In Silico Mutagenesis and Docking Study of <i>Ralstonia solanacearum</i> RSL Lectin: Performance of Docking Software To Predict Saccharide Binding

In this study, in silico mutagenesis and docking in <i>Ralstonia solanacearum</i> lectin (RSL) were carried out, and the ability of several docking software programs to calculate binding affinity was evaluated. In silico mutation of six amino acid residues (Agr17, Glu28, Gly39, Ala40, Trp76, and Trp81) was done, and a total of 114 in silico mutants of RSL were docked with Me-α-l-fucoside. Our results show that polar residues Arg17 and Glu28, as well as nonpolar amino acids Trp76 and Trp81, are crucial for binding. Gly39 may also influence ligand binding because any mutations at this position lead to a change in the binding pocket shape. The Ala40 residue was found to be the most interesting residue for mutagenesis and can affect the selectivity and/or affinity. In general, the docking software used performs better for high affinity binders and fails to place the binding affinities in the correct order

Engineering of PA-IIL lectin from – Unravelling the role of the specificity loop for sugar preference-0

<p><b>Copyright information:</b></p><p>Taken from "Engineering of PA-IIL lectin from – Unravelling the role of the specificity loop for sugar preference"</p><p>http://www.biomedcentral.com/1472-6807/7/36</p><p>BMC Structural Biology 2007;7():36-36.</p><p>Published online 1 Jun 2007</p><p>PMCID:PMC1903359.</p><p></p>ht brown. Interactions responsible for sugar preference are in yellow, newly created hydrogen bonds are in blue. Figure clearly demonstrates different orientation of O6 of methyl mannoside

Engineering of PA-IIL lectin from – Unravelling the role of the specificity loop for sugar preference-3

<p><b>Copyright information:</b></p><p>Taken from "Engineering of PA-IIL lectin from – Unravelling the role of the specificity loop for sugar preference"</p><p>http://www.biomedcentral.com/1472-6807/7/36</p><p>BMC Structural Biology 2007;7():36-36.</p><p>Published online 1 Jun 2007</p><p>PMCID:PMC1903359.</p><p></p>uffer (pH = 7.5) with 30 μM CaCl. A) Data obtained from 29 automatic injections (10 μL) of Me-α-Man each into the S23A-containing cell. B)Plot of the total heat released as a function of ligand/protein molar ratio for the titration shown in panel A. The solid represents the best least-squares fit for the obtained data

Engineering of PA-IIL lectin from – Unravelling the role of the specificity loop for sugar preference-4

<p><b>Copyright information:</b></p><p>Taken from "Engineering of PA-IIL lectin from – Unravelling the role of the specificity loop for sugar preference"</p><p>http://www.biomedcentral.com/1472-6807/7/36</p><p>BMC Structural Biology 2007;7():36-36.</p><p>Published online 1 Jun 2007</p><p>PMCID:PMC1903359.</p><p></p>and PA-IIL wild type (red) by affinity chromatography on Mannose agarose column (HR 10/10). Loading buffer: 20 mM Tris/HCl, 100 mM NaCl, 100 μM CaCl, pH 7.5; Elution buffer: 20 mM Tris/HCl, 100 mM NaCl, 100 μM CaCl, 0.1 M D-mannose, pH 7.5; Sample: cytoplasmic soluble protein fractions