Earlier quoted context omitted.
It would require an advance in theory. When I took a graph theory course it fascinated me how the Ramsey theory problem goes from paper and pencil complexity to beyond computing power in two steps (R(3,3) = 6, R(4,4) = 18, R(5,5)=(43..48?)). I once spent some time calculating the effort (but don't have the results handy), a rough number for a naive approach to exhaustively searching the problem space would involve so…
It is worse than that. Here is the calculation. The number of graphs of size n is 2^(n choose 2). (There are n choose 2 pairs of points, each of which could be or not be an edge.) If the answer is 43, that's 2^903 which is roughly 6.762 * 10^271. If the answer is 48, that's 2^1128 which is roughly 3.646 x 10^339. Naive plus better computers is not enough to tackle this problem.
This is overcounting by many orders of magnitude. For example, there's only one graph with one edge, not (n choose 2). For n = 43 you're overcounting these graphs by a factor of 903.
Similarly there are only two graphs with two edges (either the two edges are connected or not), not ((n choose 2) choose 2). For n = 43 you're overcounting these graphs by a factor of ~200k.
For graphs with three edges you can have (1) a triangle, (2) three edges connected end to end forming a single path, (3) three connected edges forming a star, (4) two connected edges and one single, or (5) three unconnected edges. Compared to your count of ((n choose 2) choose 3), you're overcounting by a factor of about 24 million for n=43.
The total (over)count is going to be dominated by graphs with approximately (n choose 2)/2 edges, which intuitively is where I also expect the overcounting factor to peak.