brought by Assuranceturix, presents an exact analytical solution for the Coupon Collector's Problem with "sticker packs".
Before writing the theorem, some notation definitions: $S$ would be the set of all possible stickers, $s = |S|$. $A \subset S$ would be the subset that interests you (in the OP, $A = S$), and $l = |A|$. We're going to draw, with replacement, $k$ random subsets of $m$ different stickers. $X_{k}(A)$ will be the number of elements of $A$ that appear in at least one of those subsets.
The theorem says that:
$$ P(X_{k}(A) = n) = {l \choose n} \sum_{j=0}^{n}(-1)^j {n \choose j}\left[\frac{s+n-l-j \choose m}{s \choose m}\right]^k $$
So, for the OP we have $ l=s=n=424$ and $m=5$. I did some tries with values of $k$ near the estimate for the classical coupon collector's problem (729 packs) and I got a probability of 90.02% for k equals to 700.
So it was not so far from the upper bound :)