The de novo purine biosynthesis enzymes are antibacterial drug design targets; PurE is essential for bacterial survival in vivo. We optimized ligand-based NMR and Surface Plasmon Resonance as primary compound screening methods to identify fragments that bind to PurE. Competition Saturation Transfer Difference NMR was optimized to eliminate false positives. We also developed a computational screening protocol to identify novel fragment-like inhibitors of PurE. This computational screening protocol utilizes molecular docking, GPU-accelerated molecular dynamics, and MM/PBSA free energy estimations to investigate the PurE-fragment binding modes and energies. The octameric structure of PurE provided a distinct advantage because we were able to place eight separate fragment compounds in the active sites to increase the MM/PBSA throughput. Theoretical results were compared with the results of the two experimental fragment screens. The protocol was able to effectively identify the competitive binders that had been independently identified by experimental testing, suggesting the potential utility of this method for the identification of novel fragments for future development as PurE inhibitors.