figshare
Browse
tbsd_a_948070_sm1105.doc (5.59 MB)

Hierarchical sampling for metastable conformers determines biomolecular recognition: the case of malectin and diglucosylated N-glycan interactions

Download (0 kB)
Version 2 2015-03-22, 13:02
Version 1 2015-03-22, 13:02
journal contribution
posted on 2015-03-22, 13:02 authored by Ashalatha Sreshty Mamidi, Avadhesha Surolia

Structural information over the entire course of binding interactions based on the analyses of energy landscapes is described, which provides a framework to understand the events involved during biomolecular recognition. Conformational dynamics of malectin’s exquisite selectivity for diglucosylated N-glycan (Dig-N-glycan), a highly flexible oligosaccharide comprising of numerous dihedral torsion angles, are described as an example. For this purpose, a novel approach based on hierarchical sampling for acquiring metastable molecular conformations constituting low-energy minima for understanding the structural features involved in a biologic recognition is proposed. For this purpose, four variants of principal component analysis were employed recursively in both Cartesian space and dihedral angles space that are characterized by free energy landscapes to select the most stable conformational substates. Subsequently, k-means clustering algorithm was implemented for geometric separation of the major native state to acquire a final ensemble of metastable conformers. A comparison of malectin complexes was then performed to characterize their conformational properties. Analyses of stereochemical metrics and other concerted binding events revealed surface complementarity, cooperative and bidentate hydrogen bonds, water-mediated hydrogen bonds, carbohydrate–aromatic interactions including CH–π and stacking interactions involved in this recognition. Additionally, a striking structural transition from loop to β-strands in malectin CRD upon specific binding to Dig-N-glycan is observed. The interplay of the above-mentioned binding events in malectin and Dig-N-glycan supports an extended conformational selection model as the underlying binding mechanism.

History