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Fast atom bombardment combined with mass spectrometry (FAB/MS), high resolution FAB/MS, FAB tandem mass spectrometry (MS/MS), and gas chromatography/mass spectrometry (GC/MS) were used to determine the composition of the resinous material recovered from the wrappings of an Egyptian mummy believed to be from the Roman period (100-350 A.D.). FAB/MS and MS/MS studies identified several oxidation products of abietic acid as the principal resin components, indicating that one or more species of coniferous trees were used by the Egyptians as a source of the resin. GC/MS studies also identified several n-alkanes with carbon numbers from C19 to C33 in the sample. The relative amounts of these n-alkanes, along with characteristic trace metals, indicate that bitumen, an asphalt native to the region, was added to the resin. The presence of this ancient source of carbon in this sample explains the inconsistent date assigned to the mummy by carbon-14 analysis.

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In this paper, we describe an automated, high-throughput analytical tool for the unambiguous characterization of the active component(s) of a combinatorially derived reaction mixture. We call this technique high-throughput bioassay-guided fractionation (BGF). The novel aspects of this communication are the systematization of the BGF concept, the application of BGF to combinatorial chemistry, and the high-throughput nature of the identification technique. The identification of the active component in a well mixture is an essential step for subsequent resynthesis or isolation of the active component(s) or for removal of intractable wells from further consideration. We believe the technique described is also applicable to any mixture library, provided the expected component (or components) of each well is (are) known. Example mixture libraries would include collections of synthetic chemicals and collections of purified natural products. The mixture need not come from libraries produced using parallel synthesis. The BGF tool described herein allows full utilization of highly diverse combinatorial libraries, thereby obviating costly up-front purification or extensive prescreening characterization efforts.

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