Unraveling the problems of protein - saccharide interactions via computational chemistry

Z. Kříž¹, J. Adam¹, O. Šulák¹, M. Wimmerová^1,2 , J. Koča^1,3

¹National Centre for Biomolecular Research, Faculty of Science, Masaryk University,

Kamenice 5, 625 00 Brno.

²Institute of Biochemistry, Faculty of Science, Masaryk University, Kamenice 5, 625 00 Brno.

³Institute of Chemistry, Faculty of Science, Masaryk University, Kotlářská 2, 611 37 Brno.

zdenek@chemi.muni.cz

Keywords: Lectin, monosaccharides, Molecular Docking, Scoring function.

Detailed knowledge of interactions between proteins and small molecules is important for understanding of significant processes in organisms. Saccharides and various glycoconjugates play a significant role in many host-pathogen interactions. Lectins are sugar-binding proteins of non-immunoglobulin nature that agglutinate cells or precipitate glycoconjugates. Their specificity is usually defined by the monosaccharides or oligosaccharides that are best at inhibiting the agglutination or precipitation the lectin causes. Lectins are of interest because of their wide variety of properties and potential applications (pharmacology, immunology, cancer therapy, agriculture ...).

Since host carbohydrates have been known for many years to constitute specific attachment sites for pathogen protein receptors, there is a great interest in structure-function studies of bacterial proteins enabling the pathogen attachment to host glycans. However, only a limited number of their complexes with receptors have been characterized by crystallography [1]. The molecular modeling methods can help in the study of the complexes.

The study will be focused on docking of a set of monosaccharides into two different lectins originally from bacteria Pseudomonas aeruginosa (PA-IIL) [2] and Ralstonia solanacearum (RS-20L) using the Dock v. 6.0 program [3]. The best docked structures (using standard scoring function) were scored again using AMBER scoring function with solvation energy based on implicit solvent model. The same structures were also solvated using TIP3P water model and MD simulations have been run. The binding energies were afterwards calculated from the trajectories. There will be shown the differences in calculated binding energies by using different scoring functions and also the effect of solvation energy on the binding energy.

1. Mitchell, E.P., Houles. C., Sudakevitz, D., Wimmerova, M., Gautier, C., Perez, S., Wu, A.M., Gilboa-Garber, N., Imberty, A. Nat. Struct Biol., 9 (2002), 918.

2. Mitchell, E.P., Sabin, Ch., Šnajdrová L., Pokorná M., Perret, S., Gautier, C., Hofr, C., Gilboa-Garber, N., Koča, J., Wimmerová, M. Imberty, A. Proteins, 58, (2005), 735.

3. Lang, T. P., Moustakas, D., Brozell, S., Carrascal, N., Mukherjee, S., Pegg, S., Raha, K., Shivakumar, D., Rizzo, R., Case, D., Shoichet, B., Kuntz, I.: Dock 6.0, University of California, San Francisco, 2006.

Acknowledgements.

This work has been financially supported by Ministry of Education (MSM0021622413 and LC06030) and Grant Agency of Czech Republic (GD204/03/016 and GA303/06/0570).