Antibody-mediated biorecognition of myelin oligodendrocyte glycoprotein: computational evidence of demyelination-related epitopes.

Antigen-antibody interaction is crucial in autoimmune disease pathogenesis, as multiple sclerosis and neuromyelitis optica. Given that, autoantibodies are essential biomolecules, of which the myelin oligodendrocyte glycoprotein (MOG) can figure as a target. Here we combined Molecular Dynamics (MD), Steered Molecular Dynamics (SMD), and Atomic Force Microscope (AFM) to detail MOG recognition by its specific antibody. The complex model consisted of the MOG external domain interacting with an experimental anti-MOG antibody from the Protein Data Bank (1PKQ). Computational data demonstrated thirteen MOG residues with a robust contribution to the antigen-antibody interaction. Comprising five of the thirteen anchor residues (ASP102, HIS103, SER104, TYR105, and GLN106), the well-known MOG92-106 peptide in complex with the anti-MOG was analysed by AFM and SMD. These analyses evidenced similar force values of 780 pN and 765 pN for computational and experimental MOG92-106 and anti-MOG detachment, respectively. MOG92-106 was responsible for 75% of the total force measured between MOG external domain and anti-MOG, holding the interaction with the antibody. The antigen-antibody binding was confirmed by Surface Plasmon Resonance (SPR) measurements. Combined approaches presented here can conveniently be adjusted to detail novel molecules in diseases research. This can optimize pre-clinical steps, guiding experiments, reducing costs, and animal model usage.

Solvation of sodium octanoate micelles in concentrated urea solution studied by means of molecular dynamics simulations.

The effects of urea on self-assembling remains a challenging topic on surface chemistry, and computational modeling may have a role on the unraveling of the molecular mechanisms underlying these effects. Bearing that in mind, we performed a set of molecular dynamics simulations to assess the effects of urea on the self-assembling properties of sodium octanoate, an anionic surfactant, as compared to the aggregation of the same surfactant in pure water as the solvent. The concentration of free monomers increased 3-fold in the presence of urea, in agreement with the accepted view that urea should increase monomer solubility. Regarding the size distribution of micellar aggregates, the urea solution favored smaller micelles and a narrower distribution. Preferential solvation by either water or urea changed along the surfactant molecules, from urea-rich shells around apolar atoms at the end of the hydrophobic tails to nearly no urea at the polar headgroups. This solvation profile is consistent with two different hypotheses from the literature: on one hand, urea molecules interact directly with apolar atoms from the hydrophobic tails, acting as a surfactant, and on the other hand the presence of urea molecules increases the hydration of polar sites. Another important observation regards the solvent structure, which exhibits a complex composition profile around both water and urea molecules. Although the solvent structure was appreciably different in each case, the free energy calculations for the dissociation of a pair of octanoate molecules pointed to a purely enthalpic free energy loss in urea solution, a finding that does not lend support to the third hypothesis that is often claimed as accounting for the urea effects, namely, that urea disrupts water structure and that this structural change decreases the hydrophobic effect due to an entropy change. The presence of urea had no significant effect on the molecular structure of the surfactant molecules, although it caused chain dynamics to become slower. The overall picture arising from the molecular-scale data extracted from our computational models is somewhat different from the traditional views about the structural and dynamical features of self-assembled surfactant systems, pointing out the need for more studies on other self-organized systems using a realistic model system as a way to achieve a more detailed picture.