ACD/Structure Elucidator: 20 Years in the History of Development

Abstract

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.

Overcoming NMR line broadening of nitrogen containing compounds: A simple solution

“…While the in‐depth analysis of the morpholine ring is not the primary focus of this paper and will not be explored here, the specific J values, along with the comprehensive 1 H, 13 C, and 15 N chemical shifts, are provided in the supporting information (refer to the general signal's assignment strategy and Figures S11–S13 for 1 H, 13 C, and 15 N assignments and Table S2 for J values and chemical shift details). This information could be crucial for assessing the viability of employing computer‐assisted structure elucidation (CASE) technique 39–42 …”

“…This information could be crucial for assessing the viability of employing computer-assisted structure elucidation (CASE) technique. [39][40][41][42] Another example explored was whether this approach could be expanded to the piperazine ring, which holds great significance owing to its frequent occurrence in medicinal chemistry. 43,44 Based on the second example, it seems that the key to the success of this approach is the presence of lone pair of electrons on the nitrogen atom available for protonation.…”

Sherlock—A Free and Open-Source System for the Computer-Assisted Structure Elucidation of Organic Compounds from NMR Data

“…Therefore, fragment data can lead to a noticeable reduction of the candidate list size or give hints to the user who might add complementary structural restrictions manually. [ 4 , 5 , 7 , 8 , 24 , 28 ]…”

“…Together with a given molecular formula (MF) mainly determined by mass spectrometry (MS), the substructures and restrictions derived from 1D and 2D NMR spectra form the cornerstone of structure generation by CASE systems. These constraints and the ones resulting from fragment search shrink the chemical search space that would be otherwise too wide for practical applications [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 ].…”

Drug discovery inspired by bioactive small molecules from nature

“…For example, machine learning software (e.g. ACD/structure elucidator, Mestrelab Mnova) has been used for structure determination and dereplication (Claridge 2009 ; Elyashberg and Williams 2021 ). An AI-based structure prediction tool (DP4-AI) has been also developed to predict metabolite structures as well as MS2DeepScore, a machine learning-based mass spectral similarity-predicting algorithm, to identify metabolites based on clustering analysis (Howarth et al 2020 ; Huber et al 2021 ).…”