Innovative technologies for combinatorial chemistry and automated synthesis make possible the synthesis of large collections of compounds as potential sources of lead structures in medicinal chemistry. While the synthesis, purification, and biological screening of combinatorial libraries can be performed automatically, purity control and structure verification remain bottlenecks. Insufficient purity or ambiguous structures of screened samples hinder the exploitation of structure ± activity relationships, which are critical elements for the further design of libraries. The HPLC, MS, and liquid chromatography mass spectrometry (LC-MS) techniques are generally accepted as the most appropriate means of characterization. [1] These analytical methods are fast and easy to automate, but they do not provide sufficient structural and quantitative data on the desired product. The existing automated methods based on 13 C and 1 H NMR spectroscopy [2] are not routinely applied due to the intrinsic low sensitivity of 13 C NMR spectroscopy and the lack of reliable proton-based automated structure verification methods. We report here a novel approach for the automated structure verification of compound libraries by using the experimental data from 2D
[1] a) G.