Comprehensive characterization of oligosaccharide conformational ensembles with conformer classification by free-energy landscape via reproductive kernel Hilbert space.

Abstract

Oligosaccharides play versatile roles in various biological systems but are difficult to characterize from a structural viewpoint due to their remarkable degrees of freedom in internal motion. Therefore, molecular dynamics simulations have been widely used to delineate the dynamic conformations of oligosaccharides. However, hardly any methods have thus far been available for the comprehensive characterization of simulation-derived conformational ensembles of oligosaccharides. In this research, we attempted to develop a non-linear multivariate analysis by employing a kernel method using two homologous high-mannose-type oligosaccharides composed of ten and eleven residues as model molecules. These oligosaccharides' conformers derived from simulations were mapped into reproductive kernel Hilbert space with a positive definite function in which all required non-redundant variables for describing the oligosaccharide conformations can be treated in a non-biased manner. By applying Gaussian mixture model clustering, the oligosaccharide conformers were successfully classified by different funnels in the free-energy landscape, enabling a systematic comparison of conformational ensembles of the homologous oligosaccharides. The results shed light on the contributions of intraresidue conformational factors such as the hydroxyl group orientation and/or ring puckering state to their global conformational dynamics. Our methodology will open opportunities to explore oligosaccharides' conformational spaces, and more generally, molecules with high degrees of motional freedom.