Optimal 3-way comparison search trees (3WCST's) can be computed using standard dynamic programming in time O(n^3), and this can be further improved to O(n^2) by taking advantage of the Monge property. In contrast, the fastest algorithm in the literature for computing optimal 2-way comparison search trees (2WCST's) runs in time O(n^4). To shed light on this discrepancy, we study structure properties of 2WCST's. On one hand, we show some new threshold bounds involving key weights that can be helpful in deciding which type of comparison should be at the root of the optimal tree. On the other hand, we also show that the standard techniques for speeding up dynamic programming (the Monge property / quadrangle inequality) do not apply to 2WCST's.