MOLGEN+, a generator of connectivity isomers and stereoisomers for molecular structure elucidation

Benecke, C.; Grund, R.; Hohberger, R.; Kerber, Adalbert; Laue, Reinhard; Wieland, Th.

doi:10.1016/0003-2670(95)00291-7

Cited by 70 publications

(56 citation statements)

References 4 publications

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“…Researchers then have the option of formulating chemical structures from the filtered (based on accurate mass and isotopic distribution) list of empirical formulae, which would be a laborious task without automated software. Benecke et al [163] have previously developed software, MOLGEN, for the automated generation of all the stereoisomers of a given empirical formula; Kind and Fiehn recently utilized MOLGEN in an in silico evaluation of an empirical formula query against common metabolite and compound databases, and the various databases queried returned 2 to 181 matches for the molecular formula C 15 H 12 O 7 (corresponding to a pentahydroxyflavone) [143]. However, MOLGEN generated 788,000 stereoisomers for the same molecular formula [143], highlighting the difficulties faced when trying to structurally identify a novel biomarker that may have been previously uncharacterized.…”

Section: Targeted Ms/ms Studies and De Novo Structural Elucidationmentioning

confidence: 99%

Future of Liquid Chromatography–Mass Spectrometry in Metabolic Profiling and Metabolomic Studies for Biomarker Discovery

et al. 2007

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SUMMARYThe future utility of liquid chromatography-mass spectrometry (LC-MS) in metabolic profiling and metabolomic studies for biomarker discover will be discussed, beginning with a brief description of the evolution of metabolomics and the utilization of the three most popular analytical platforms in such studies: NMR, GC-MS, and LC-MS. Emphasis is placed on recent developments in highefficiency LC separations, sensitive electrospray ionization approaches, and the benefits to incorporating both in LC-MS-based approaches. The advantages and disadvantages of various quantitative approaches are reviewed, followed by the current LC-MS-based tools available for candidate biomarker characterization and identification. Finally, a brief prediction on the future path of LC-MS-based methods in metabolic profiling and metabolomic studies is given.

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Section: Targeted Ms/ms Studies and De Novo Structural Elucidationmentioning

confidence: 99%

Future of Liquid Chromatography–Mass Spectrometry in Metabolic Profiling and Metabolomic Studies for Biomarker Discovery

et al. 2007

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“…In terms of these notions, the structure generator MOL-GEN (up to version 3.5, see [3]) is able to generate chemical compounds from RC. From version 4.0, cf.…”

Section: Rc C S C I C M Cmentioning

confidence: 99%

Molecules in Silico: The Generation of Structural Formulae and Its Applications

Kerber

Laue

Meringer

et al. 2004

J. Comput. Chem. Jpn.

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In information processing, in combinatorial chemistry, in structure elucidation, and in several other fields of chemistry, the computer-aided generation of all structures (constitutional formulae) within a defined structure space has become increasingly important. In this brief review the mathematical foundations of the classical molecular model and thus of the generation process are outlined, and the current state of structure generation as applied in software developed by the Bayreuth group is discussed.

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“…[3,4] Using the QSPR and QSAR models, we can estimate values of objective variables, y, such as activities or properties from values of explanatory variables or molecular descriptors, X, by modeling relationships between X and y using compounds with known activities or properties, then inputting new data for X into the QSPR and QSAR models. New data for X come from virtual molecular structures created by structure generators [5][6][7][8] . Thus, virtual molecular structures are input into the QSAR or QSPR models, and activities or properties are estimated for each.…”

Section: Introductionmentioning

confidence: 99%

Applicability Domains and Consistent Structure Generation

Kaneko

Funatsu

2016

Molecular Informatics

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In de novo molecular design, quantitative structure-activity relationship (QSAR) and quantitative structure-property relationship (QSPR) models are important to estimate activity and property values, respectively, for virtual molecular structures. To operate QSAR and QSPR models appropriately, applicability domains (ADs) of the models must be defined because estimated values are unreliable for virtual molecular structures that are dissimilar to structures of training compounds. We describe several methods to construct AD models, and then introduce a structure generator to change molecular structures that exist outside ADs to conform to ADs.

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MOLGEN+, a generator of connectivity isomers and stereoisomers for molecular structure elucidation

Cited by 70 publications

References 4 publications

Future of Liquid Chromatography–Mass Spectrometry in Metabolic Profiling and Metabolomic Studies for Biomarker Discovery

Future of Liquid Chromatography–Mass Spectrometry in Metabolic Profiling and Metabolomic Studies for Biomarker Discovery

Molecules in Silico: The Generation of Structural Formulae and Its Applications

Applicability Domains and Consistent Structure Generation

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