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      Mass Spectrometry-Based Techniques to Elucidate the Sugar Code

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          Abstract

          Cells encode information in the sequence of biopolymers, such as nucleic acids, proteins, and glycans. Although glycans are essential to all living organisms, surprisingly little is known about the “sugar code” and the biological roles of these molecules. The reason glycobiology lags behind its counterparts dealing with nucleic acids and proteins lies in the complexity of carbohydrate structures, which renders their analysis extremely challenging. Building blocks that may differ only in the configuration of a single stereocenter, combined with the vast possibilities to connect monosaccharide units, lead to an immense variety of isomers, which poses a formidable challenge to conventional mass spectrometry. In recent years, however, a combination of innovative ion activation methods, commercialization of ion mobility–mass spectrometry, progress in gas-phase ion spectroscopy, and advances in computational chemistry have led to a revolution in mass spectrometry-based glycan analysis. The present review focuses on the above techniques that expanded the traditional glycomics toolkit and provided spectacular insight into the structure of these fascinating biomolecules. To emphasize the specific challenges associated with them, major classes of mammalian glycans are discussed in separate sections. By doing so, we aim to put the spotlight on the most important element of glycobiology: the glycans themselves.

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          Generalized Gradient Approximation Made Simple

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            A consistent and accurate ab initio parametrization of density functional dispersion correction (DFT-D) for the 94 elements H-Pu.

            The method of dispersion correction as an add-on to standard Kohn-Sham density functional theory (DFT-D) has been refined regarding higher accuracy, broader range of applicability, and less empiricism. The main new ingredients are atom-pairwise specific dispersion coefficients and cutoff radii that are both computed from first principles. The coefficients for new eighth-order dispersion terms are computed using established recursion relations. System (geometry) dependent information is used for the first time in a DFT-D type approach by employing the new concept of fractional coordination numbers (CN). They are used to interpolate between dispersion coefficients of atoms in different chemical environments. The method only requires adjustment of two global parameters for each density functional, is asymptotically exact for a gas of weakly interacting neutral atoms, and easily allows the computation of atomic forces. Three-body nonadditivity terms are considered. The method has been assessed on standard benchmark sets for inter- and intramolecular noncovalent interactions with a particular emphasis on a consistent description of light and heavy element systems. The mean absolute deviations for the S22 benchmark set of noncovalent interactions for 11 standard density functionals decrease by 15%-40% compared to the previous (already accurate) DFT-D version. Spectacular improvements are found for a tripeptide-folding model and all tested metallic systems. The rectification of the long-range behavior and the use of more accurate C(6) coefficients also lead to a much better description of large (infinite) systems as shown for graphene sheets and the adsorption of benzene on an Ag(111) surface. For graphene it is found that the inclusion of three-body terms substantially (by about 10%) weakens the interlayer binding. We propose the revised DFT-D method as a general tool for the computation of the dispersion energy in molecules and solids of any kind with DFT and related (low-cost) electronic structure methods for large systems.
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              Density-functional thermochemistry. III. The role of exact exchange

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                Author and article information

                Journal
                Chem Rev
                Chem Rev
                cr
                chreay
                Chemical Reviews
                American Chemical Society
                0009-2665
                1520-6890
                07 September 2021
                27 April 2022
                : 122
                : 8 , Mass Spectrometry Applications in Structural Biology
                : 7840-7908
                Affiliations
                []Institute of Chemistry and Biochemistry, Freie Universität Berlin , Arnimallee 22, 14195 Berlin, Germany
                []Department of Molecular Physics, Fritz Haber Institute of the Max Planck Society , Faradayweg 4−6, 14195 Berlin, Germany
                Author notes
                Author information
                https://orcid.org/0000-0002-2550-637X
                https://orcid.org/0000-0003-4063-1977
                https://orcid.org/0000-0003-3192-0785
                https://orcid.org/0000-0002-9107-2282
                https://orcid.org/0000-0001-8054-4718
                Article
                10.1021/acs.chemrev.1c00380
                9052437
                34491038
                6d2c5548-5d59-41bb-8080-aa4c7dd88c21
                © 2021 The Authors. Published by American Chemical Society

                Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained ( https://creativecommons.org/licenses/by/4.0/).

                History
                : 03 May 2021
                Funding
                Funded by: Verband der Chemischen Industrie, doi 10.13039/100007215;
                Award ID: NA
                Funded by: Fonds National de la Recherche Luxembourg, doi 10.13039/501100001866;
                Award ID: 13549747
                Funded by: Deutsche Forschungsgemeinschaft, doi 10.13039/501100001659;
                Award ID: SFB 1340
                Funded by: Deutsche Forschungsgemeinschaft, doi 10.13039/501100001659;
                Award ID: FOR 2177
                Funded by: H2020 European Research Council, doi 10.13039/100010663;
                Award ID: ERC-2019-CoG-863934-GlycoSpec
                Funded by: Horizon 2020 Framework Programme, doi 10.13039/100010661;
                Award ID: 899687
                Categories
                Review
                Custom metadata
                cr1c00380
                cr1c00380

                Chemistry
                Chemistry

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