Stacking Interactions between Carbohydrate and Protein Quantified by Combination of Theoretical and Experimental Methods

<div><p>Carbohydrate – receptor interactions are an integral part of biological events. They play an important role in many cellular processes, such as cell-cell adhesion, cell differentiation and in-cell signaling. Carbohydrates can interact with a receptor by using several types of intermolecular interactions. One of the most important is the interaction of a carbohydrate's apolar part with aromatic amino acid residues, known as dispersion interaction or CH/π interaction. In the study presented here, we attempted for the first time to quantify how the CH/π interaction contributes to a more general carbohydrate - protein interaction. We used a combined experimental approach, creating single and double point mutants with high level computational methods, and applied both to <em>Ralstonia solanacearum</em> (RSL) lectin complexes with α-l-Me-fucoside. Experimentally measured binding affinities were compared with computed carbohydrate-aromatic amino acid residue interaction energies. Experimental binding affinities for the RSL wild type, phenylalanine and alanine mutants were −8.5, −7.1 and −4.1 kcal.mol⁻¹, respectively. These affinities agree with the computed dispersion interaction energy between carbohydrate and aromatic amino acid residues for RSL wild type and phenylalanine, with values −8.8, −7.9 kcal.mol⁻¹, excluding the alanine mutant where the interaction energy was −0.9 kcal.mol⁻¹. Molecular dynamics simulations show that discrepancy can be caused by creation of a new hydrogen bond between the α-l-Me-fucoside and RSL. Observed results suggest that in this and similar cases the carbohydrate-receptor interaction can be driven mainly by a dispersion interaction.</p> </div

Measured distances between α-l-Me-fucoside carbon atoms and geometric centers of the aromatic parts of residues for the 76^th amino acid.

<p>Values in 2BT9 column represent distances in the crystal structure.</p>[a]<p>Values before geometry optimization.</p

Graphical representation of the α-l-Me-fucoside apolar faces.

<p>We can define two apolar faces for the Me-fucoside. The plane defined by C1, C2 and O5 atoms creates smaller one whereas the plane defined by C3, C4, C5 and C6 atoms creates larger one. This larger apolar face creates stacking interaction with Trp76 residue in RSL lectin.</p

Comparison of the observed water densities from the MD simulation of the wild type RSL and W76A RSL mutant.

<p>The water densities in the 34 ns long molecular dynamic simulations of the wild type RSL (<b>A</b>) and W76A RSL mutant (<b>B</b>) are shown. Detailed analysis of the trajectories show increased water density around the α-L-Me-fucoside moiety in the W76A mutant in position occupied by Trp76 side chain in the wild type lectin complex simulation. This increased water density is highlighted by green circle. The α-L-Me-fucoside is shown in ball and stick representation.</p

Superimposition of the modeled active site structures.

<p>The X-ray structure and the structures of the mutated models' carbons are colored in cyan, optimized BS_W76 model carbons are colored in green, optimized BS_W76F model carbons are colored in violet and optimized BS_W76A model carbons are colored in light brown. Balls represent restrained alpha carbons.</p

Thermodynamics of binding for wild type RSL and its mutants with α-l-Me-fucoside by ITC at 293 K (standard deviations were calculated from three independent measurements).

<p>The <i>E</i>_Int represents calculated interaction energy for a specific binding site model, <i>n</i> stands for stochiometry. Single point alanine mutations clearly show the stoichiometry change.</p>[a]<p>fitted for two independent binding sites, parameters for W31A fixed.</p