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The first efforts for the development of methods for Computer‐Assisted Structure Elucidation (CASE) were published more than 50 years ago. CASE expert systems based on one‐dimensional (1D) and two‐dimensional (2D) Nuclear Magnetic Resonance (NMR) data have matured considerably by now. The structures of a great number of complex natural products have been elucidated and/or revised using such programs. In this article, we discuss the most likely directions in which CASE will evolve. We act on the premise that a synergistic interaction exists between CASE, new NMR experiments, and methods of computational chemistry, which are continuously being improved. The new developments in NMR experiments (long‐range correlation experiments, pure‐shift methods, coupling constants measurement and prediction, residual dipolar couplings [RDCs]), and residual chemical shift anisotropies [RCSAs], evolution of density functional theory (DFT), and machine learning algorithms will have an influence on CASE systems and vice versa. This is true also for new techniques for chemical analysis (Atomic Force Microscopy [AFM], "crystalline sponge" X‐ray analysis, and micro‐Electron Diffraction [micro‐ED]), which will be used in combination with expert systems. We foresee that CASE will be utilized widely and become a routine tool for NMR spectroscopists and analysts in academic and industrial laboratories. We believe that the "golden age" of CASE is still in the future. [ABSTRACT FROM AUTHOR]

Computer‐assisted structure elucidation (CASE) is the class of expert systems that derives molecular structures primarily from one‐dimensional and two‐dimensional nuclear magnetic resonance data. Contemporary CASE systems, including Advanced Chemistry Development/Structure Elucidator (ACD/SE), consider cross‐peaks in heteronuclear multiple bond coherence (HMBC) and correlation spectroscopy (COSY) spectra as two‐ or three‐bond correlations by default. However, four and more bond correlations (nonstandard correlations [NSCs]) could be present in these spectra too. The indiscriminate addition of NSCs to the CASE computations is prohibitively expensive. To address this problem, the ACD/SE program performs a logical analysis of observed correlations and determines the minimum number of NSCs. Guided by this information, a more efficient fuzzy structure generation (FSG) algorithm is subsequently applied. Until now, the FSG algorithm was utilized without any verification of the reliability of found NSCs. Here, we report a verification method for NSCs based on the relationship between NSCs and J‐couplings computed with high accuracy density functional theory (DFT) methods. We used the example of strychnine to show that 41 (32%) of 8‐Hz HMBC cross‐peaks were NSCs and were consistent with 4–6JCH couplings greater than 0.3 Hz. This cutoff value was largely confirmed by the analysis of NSCs in 11 real‐world natural products elucidated by ACD/SE. Additionally, utilizing the example of the CASE study of cleospinol A, we showed that the DFT‐computed J‐couplings of NSCs can distinctively differentiate the correct structure among six proposed isomers. The proposed approach of NSC verification should further improve the robustness of CASE analysis and can help reveal potential problems with reported experimental data. [ABSTRACT FROM AUTHOR]