Mikhail Elyashberg

Prof. Mikhail Elyashberg

Advanced Chemistry Development, Moscow, Russia

Research Focus & Metrics

Academic Career Length

24Years (2003-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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16 November 2020 in Magnetic Resonance in Chemistry
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Journal Article
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Mikhail ElyashbergMikhail Elyashberg
Mikhail Elyashberg
DADimitris Argyropoulos
Dimitris Argyropoulos
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.


17 March 2009 in Journal of Cheminformatics
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Journal Article
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Mikhail ElyashbergMikhail Elyashberg
Mikhail Elyashberg
KBKirill Blinov
Kirill Blinov
SMSergey Molodtsov
Sergey Molodtsov
YSYegor Smurnyy
Yegor Smurnyy
Antony J. WilliamsAntony J. Williams
Antony J. Williams
TCTatiana Churanova
Tatiana Churanova
This article coincides with the 40 year anniversary of the first published works devoted to the creation of algorithms for computer-aided structure elucidation (CASE). The general principles on which CASE methods are based will be reviewed and the present state of the art in this field will be described using, as an example, the expert system Structure Elucidator.

9 January 2020 in Magnetic Resonance in Chemistry
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Journal Article
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ABAlexei Buevich
Alexei Buevich
Mikhail ElyashbergMikhail Elyashberg
Mikhail Elyashberg

9 February 2012 in Journal of Cheminformatics
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Journal Article
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AMArvin Moser
Arvin Moser
Mikhail ElyashbergMikhail Elyashberg
Mikhail Elyashberg
Antony J. WilliamsAntony J. Williams
Antony J. Williams
KBKirill A Blinov
Kirill A Blinov
JDJoseph C DiMartino
Joseph C DiMartino
One of the largest challenges in chemistry today remains that of efficiently mining through vast amounts of data in order to elucidate the chemical structure for an unknown compound. The elucidated candidate compound must be fully consistent with the data and any other competing candidates efficiently eliminated without doubt by using additional data if necessary. It has become increasingly necessary to incorporate an in silico structure generation and verification tool to facilitate this elucidation process. An effective structure elucidation software technology aims to mimic the skills of a human in interpreting the complex nature of spectral data while producing a solution within a reasonable amount of time. This type of software is known as computer-assisted structure elucidation or CASE software. A systematic trial of the ACD/Structure Elucidator CASE software was conducted over an extended period of time by analysing a set of single and double-blind trials submitted by a global audience of scientists. The purpose of the blind trials was to reduce subjective bias. Double-blind trials comprised of data where the candidate compound was unknown to both the submitting scientist and the analyst. The level of expertise of the submitting scientist ranged from novice to expert structure elucidation specialists with experience in pharmaceutical, industrial, government and academic environments.

1 November 2021 in Molecules
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Journal Article
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Mikhail ElyashbergMikhail Elyashberg
Mikhail Elyashberg
Antony J. WilliamsAntony J. Williams
Antony J. Williams
The first methods associated with the Computer-Assisted Structure Elucidation (CASE) of small molecules were published over fifty years ago when spectroscopy and computer science were both in their infancy. The incredible leaps in both areas of technology could not have been envisaged at that time, but both have enabled CASE expert systems to achieve performance levels that in their present state can outperform many scientists in terms of speed to solution. The computer-assisted analysis of enormous matrices of data exemplified 1D and 2D high-resolution NMR spectroscopy datasets can easily solve what just a few years ago would have been deemed to be complex structures. While not a panacea, the application of such tools can provide support to even the most skilled spectroscopist. By this point the structures of a great number of molecular skeletons, including hundreds of complex natural products, have been elucidated using such programs. At this juncture, the expert system ACD/Structure Elucidator is likely the most advanced CASE system available and, being a commercial software product, is installed and used in many organizations. This article will provide an overview of the research and development required to pursue the lofty goals set almost two decades ago to facilitate highly automated approaches to solving complex structures from analytical spectroscopy data, using NMR as the primary data-type.