title: Computational analysis of interactions in structurally available protein-glycosaminoglycan complexes.
abstract: Glycosaminoglycans represent a class of linear anionic periodic polysaccharides, which play a key role in a variety of biological processes in the extracellular matrix via interactions with their protein targets. Computationally, glycosaminoglycans are very challenging due to their high flexibility, periodicity and electrostatics-driven nature of the interactions with their protein counterparts. In this work, we carry out a detailed computational characterization of the interactions in protein-glycosaminoglycan complexes from the Protein Data Bank (PDB), which are split into two subsets accounting for their intrinsic nature: non-enzymatic-protein-glycosaminoglycan and enzyme-glycosaminoglycan complexes. We apply molecular dynamics to analyze the differences in these two subsets in terms of flexibility, retainment of the native interactions in the simulations, free energy components of binding and contributions of protein residue types to glycosaminoglycan binding. Furthermore, we systematically demonstrate that protein electrostatic potential calculations, previously found to be successful for glycosaminoglycan binding sites prediction for individual systems, are in general very useful for proposing protein surface regions as putative glycosaminoglycan binding sites, which can be further used for local docking calculations with these particular polysaccharides. Finally, the performance of six different docking programs (Autodock 3, Autodock Vina, MOE, eHiTS, FlexX and Glide), some of which proved to perform well for particular protein-glycosaminoglycan complexes in previous work, is evaluated on the complete protein-glycosaminoglycan data set from the PDB. This work contributes to widen our knowledge of protein-glycosaminoglycan molecular recognition and could be useful to steer a choice of the strategies to be applied in theoretical studies of these systems.
authors: Structural Bioinformatics, BIOTEC TU Dresden, Dresden 01307, Germany.
authors: Sergey A
authors: SA
authors: Samsonov
authors: Structural Bioinformatics, BIOTEC TU Dresden, Dresden 01307, Germany.
authors: M Teresa
authors: MT
authors: Pisabarro
mesh_terms: D001665:Binding Sites; D019295:Computational Biology / Q000379:methods*; D030562:Databases, Protein; D006025:Glycosaminoglycans / Q000737:chemistry* / Q000378:metabolism; D007700:Kinetics; D062105:Molecular Docking Simulation; D056004:Molecular Dynamics Simulation; D011485:Protein Binding; D054730:Protein Interaction Domains and Motifs; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism; D055672:Static Electricity; D013816:Thermodynamics
chemical_list: D006025:Glycosaminoglycans; D011506:Proteins
keywords: MM-GBSA; docking; electrostatic potential; molecular dynamics; protein–glycosaminoglycan interactions