Enhanced conformational sampling of carbohydrates by Hamiltonian replica-exchange simulation
Jazyk angličtina Země Velká Británie, Anglie Médium print-electronic
Typ dokumentu časopisecké články, práce podpořená grantem
PubMed
24134878
DOI
10.1093/glycob/cwt093
PII: cwt093
Knihovny.cz E-zdroje
- Klíčová slova
- adaptive biasing force simulations, biasing potential replica-exchange simulation, conformational sampling, molecular dynamics simulation, saccharides,
- MeSH
- antigeny krevních skupin chemie genetika MeSH
- disacharidy chemie genetika MeSH
- konformace sacharidů MeSH
- lidé MeSH
- sekvenční analýza * MeSH
- simulace molekulární dynamiky * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Názvy látek
- antigeny krevních skupin MeSH
- disacharidy MeSH
Knowledge of the structure and conformational flexibility of carbohydrates in an aqueous solvent is important to improving our understanding of how carbohydrates function in biological systems. In this study, we extend a variant of the Hamiltonian replica-exchange molecular dynamics (MD) simulation to improve the conformational sampling of saccharides in an explicit solvent. During the simulations, a biasing potential along the glycosidic-dihedral linkage between the saccharide monomer units in an oligomer is applied at various levels along the replica runs to enable effective transitions between various conformations. One reference replica runs under the control of the original force field. The method was tested on disaccharide structures and further validated on biologically relevant blood group B, Lewis X and Lewis A trisaccharides. The biasing potential-based replica-exchange molecular dynamics (BP-REMD) method provided a significantly improved sampling of relevant conformational states compared with standard continuous MD simulations, with modest computational costs. Thus, the proposed BP-REMD approach adds a new dimension to existing carbohydrate conformational sampling approaches by enhancing conformational sampling in the presence of solvent molecules explicitly at relatively low computational cost.
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