Abstract
While the construction of a dependable force field for performing classical molecular dynamics (MD) simulation is crucial for elucidating the structure and function of biomolecular systems, the attempts to do this for glycans are relatively sparse compared to those for proteins and nucleic acids. Currently, the use of GLYCAM06 force field is the most popular, but there have been a number of concerns about its accuracy in the systematic description of structural changes. In the present work, we focus on the improvement of the GLYCAM06 force field for -d-glucose, a simple and the most abundant monosaccharide molecule, with the aid of machine learning techniques implemented with the TensorFlow library. Following the pre-sampling over a wide range of configuration space generated by MD simulation, the atomic charge and dihedral angle parameters in the GLYCAM06 force field were re-optimized to accurately reproduce the relative energies of -d-glucose obtained by the density functional theory (DFT) calculations according to the structural changes. The validation for the newly proposed force-field parameters was then carried out by verifying that the relative energy errors compared to the DFT value were significantly reduced and that some inconsistencies with experimental (e.g., NMR) results observed in the GLYCAM06 force field were resolved relevantly.
Highlights
We would like to replace the parameters in the GLYCAM06 force field with improved ones step by step, and at least for β-glucose, we have found an improvement over GLYCAM06 from the viewpoint of energy evaluation
The features of this structure are consistent with those of the most stable structure described in the structural analysis report of β-glucose by Alonso et al [33]
The sampling structures obtained using the molecular dynamics (MD) simulations at 300 K and 600 K are shown for the system of C-P puckering coordinates in Figures S2 and S3 in Supplementary Materials (SM)
Summary
X-ray-based crystal structure analysis has been widely used for structural analysis of proteins. As for the glycans attached to proteins, X-ray-based crystal structure analysis shows that (i) glycans are often removed by enzymatic deglycosylation treatment to obtain a single crystal, and (ii) it is difficult to identify their electron density, owing to their heterogeneity and conformational diversity [4]. For these reasons, information about the three-dimensional structure of glycans is sparse, compared with that for proteins
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