Within the project "Computational analysis of protein-glycosaminoglycan interactions" we model protein-glycosaminoglycan (GAG) interactions using such computational techniques as molecular docking, molecular dynamics (MD), quantum chemistry (QM). Our goal is to contribute to the general understanding of protein-GAG molecular recognition and conformational properties GAG molecules, to develop appropriate computational strategies to treat these systems more effectively, to assist and complement the experimental data providing atomic details basis for molecular mechanisms underlying protein-GAG interactions. The data obtained in this project will be useful for theoretical rationale in the further development of novel approaches for tissue regeneration.
Glycosaminoglycans are linear, periodic, anionic polysaccharides playing a key role in the extracellular matrix via interaction with proteins such as growth factors and chemokines and so representing promising targets in artificial matrix engineering for potential applications in regenerative medicine. Computationally, these molecules are challenging due to their high flexibility, importance of the solvent-mediated interactions, sugar ring conformational interconversions, periodicity and binding to the long and flexible positively charged residues on the protein surface. In comparison to other classes of molecules, there is a lack of specific computational approaches to effectively treat protein-GAG systems.
GAG recognition by particular protein targets
We apply molecular docking, MD-based approaches and free binding energy calculations previously successfully used for other protein-GAG systems to systematically and rigorously characterize binding of GAGs of different types, length and sulfation to particular protein targets in order to complement and explain the experimental data (binding specificity, affinity and kinetic parameters) obtained by biochemical assays, surface plasmon resonance and nuclear magnetic resonance and other techniques by our collaborators. At the moment we investigate the following protein targets:
Analysis of phosphorylated GAGs
Using MD-based and QM-based methods we theoretically investigate phosphorylated GAGs, a novel and uncharacterized class of synthetically modified GAGs, which are potential targets for matrix engineering due to the chemical nature of their phosphate groups. Numerous experimental and computational studies indicate the high potential of natural and artificially sulfated GAGs for applications in regenerative medicine by exploiting their interactions with protein targets in ECM. There are several reasons why phosphorylated GAGs can be very interesing for the studies aimed to understand and to control tissue regeneration: phosphates are weak eletrolytes in comparison to sulfates and, therefore, are potentially more efficient in the organization of more complex and variable H-bonding network structures; phosphate groups have very different charge characteristics in comparison to sulfates, and this could be used for regulating of specificity of their interactions with proteins; phosphorylated GAGs can not be substrates for classical GAGs-specific glycosidases, which make their potential applicability substantially different and attractive for biological systems; 31P is a more conventional nucleus for NMR approaches than 33S, which makes analysis of phosphorylated GAGs binding more straightforward in comparison to sulfated GAGs.
Development of new computational strategies to analyze protein-GAG interactions
We develop new protocols and methodologies in order to specifically approach protein-GAG systems. In particular we are working on:
Calibration, testing and modification of docking approaches with the aim to take into account ligand and receptor flexibility as well as solvent, to improve the performance of docking for GAG molecules which is unfeasible for classical docking approaches
Scoring schemes and functions for protein-GAG complexes
Coarse-grained models of GAG molecules
Analysis of allostery in protein-GAG systems
Thermodymics and kinetics description in protein-GAG systems
Analysis of structural information on protein-GAG complexes available in the PDB
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 665778.