Building the two QM-based conformational databases introduced above was relatively straightforward, especially with our new implementation for Azure. The overall computational cost with our DFT program was moderate, and with a more significant one-time investment, it would be possible to build much larger QM-based conformational databases, orders of magnitude larger, for general-purpose drug design. This brings us to a broader discussion on computational expenses, which is increasingly important as the world faces growing challenges related to energy usage.