Podrobný výpis o publikaci

@proceedings{58326,
   author = {Biriukov, Denys and Miguel, Riopedre Fernández and Hector, MartinezandSeara},
   booktitle = {GGMM 2023 – Young Modellers Conference},
   keywords = {glycosaminglycans; drug design; molecular dynamics simulations},
   language = {eng},
   title = {Model Sugars Right: Improved Interactions of Glycans in All-Atom Molecular Dynamics Simulations},
   url = {https://ggmm2023.sciencesconf.org/},
   year = {2023}
}

TY  - CONF
ID  - 58326
AU  - Biriukov, Denys - Miguel, Riopedre Fernández - Hector, Martinez-Seara
PY  - 2023
TI  - Model Sugars Right: Improved Interactions of Glycans in All-Atom Molecular Dynamics Simulations
KW  - glycosaminglycans
KW  - drug design
KW  - molecular dynamics simulations
UR  - https://ggmm2023.sciencesconf.org/
N2  - Glycans are ubiquitously present in various organisms and tissues, particularly in the cellular environment of mammals and bacteria. They naturally occur as building blocks in larger biomolecules, such as glycolipids and glycoproteins, and also constitute huge polysaccharides called glycosaminoglycans. Glycosaminoglycans (GAGs), negatively charged sugar polymers located above the cell membrane, form the scaffold of the extracellular matrix. Due to numerous carboxyl and sulfonate groups present along polysaccharide chains, the biological function and binding affinities of GAGs are presumably closely connected to electrostatic interactions with other biomolecules present in the extracellular space, such as ions, peptides, proteins, and lipids. Moreover, given the high occurrence of GAGs and glycans in general, novel drugs can be specifically designed to target unique glycan sequences of pathogens. Molecular dynamics (MD) simulations are an excellent tool to rationalize the molecular mechanisms of how glycans recognize other molecules, particularly via mostly uncharacterized sulfation-specific interactions. However, most all-atom MD force fields are known to suffer from the inconsistent description of electrostatic interactions due to missing electronic polarizability. This work summarizes our recent efforts to improve MD models of glycans using the “charge-scaling” approach, which accounts for the electronic polarization in a mean-field way1. We first compared available MD force fields for glycans and functional groups common for GAGs and elucidated their main problems. Then, we developed implicitly polarizable, charge-scaled models that outperform other force fields in the description of electrostatic interactions avoiding unphysical overbinding and overestimated contact ion pairing. Finally, using newly derived models, we investigated sugar-ion and sugar-peptide interactions as exemplifying electrostatic interactions. On the one hand, we revealed that short arginine-containing peptide sequences have a higher affinity for hyaluronan (the only non-sulfated GAG) compared to lysine-containing peptides, in agreement with the NMR experiments2. On the other hand, we showed that solvent-shared ion pairing is the dominant binding mode of calcium cations to sulfonates, the prevailing functional group of sulfated GAGs, which was supported by ab initio molecular dynamics simulations. Our results highlight that currently available MD force fields for glycans can be notably improved, especially if electrostatic interactions are of interest. Such improvement can be achieved using the bottom-up approach when the principal building blocks are optimized first, and then large-scale biosimulations involving glycan-containing molecules are carried out. The accurate simulation models for glycans are vital for basic research and potential medical applications, including designing novel antibacterial and antiviral therapeutics.
ER  - 

BIRIUKOV, Denys, Riopedre Fernández MIGUEL a Martinez-Seara HECTOR. Model Sugars Right: Improved Interactions of Glycans in All-Atom Molecular Dynamics Simulations. In \textit{GGMM 2023 – Young Modellers Conference}. 2023.