Engineering the Pseudomonas aeruginosa II lectin: designing mutants with changed affinity and specificity
Language English Country Netherlands Media print-electronic
Document type Journal Article, Research Support, Non-U.S. Gov't
- MeSH
- Adhesins, Bacterial chemistry genetics metabolism MeSH
- Computer-Aided Design MeSH
- Lectins chemistry genetics metabolism MeSH
- Carbohydrate Metabolism MeSH
- Mutation MeSH
- Mutagenesis * MeSH
- Computer Simulation MeSH
- Pseudomonas aeruginosa chemistry genetics metabolism MeSH
- Molecular Dynamics Simulation MeSH
- Molecular Docking Simulation MeSH
- Thermodynamics MeSH
- Binding Sites MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Names of Substances
- adhesin, Pseudomonas MeSH Browser
- Adhesins, Bacterial MeSH
- Lectins MeSH
This article focuses on designing mutations of the PA-IIL lectin from Pseudomonas aeruginosa that lead to change in specificity. Following the previous results revealing the importance of the amino acid triad 22-23-24 (so-called specificity-binding loop), saturation in silico mutagenesis was performed, with the intent of finding mutations that increase the lectin's affinity and modify its specificity. For that purpose, a combination of docking, molecular dynamics and binding free energy calculation was used. The combination of methods revealed mutations that changed the performance of the wild-type lectin and its mutants to their preferred partners. The mutation at position 22 resulted in 85% in inactivation of the binding site, and the mutation at 23 did not have strong effects thanks to the side chain being pointed away from the binding site. Molecular dynamics simulations followed by binding free energy calculation were performed on mutants with promising results from docking, and also at those where the amino acid at position 24 was replaced for bulkier or longer polar chain. The key mutants were also prepared in vitro and their binding properties determined by isothermal titration calorimetry. Combination of the used methods proved to be able to predict changes in the lectin performance and helped in explaining the data observed experimentally.
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