Parasitic protozoa lack the ability to synthesize purine nucleotides de novo, relying instead on purine salvage enzymes for their survival. Guanine phosphoribosyltransferase (GPRT) from the protozoan parasite Giardia lamblia is a potential target for rational antiparasitic drug design, based on the experimental evidence, which indicates the lack of interconversion between adenine and guanine nucleotide pools. The present study is a continuation of our efforts to use three-dimensional structures of parasitic phosphoribosyltransferases (PRTs) to design novel antiparasitic agents. Two micromolar phthalimide-based GPRT inhibitors were identified by screening the in-house phthalimide library. A combination of structure-based scaffold selection using virtual library screening across the PRT gene family and solid phase library synthesis led to identification of smaller (molecular weight, <300) ligands with moderate to low specificity for GPRT; the best inhibitors, GP3 and GP5, had K i values in the 23 to 25 M range. These results represent significant progress toward the goal of designing potent inhibitors of purine salvage in Giardia parasites. As a second step in this process, altering the phthalimide moiety to optimize interactions in the guanine-binding pocket of GPRT is expected to lead to compounds with promising activity against G. lamblia PRT.Computer-aided drug design in combination with combinatorial chemistry approaches, whereby focused or diverse combinatorial libraries can be designed using computational methods, is becoming increasingly important in the process of drug discovery for parasitic targets (7,11). A number of groups have reported on the successful design of inhibitors directed against trypanosomal (2,4,(15)(16), leishmanial (6), malarial (19), and tritrichomonal (3, 27) targets active in the 10 nM to 50 M range. However, with the number of compounds that could be generated by combinatorial chemistry growing exponentially, it has become apparent that chemical diversity has surpassed the capacity of high-throughput screening. In the case of antiparasitics research, which is concentrated in a limited number of mostly academic labs, the need for more rapid ligand screening tools has become apparent. Recently, in silico methods for database screening have come to the forefront of drug discovery (30). By accelerating the screening process, these methods are able to capitalize on the potential of virtual combinatorial libraries. While a number of recent reports have focused on structure-based pruning of the virtual combinatorial libraries built around a given preselected scaffold, there has been a growing trend toward combinatorial scaffold evaluation against a number of biological targets. Evaluation of binding preferences for combinatorial libraries across a range of targets could, in principle, provide information about scaffold generality or selectivity as related to the target selection (M. L. Lamb, K. W. Burdick, S. Toba, M. M. Young, A. G. Skillman, X. Zou, J. R. Arnold, and I. D. Kuntz, unpubl...