a 2023

Model Sugars Right: Improved Interactions of Glycans in All-Atom Molecular Dynamics Simulations

BIRIUKOV, Denys; Riopedre Fernández MIGUEL a Martinez-Seara HECTOR

Základní údaje

Originální název

Model Sugars Right: Improved Interactions of Glycans in All-Atom Molecular Dynamics Simulations

Název česky

Správný model: Vylepšení interakcí glykanů v simulacích molekulové dynamiky

Autoři

BIRIUKOV, Denys; Riopedre Fernández MIGUEL a Martinez-Seara HECTOR

Vydání

GGMM 2023 – Young Modellers Conference, 2023

Další údaje

Jazyk

angličtina

Typ výsledku

Konferenční abstrakta

Stát vydavatele

Francie

Utajení

není předmětem státního či obchodního tajemství

Odkazy

Organizace

Středoevropský technologický institut – Masarykova univerzita – Repozitář

Klíčová slova česky

glykosaminy; návrh léčiv; simulace molekulové dynamiky

Klíčová slova anglicky

glycosaminglycans; drug design; molecular dynamics simulations

Návaznosti

LX22NPO5103, projekt VaV.
Změněno: 7. 3. 2024 03:59, RNDr. Daniel Jakubík

Anotace

V originále

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.

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