Structure Elucidation Of Organic Molecules Research Articles

Crystalline mate for structure elucidation of organic molecules

Crystalline mate for structure elucidation of organic molecules

Residual Dipolar Coupling Based Conformational Analysis Allows the Configurational Assessment of Steroids with up to Eight Stereocenters.

Residual dipolar couplings (RDCs) induced by anisotropic media have been proved as a powerful tool for the structure elucidation of organic molecules in solution in nuclear magnetic resonance (NMR) based analysis. The value of dipolar couplings to solve complex conformational and configurational problems represents indeed an appealing analytical tool for the pharmaceutical industry particularly focusing on the stereochemistry characterization of NCEs since the early phase of the drug development process. In our work, RDCs were used for the conformational and configurational study of synthetic steroids with multiple stereocenters - prednisone and beclomethasone dipropionate (BDP) -. For both molecules the correct relative configuration was identified among all the possible diastereoisomers (32 and 128 respectively) arising from the compounds stereogenic carbons. Only for prednisone the use of additional experimental data (i. e. rOes) was necessary to resolve the right stereochemical structure.

Simplified Procedure for Application of DBE, the Rule of 13 & Nitrogen Rule in Structure Elucidation of Organic Compounds

Abstract: Determination of the exact structure of any compound is extremely critical task. Primarily organic chemistry relies on NMR, IR & Mass spectrometric data. Authors have experienced that introduction of structure elucidation in undergraduate courses and postgraduate courses is helpful for students later in their research career. Based on our experience, this article discusses double bond equivalents, the rule of 13 and the nitrogen rule. We have compared the result of these three rules with real spectroscopic data. This article demonstrates the applicability of double bond equivalents, the rule of 13 and the nitrogen rule in solving compound structures using spectroscopic data. Based on availability of molecular weight or molecular formula, we can predict the possible structure of any organic compound using these concepts. In addition, if we have the spectroscopic data like NMR, IR, Mass spectrometry data and UV spectrophotometry data, we can easily confirm the exact structure. This article will be critical for the all the organic chemist for structure elucidation of organic molecules; however, several spectroscopic data is still required for analyzing the exact structure of any molecule.

Self‐Assembly of Helical Polymers and Oligomers to Create Liquid Crystalline Alignment for Anisotropic NMR Parameters

The measurement of anisotropic residual dipolar couplings (RDCs) parameters for the structure elucidation of organic molecules relies on suitable alignment media. Employment of self-assembled liquid crystalline systems to create anisotropic alignment can be an effective way to realize aligned samples and acquire RDCs. This Mini-review highlights the recent advances on amino acid-based helical polymers and supramolecular oligomers forming rigid, rod-like structures that aggregate into ordered liquid crystalline phases, including amino acid-based helical polyisocyanides, polyacetylenes, polypeptides, and oligopeptides assembled alignment media. The methodology for the determination of anisotropic liquid crystals is briefly discussed, and a summary of recent research progress in the enantiodifferentiation of helical polymers aligned media is followed. In addition, the self-assembled mechanism of oligopeptides and their RDCs structural analysis are also described.

Database Independent Automated Structure Elucidation of Organic Molecules Based on IR, 1H NMR, 13C NMR, and MS Data.

Herein, we report a computational algorithm that follows a spectroscopist-driven elucidation process of the structure of an organic molecule based on IR, 1H and 13C NMR, and MS tabular data. The algorithm is independent from database searching and is based on a bottom-up approach, building the molecular structure from small structural fragments visible in spectra. It employs an analytical combinatorial approach with a graph search technique to determine the connectivity of structural fragments that is based on the analysis of the NMR spectra, to connect the identified structural fragments into a molecular structure. After the process is completed, the interface lists the compound candidates, which are visualized by the WolframAlpha computational knowledge engine within the interface. The candidates are ranked according to the predefined rules for analyzing the spectral data. The developed elucidator has a user-friendly web interface and is publicly available (http://schmarnica.si).

Structure elucidation capabilities on typical pharmaceutical drugs by new nuclear magnetic resonance technology: a 400 MHz high-temperature superconducting power-driven magnet NMR system

Nuclear magnetic resonance (NMR) is a powerful technique for the structure elucidation of organic molecules and significantly important in the pharmaceutical industry supporting the discovery and development of drug substances or active pharmaceutical ingredients (APIs). Following an initial study and assessment of a prototype NMR instrument with a high-temperature superconducting (HTS) power-driven magnet of 9.4 T (400 MHz for 1H observation) operating with standard commercial electronics and probes, we tested the instrument with three compounds representing typical pharmaceutical drugs. We compared results from two probes and shimstacks with different geometries (broadband fluorine observe (BBFO) with Bruker orthogonal shim system-3 (BOSS3) and Bruker quattro nucleus probe (QNP) with BOSS1 shims) testing standard one-dimensional (1D) NMR experiments including selective excitation experiments, and two-dimensional (2D) homonuclear and heteronuclear experiments for the purposes of evaluating the equipment for structure elucidation capabilities. In our initial study on cinacalcet HCl, only the 1D 1H experiment showed a loss of resolution when using the longer coiled BBFO probe with the BOSS3 shims compared to the shorter coiled QNP probe with BOSS1 shims. The selective excitation experiments using the cinacalcet HCl were successful. Our characterization of 1D (1H, 13C, 19F) and 2D (1H-1H and 1H-13C) NMR experiments for compounds I and II with the two probes and shimstacks indicated no significance differences. Overall, these results are satisfactory with the HTS magnet at the field of 9.4 T for the structural elucidation work of standard pharmaceutical compounds. This new technology has the advantage of being able to locate the HTS NMR magnet system in any chemistry or analytical laboratory where the samples are produced, facilitating rapid analysis with minor needs from the facilities and without cryogenic liquids.

Molecular structure from a single NMR supersequence.

New NOAH supersequences (NMR by Ordered Acquisition using 1H-detection) are introduced that allow fast structure elucidation of organic molecules from a single measurement. The application of the proposed NOAH-3 BSC and NOAH-4 BSCN experiments, combining two new modules (ZZ-HMBC (B) and ASAP-COSY (C)) with multiplicity-edited HSQC (S) and NOESY (N), is exemplified here through their use in computer-assisted structure elucidation.

ISpec: A Web-Based Activity for Spectroscopy Teaching

Students’ skills in structure elucidation of organic molecules are developed by training them to understand advanced spectroscopic measurements and elucidate structures of small organic molecules from mass spectrometry (MS) and infrared (IR), ultraviolet (UV), and 1H and 13C nuclear magnetic resonance (NMR) spectroscopic data. The present work puts a specific focus on developing student skills to ensure that the students (i) are aware of the resources involved in obtaining the spectral data and (ii) obtain the skills necessary to handle spectra which have not been processed by experts, to better reflect the use of spectroscopic techniques in their later work life. This is achieved through the web-based spectroscopy activity iSpec, in which the basic idea is that every action costs resources. The cost of a resource is given in the form of resource points (RPs), such that different experimental data can be “purchased” for a number of RPs.

Chemically synthesized and cross-linked PDMS as versatile alignment medium for organic compounds.

A useful procedure for the preparation of chemically synthesized and cross-linked polydimethylsiloxane (PDMS) gels is presented, which does not require β-irradiation for cross-linking. NMR spectra of high quality are obtained, such that even mixtures of compounds exhibiting similar NMR spectra like interconverting stereoisomers can be investigated in the residual dipolar coupling (RDC) approach of organic structure determination.

A comprehensive discussion of HMBC pulse sequences. 2. Some useful variants

AbstractThe classical HMBC experiment, introduced in the first part, has revolutionized NMR spectroscopy for the structural studies of small to medium molecules, and impressive examples for structure elucidation of organic molecules, peptides, or natural products making use of the HMBC experiment have been published in the last 20 years. In the first article, we have explored the mechanisms of the two (2D)‐HMBC pulse sequence and have discussed how the pulse sequence elements cooperate to the observed cross‐peaks, wanted and unwanted. We have seen that further improvement of the 2D‐HMBC pulse sequence can be achieved by properly setting the acquisition and processing parameters. After a short introduction, this second article, with the aid of product operator formalism, will provide a comprehensive description of some useful HMBC pulse sequences. Building from basic principles, the constant‐time HMBC variant, the sensitivity‐enhanced HMBC, and some strategy for rejecting unwanted 1 JCH signals are explained in detail. © 2012 Wiley Periodicals, Inc. Concepts Magn Reson Part A 40A: 146–169, 2012.

A comprehensive discussion of hmbc pulse sequences, part 1: The classical HMBC

AbstractSince its introduction in 1986, the heteronuclear multiple bond correlation (HMBC) experiment has modernized nuclear magnetic resonance spectroscopy for the structural studies of small to medium molecules. The experiment provides information about which protons are near through bonds (but not directly bonded to) different carbons or to another heteronucleus. This experiment (in conjunction with the heteronuclear single‐quantum coherence experiment) provides significant amount of information about molecular structure, as the long‐range proton–carbon or proton–nitrogen correlations can include quaternary carbons or nitrogens, in addition to protonated carbons or nitrogens. Impressive examples for structure elucidation of organic molecules, peptides, or natural products have been published in the last 20 years. After a short introduction into the basic theory, this article will provide a comprehensive and pedagogical description of the classical HMBC pulse sequences, with the aid of product operator formalism. Building from basic principles, low‐pass filtering for rejecting unwanted 1 JCH correlations, and the role of pulsed‐field gradients for coherence transfer pathway selection are explained in detail. This article is intended to be used as a basic coverage for students and researchers seeking a simple theoretical understanding of the fundamental tools of the HMBC experiment. © 2012 Wiley Periodicals, Inc. Concepts Magn Reson Part A 40A: 101–127, 2012.

ChemInform Abstract: Expert Systems for Structure Elucidation of Organic Molecules by Spectral Methods

ChemInform is a weekly Abstracting Service, delivering concise information at a glance that was extracted from about 100 leading journals. To access a ChemInform Abstract of an article which was published elsewhere, please select a “Full Text” option. The original article is trackable via the “References” option.

Obituary: Claus-Wilhelm von der Lieth (1949–2007)

On November 16, 2007, Dr. rer. nat. Claus-Wilhelm (Willi) von der Lieth died unexpectedly, a victim of cancer, at the age of 58. He was born on June 13, 1949 in Bremervorde, Germany, studied chemistry at the Technical University of Hannover from 1969 to 1977, and received his diploma under Prof. H. Seidel with a thesis entitled Nitrates of metals with valence I and II: preparation and vibrational spectroscopy. Willi then pursued further studies in theoretical chemistry at the University of Heidelberg under Prof. H.-H. Eysel and received his doctoral degree in 1980 with a thesis on Single-crystal Raman bandshape analysis of sodium nitrite: studies of order–disorder phenomena through the interpretation of the relative intensities of the internal vibrations of the nitrite ion. In that same year Willi joined the staff of the German Cancer Research Center (DKFZ) in Heidelberg as a research scientist in the Central Spectroscopy service group initiated by Prof. E. Hecker and began the development of a computer-based spectroscopic information system for NMR, MS, and IR spectra. In 1984 Willi was a Guest Scientist at the University of Lund, Sweden, and worked with Prof. R. E. Carter and Dr. T. Liljefors on the structure elucidation of organic molecules by force-field calculations and the development of software for the generation and display of 3D structures. Upon his return to Heidelberg, Willi introduced the techniques of molecular modeling as a research tool and central service in the DKFZ. From 1986 to 1987, a further sabbatical in Lund was used to learn the techniques of molecular dynamics simulations of peptides and proteins and to pursue several research projects in the field of Computational Chemistry. For the last 20 years Willi headed the Molecular Modeling group within the Central Spectroscopy Dept. at the DKFZ, where he introduced a wide variety of modeling services and open-access software, conducted courses in modeling techniques, collaborated with many diverse research groups, and organized the development of sophisticated 3D structure and spectroscopy data banks as well as Internet-based educational and research applications in Glycoconj J (2008) 25:189–190 DOI 10.1007/s10719-008-9103-2

Fuzzy Structure Generation: A New Efficient Tool for Computer-Aided Structure Elucidation (CASE)

Contemporary Computer-Aided Structure Elucidation (CASE) systems are heavily based on the utilization of 2D NMR spectra. The utilization of HMBC/GHMBC and COSY/GCOSY correlations generally assumes that these correlations result from (2-3)JCH and (2-3)JHH spin-spin couplings, respectively, and consequently these values are used as the default setting in these systems. Our previous studies1,2 have shown that about half of the problems studied actually contain some correlations of 4-6 bonds, so-called "nonstandard" correlations. In such cases the initial 2D NMR data are contradictory, and the correct solution is therefore not directly attainable. Unfortunately nonstandard correlations and the number of intervening bonds usually cannot be identified experimentally. In this work we suggest a new approach that we term Fuzzy Structure Generation. This allows the solution of structural problems whose 2D NMR data contain an unknown number of nonstandard correlations having different and unknown lengths. Suggested methods for the application of Fuzzy Structure Generation are described, and their application is illustrated by a series of real-world examples. We conclude that Fuzzy Structure Generation is efficient, and there is no real alternative at present in terms of a universal practical method for the structure elucidation of organic molecules from 2D NMR data.

Using Neural Networks for 13C NMR Chemical Shift Prediction–Comparison with Traditional Methods

Interpretation of 13C chemical shifts is essential for structure elucidation of organic molecules by NMR. In this article, we present an improved neural network approach and compare its performance to that of commonly used approaches. Specifically, our recently proposed neural network ( J. Chem. Inf. Comput. Sci. 2000, 40, 1169–1176) is improved by introducing an extended hybrid numerical description of the carbon atom environment, resulting in a standard deviation (std. dev.) of 2.4 ppm for an independent test data set of ∼42,500 carbons. Thus, this neural network allows fast and accurate 13C NMR chemical shift prediction without the necessity of access to molecule or fragment databases. For an unbiased test dataset containing 100 organic structures the accuracy of the improved neural network was compared to that of a prediction method based on the HOSE code ( hierarchically ordered spherical description of environment) using S PECI NFO. The results show the neural network predictions to be of quality (std. dev.=2.7 ppm) comparable to that of the HOSE code prediction (std. dev.=2.6 ppm). Further we compare the neural network predictions to those of a wide variety of other 13C chemical shift prediction tools including incremental methods (C HEMD RAW, S PECT OOL), quantum chemical calculation (G AUSSIAN, C OSMOS), and HOSE code fragment-based prediction (S PECI NFO, ACD/CNMR, P REDICTI T NMR) for the 47 13C-NMR shifts of Taxol, a natural product including many structural features of organic substances. The smallest standard deviations were achieved here with the neural network (1.3 ppm) and S PECI NFO (1.0 ppm).

ChemInform Abstract: Automated Structure Elucidation of Organic Molecules from 13C NMR Spectra Using Genetic Algorithms and Neural Networks.

AbstractChemInform is a weekly Abstracting Service, delivering concise information at a glance that was extracted from about 100 leading journals. To access a ChemInform Abstract of an article which was published elsewhere, please select a “Full Text” option. The original article is trackable via the “References” option.

Genius: a genetic algorithm for automated structure elucidation from 13C NMR spectra.

The automated structure elucidation of organic molecules from experimentally obtained properties is extended by an entirely new approach. A genetic algorithm is implemented that uses molecular constitution structures as individuals. With this approach, the structure of organic molecules can be optimized to meet experimental criteria, if in addition a fast and accurate method for the prediction of the used physical or chemical features is available. This is demonstrated using 13C NMR spectrum as readily obtainable information. By means of artificial neural networks a fast and accurate method for calculating the 13C NMR spectrum of the generated structures exists. The method is implemented and tested successfully for organic molecules with up to 18 non-hydrogen atoms.

Automated structure elucidation of organic molecules from (13)c NMR spectra using genetic algorithms and neural networks.

The automated structure elucidation of organic molecules from experimentally obtained properties is extended by an entirely new approach. A genetic algorithm is implemented that uses molecular constitution structures as individuals. With this approach, the structure of organic molecules can be optimized to meet experimental criteria, if in addition a fast and accurate method for the prediction of the used physical or chemical features is available. This is demonstrated using (13)C NMR spectrum as readily obtainable information. (13)C NMR chemical shift, intensity, and multiplicity information is available from (13)C NMR DEPT spectra. By means of artificial neural networks a fast and accurate method for calculating the (13)C NMR spectrum of the generated structures exists. The approach is limited by the size of the constitutional space that has to be searched and by the accuracy of the shift prediction for the unknown substance. The method is implemented and tested successfully for organic molecules with up to 20 non-hydrogen atoms.

Isomer generators in structure elucidation

Computers have been used in structure elucidation of organic molecules for almost 40 years. Both successes and failures are abundant. Some guidelines are given on how to employ and develop structure elucidation software from today's point of view. The usefulness of some methods to transform spectral into structural information is discussed.

Methodology of using expert systems for structure elucidation of organic molecules by their spectra

Major axioms underlying structure elucidation of molecules by their characteristic spectral data are considered. The amount of information obtained by solving the problem on structure elucidation of molecules serves as a basis to evaluate the quality of solution. Conditions for computer-aided solution of problems using expert systems (ES) are analyzed. Reasons for incorrect or zero solutions and for inconsistencies leading to negative results are examined. The role of additional information as a necessary condition for correct solution is discussed. On the basis of this analysis, a general strategy for structure elucidation of molecules by their spectra using ES is suggested. The principal idea is to use the iteration method, gradually increasing the rigidity of constraints. Strategies named ARCHEOLOGIST and SCULPTOR are discussed. Examples are given.