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Computer Assisted Structure Elucidation (CASE): Current and future perspectives
Author(s) -
Elyashberg Mikhail,
Argyropoulos Dimitris
Publication year - 2021
Publication title -
magnetic resonance in chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.483
H-Index - 72
eISSN - 1097-458X
pISSN - 0749-1581
DOI - 10.1002/mrc.5115
Subject(s) - chemistry , premise , residual , chemical shift , nanotechnology , computer science , algorithm , epistemology , philosophy , materials science
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.