Literature DB >> 16906231

Quantifying the role of water in protein-carbohydrate interactions.

Sarah M Tschampel1, Robert J Woods.   

Abstract

Water-mediated interactions play a key role in carbohydrate-lectin binding, where the interactions involve a conserved water that is separated from the bulk solvent and present a bridge between the side chains of the protein and the carbohydrate ligand. To apply quantum mechanical methods to examine the role of conserved waters, we present an analysis in which the relevant carbohydrate atoms are modeled by methanol, and in which the protein is replaced by a limited number of amino acid side chains. Clusters containing a conserved water and a representative amino acid fragment were also examined to determine the influence of amino acid side chains on interaction energies. To quantify the differential binding energies of methanol versus water, quantum mechanical calculations were performed at the B3LYP/6-311++G(3df,3pd)//B3LYP/6-31+G(d) level in which either a methanol molecule was bound to the conserved water (liganded state) or in which a water molecule replaces the methanol (unliganded state). Not surprisingly, the binding of a water to clusters containing charged amino acid side chains was more favorable by 1.55 to 7.23 kcal/mol than that for the binding of a water to the corresponding pure water clusters. In contrast, the binding energy of water to clusters containing polar-uncharged amino acid side chains ranged from 4.35 kcal/mol less favorable to 4.72 kcal/mol more favorable than for binding to the analogous pure water clusters. The overall trend for the binding of methanol versus water, in any of the clusters, favored methanol by an average value of 1.05 kcal/mol. To extend these studies to a complex between a protein (Concanavalin A) and its carbohydrate ligand, a cluster was examined that contained the side chains of three key amino acids, namely asparagine, aspartate, and arginine, as well as a key water molecule, arranged as in the X-ray diffraction structure of Con A. Again, using methanol as a model for the endogenous carbohydrate ligand, energies of -5.94 kcal/mol and -5.70 kcal/mol were obtained for the binding of methanol and water, respectively, to the Con A-water cluster. The extent to which cooperativity enhanced the binding energies has been quantified in terms of nonadditive three-body contributions. In general, the binding of water or methanol to neutral dimers formed cooperative clusters; in contrast, the cooperativity in charged clusters depended on the overall geometry as well as the charge.

Entities:  

Year:  2003        PMID: 16906231      PMCID: PMC1538976          DOI: 10.1021/jp035027u

Source DB:  PubMed          Journal:  J Phys Chem A        ISSN: 1089-5639            Impact factor:   2.781


  16 in total

1.  Quantifying hydrogen bond cooperativity in water: VRT spectroscopy of the water tetramer.

Authors:  J D Cruzan; L B Braly; K Liu; M G Brown; J G Loeser; R J Saykally
Journal:  Science       Date:  1996-01-05       Impact factor: 47.728

2.  High-resolution crystal structure of deoxy hemoglobin complexed with a potent allosteric effector.

Authors:  M K Safo; C M Moure; J C Burnett; G S Joshi; D J Abraham
Journal:  Protein Sci       Date:  2001-05       Impact factor: 6.725

3.  Development of the Colle-Salvetti correlation-energy formula into a functional of the electron density.

Authors: 
Journal:  Phys Rev B Condens Matter       Date:  1988-01-15

4.  Involvement of water in carbohydrate-protein binding.

Authors:  C Clarke; R J Woods; J Gluska; A Cooper; M A Nutley; G J Boons
Journal:  J Am Chem Soc       Date:  2001-12-12       Impact factor: 15.419

5.  Structural bases of lectin-carbohydrate affinities: comparison with protein-folding energetics.

Authors:  E García-Hernández; A Hernández-Arana
Journal:  Protein Sci       Date:  1999-05       Impact factor: 6.725

6.  Carbohydrate-protein recognition: molecular dynamics simulations and free energy analysis of oligosaccharide binding to concanavalin A.

Authors:  R A Bryce; I H Hillier; J H Naismith
Journal:  Biophys J       Date:  2001-09       Impact factor: 4.033

7.  A structure of the complex between concanavalin A and methyl-3,6-di-O-(alpha-D-mannopyranosyl)-alpha-D-mannopyranoside reveals two binding modes.

Authors:  R Loris; D Maes; F Poortmans; L Wyns; J Bouckaert
Journal:  J Biol Chem       Date:  1996-11-29       Impact factor: 5.157

8.  Refined structure of concanavalin A complexed with methyl alpha-D-mannopyranoside at 2.0 A resolution and comparison with the saccharide-free structure.

Authors:  J H Naismith; C Emmerich; J Habash; S J Harrop; J R Helliwell; W N Hunter; J Raftery; A J Kalb; J Yariv
Journal:  Acta Crystallogr D Biol Crystallogr       Date:  1994-11-01

9.  Thermodynamics of monosaccharide binding to concanavalin A, pea (Pisum sativum) lectin, and lentil (Lens culinaris) lectin.

Authors:  F P Schwarz; K D Puri; R G Bhat; A Surolia
Journal:  J Biol Chem       Date:  1993-04-15       Impact factor: 5.157

10.  Structural basis of trimannoside recognition by concanavalin A.

Authors:  J H Naismith; R A Field
Journal:  J Biol Chem       Date:  1996-01-12       Impact factor: 5.157

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  5 in total

1.  TIP5P-Consistent Treatment of Electrostatics for Biomolecular Simulations.

Authors:  Sarah M Tschampel; Michael R Kennerty; Robert J Woods
Journal:  J Chem Theory Comput       Date:  2007-09-01       Impact factor: 6.006

2.  Structure and binding analysis of Polyporus squamosus lectin in complex with the Neu5Ac{alpha}2-6Gal{beta}1-4GlcNAc human-type influenza receptor.

Authors:  Renuka Kadirvelraj; Oliver C Grant; Irwin J Goldstein; Harry C Winter; Hiroaki Tateno; Elisa Fadda; Robert J Woods
Journal:  Glycobiology       Date:  2011-03-24       Impact factor: 4.313

3.  Binding energies of water to lithiated valine: formation of solution-phase structure in vacuo.

Authors:  Andrew S Lemoff; Evan R Williams
Journal:  J Am Soc Mass Spectrom       Date:  2004-07       Impact factor: 3.109

4.  Development and Evaluation of GlycanDock: A Protein-Glycoligand Docking Refinement Algorithm in Rosetta.

Authors:  Morgan L Nance; Jason W Labonte; Jared Adolf-Bryfogle; Jeffrey J Gray
Journal:  J Phys Chem B       Date:  2021-06-16       Impact factor: 2.991

5.  SCOWLP update: 3D classification of protein-protein, -peptide, -saccharide and -nucleic acid interactions, and structure-based binding inferences across folds.

Authors:  Joan Teyra; Sergey A Samsonov; Sven Schreiber; M Teresa Pisabarro
Journal:  BMC Bioinformatics       Date:  2011-10-13       Impact factor: 3.169

  5 in total

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