Literature DB >> 20574564

Population distribution of flexible molecules from maximum entropy analysis using different priors as background information: application to the Φ, Ψ-conformational space of the α-(1-->2)-linked mannose disaccharide present in N- and O-linked glycoproteins.

Elin Säwén1, Tariq Massad, Clas Landersjö, Peter Damberg, Göran Widmalm.   

Abstract

The conformational space available to the flexible molecule α-D-Manp-(1-->2)-α-D-Manp-OMe, a model for the α-(1-->2)-linked mannose disaccharide in N- or O-linked glycoproteins, is determined using experimental data and molecular simulation combined with a maximum entropy approach that leads to a converged population distribution utilizing different input information. A database survey of the Protein Data Bank where structures having the constituent disaccharide were retrieved resulted in an ensemble with >200 structures. Subsequent filtering removed erroneous structures and gave the database (DB) ensemble having three classes of mannose-containing compounds, viz., N- and O-linked structures, and ligands to proteins. A molecular dynamics (MD) simulation of the disaccharide revealed a two-state equilibrium with a major and a minor conformational state, i.e., the MD ensemble. These two different conformation ensembles of the disaccharide were compared to measured experimental spectroscopic data for the molecule in water solution. However, neither of the two populations were compatible with experimental data from optical rotation, NMR (1)H,(1)H cross-relaxation rates as well as homo- and heteronuclear (3)J couplings. The conformational distributions were subsequently used as background information to generate priors that were used in a maximum entropy analysis. The resulting posteriors, i.e., the population distributions after the application of the maximum entropy analysis, still showed notable deviations that were not anticipated based on the prior information. Therefore, reparameterization of homo- and heteronuclear Karplus relationships for the glycosidic torsion angles Φ and Ψ were carried out in which the importance of electronegative substituents on the coupling pathway was deemed essential resulting in four derived equations, two (3)J(COCC) and two (3)J(COCH) being different for the Φ and Ψ torsions, respectively. These Karplus relationships are denoted JCX/SU09. Reapplication of the maximum entropy analysis gave excellent agreement between the MD- and DB-posteriors. The information entropies show that the current reparametrization of the Karplus relationships constitutes a significant improvement. The Φ(H) torsion angle of the disaccharide is governed by the exo-anomeric effect and for the dominating conformation Φ(H) = -40 degrees and Ψ(H) = 33 degrees. The minor conformational state has a negative Ψ(H) torsion angle; the relative populations of the major and the minor states are approximately 3 : 1. It is anticipated that application of the methodology will be useful to flexible molecules ranging from small organic molecules to large biomolecules.

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Year:  2010        PMID: 20574564     DOI: 10.1039/c003958f

Source DB:  PubMed          Journal:  Org Biomol Chem        ISSN: 1477-0520            Impact factor:   3.876


  12 in total

1.  Exploiting Uniformly 13C-Labeled Carbohydrates for Probing Carbohydrate-Protein Interactions by NMR Spectroscopy.

Authors:  Gustav Nestor; Taigh Anderson; Stefan Oscarson; Angela M Gronenborn
Journal:  J Am Chem Soc       Date:  2017-04-21       Impact factor: 15.419

2.  Synthesis and O-Glycosidic Linkage Conformational Analysis of 13C-Labeled Oligosaccharide Fragments of an Antifreeze Glycolipid.

Authors:  Wenhui Zhang; Reagan Meredith; Mi-Kyung Yoon; Xiaocong Wang; Robert J Woods; Ian Carmichael; Anthony S Serianni
Journal:  J Org Chem       Date:  2019-01-29       Impact factor: 4.354

3.  Delineating the conformational flexibility of trisaccharides from NMR spectroscopy experiments and computer simulations.

Authors:  Mingjun Yang; Thibault Angles d'Ortoli; Elin Säwén; Madhurima Jana; Göran Widmalm; Alexander D MacKerell
Journal:  Phys Chem Chem Phys       Date:  2016-06-27       Impact factor: 3.676

4.  Conformational properties of methyl β-maltoside and methyl α- and β-cellobioside disaccharides.

Authors:  Elizabeth Hatcher; Elin Säwén; Göran Widmalm; Alexander D MacKerell
Journal:  J Phys Chem B       Date:  2010-12-15       Impact factor: 2.991

5.  Overexpression of a homogeneous oligosaccharide with 13C labeling by genetically engineered yeast strain.

Authors:  Yukiko Kamiya; Sayoko Yamamoto; Yasunori Chiba; Yoshifumi Jigami; Koichi Kato
Journal:  J Biomol NMR       Date:  2011-06-23       Impact factor: 2.835

6.  Modeling of Oligosaccharides within Glycoproteins from Free-Energy Landscapes.

Authors:  Aysegül Turupcu; Chris Oostenbrink
Journal:  J Chem Inf Model       Date:  2017-08-30       Impact factor: 4.956

7.  A detailed picture of a protein-carbohydrate hydrogen-bonding network revealed by NMR and MD simulations.

Authors:  Gustav Nestor; Alessandro Ruda; Taigh Anderson; Stefan Oscarson; Göran Widmalm; Angela M Gronenborn
Journal:  Glycobiology       Date:  2021-05-03       Impact factor: 4.313

8.  Glycan fragment database: a database of PDB-based glycan 3D structures.

Authors:  Sunhwan Jo; Wonpil Im
Journal:  Nucleic Acids Res       Date:  2012-10-26       Impact factor: 16.971

9.  Methyl α-l-rhamnosyl-(1→2)[α-l-rhamnosyl-(1→3)]-α-l-rhamnoside penta-hydrate: synchrotron study.

Authors:  Lars Eriksson; Göran Widmalm
Journal:  Acta Crystallogr Sect E Struct Rep Online       Date:  2012-06-27

10.  Conformational properties of α- or β-(1→6)-linked oligosaccharides: Hamiltonian replica exchange MD simulations and NMR experiments.

Authors:  Dhilon S Patel; Robert Pendrill; Sairam S Mallajosyula; Göran Widmalm; Alexander D MacKerell
Journal:  J Phys Chem B       Date:  2014-03-05       Impact factor: 2.991

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