Enhanced Concanavalin A Binding to Preorganized Mannose Nanoarrays in Glycodendrimersomes Revealed Multivalent Interactions.
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ABSTRACT:
SUBMITTER: Yu Kostina N
PROVIDER: S-EPMC8048596 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:A highly efficient cap-exchange approach for preparing compact, dense polyvalent mannose-capped quantum dots (QDs) has been developed. The resulting QDs have been successfully used to probe multivalent interactions of HIV/Ebola receptors DC-SIGN and DC-SIGNR (collectively termed as DC-SIGN/R) using a sensitive, ratiometric Förster resonance energy transfer (FRET) assay. The QD probes specifically bind DC-SIGN, but not its closely related receptor DC-SIGNR, which is further confirmed by its specific blocking of DC-SIGN engagement with the Ebola virus glycoprotein. Tuning the QD surface mannose valency reveals that DC-SIGN binds more efficiently to densely packed mannosides. A FRET-based thermodynamic study reveals that the binding is enthalpy-driven. This work establishes QD FRET as a rapid, sensitive technique for probing structure and thermodynamics of multivalent protein-ligand interactions.
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Project description:A highly efficient cap-exchange approach for preparing compact, dense polyvalent mannose-capped quantum dots (QDs) has been developed. The resulting QDs have been successfully used to probe multivalent interactions of HIV/Ebola receptors DC-SIGN and DC-SIGNR (collectively termed as DC-SIGN/R) using a sensitive, ratiometric Förster resonance energy transfer (FRET) assay. The QD probes specifically bind DC-SIGN, but not its closely related receptor DC-SIGNR, which is further confirmed by its specific blocking of DC-SIGN engagement with the Ebola virus glycoprotein. Tuning the QD surface mannose valency reveals that DC-SIGN binds more efficiently to densely packed mannosides. A FRET-based thermodynamic study reveals that the binding is enthalpy-driven. This work establishes QD FRET as a rapid, sensitive technique for probing structure and thermodynamics of multivalent protein-ligand interactions.
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Project description:Computer modeling of complexation of mono- and oligosaccharide ligands with the main (fourth) carbohydrate-binding domain of the mannose receptor CD206 (CRD4), as well as with the model receptor concanavalin A (ConA), was carried out for the first time, using methods of molecular dynamics and neural network analysis. ConA was shown to be a relevant model of CD206 (CRD4) due to similarity of the structural organization of the binding sites and high correlation of the values of free energies of complexation between the literature data and computer modeling (r > 0.9). Role of the main factors affecting affinity of the ligand–receptor interactions is discussed: the number and nature of carbohydrate residues, presence of Me-group in the O1 position, type of the glycoside bond in dimannose. Complexation of ConA and CD206 with ligands is shown to be energetically caused by electrostatic interactions (E) of the charged residues (Asn, Asp, Arg) with oxygen and hydrogen atoms in carbohydrates; contributions of hydrophobic and van der Waals components is lower. Possibility of the additional stabilization of complexes due to the CH–π stacking interactions of Tyr with the Man plane is discussed. The role of calcium and manganese ions in binding ligands has been studied. The values of free energies of complexation calculated in the course of molecular dynamics simulation correlate with experimental data (published for the model ConA): correlation coefficient r = 0.68. The Pafnucy neural network was trained based on the set of PDBbind2020 ligand–receptor complexes, which significantly increased accuracy of the energy predictions to r = 0.8 and 0.82 for CD206 and ConA receptors, respectively. A model of normalization of the complexation energy values for calculating the relevant values of ΔGbind, Kd is proposed. Based on the developed technique, values of the dissociation constants of a series of CD206 complexes with nine carbohydrate ligands of different structures were determined, which were not previously known. The obtained data open up possibilities for using computer modeling for the development of optimal drug carriers capable of active macrophage targeting, and also determine the limits of applicability of using ConA as a relevant model for studying parameters of the CD206 binding to various carbohydrate ligands. Electronic supplementary material The online version contains supplementary material available at 10.1134/S0006297922010059.
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