Peptide-Conjugated Silver Nanoparticle for Autoantibody Recognition.

In this work, we considered the autoantibodies proposed as putative biomarkers of demyelination taking into account their reactivity towards myelin oligodendrocyte glycoprotein (MOG) and myelin basic protein (MBP). These myelin proteins are among the most commonly researched targets in the immunopathology of demyelinating diseases. In this context, the development of assays for autoantibody detection can contribute as a predictive value for the early diagnosis of demyelinating diseases. Hence, we aimed to address the application of silver nanoparticles (AgNPs) as a sensing device of autoantibodies. AgNPs were synthesized via a chemical reduction method and characterized using atomic force microscopy (AFM), X-ray diffractometry, dynamic light scattering, and UV-visible spectrophotometry. The process of peptide conjugation on the nanoparticles was also analyzed. The autoantibody recognition by the peptide-conjugated AgNPs was evaluated with UV-visible spectrophotometry, atomic force spectroscopy (AFS), and color changing. AgNPs exhibited spherical morphology, low polydispersity, face-centered cubic crystal structure, and an average size of 29.3±3.0 nm. The hydrodynamic diameter variation and AFM showed that the MBP peptide induced greater agglomeration, compared to MOG peptide. The AFS measurements indicated the efficient binding of peptides to the AgNPs maintaining their activity, revealed by typical adhesion force and shapes of curves. The absorption spectrum features were more affected by the interaction with the specific autoantibodies, which also caused a visible color change in suspension providing a qualitative response. We described a preliminary study of MOG- and MBP-conjugated AgNPs which showed to be applicable in the autoantibody recognition. These have promising implication in the searching for biological markers for diagnostic purposes in the demyelination context, in which the nanoscale sensing exploitation is recent.

Immobilization and unbinding investigation of the antigen-antibody complex using theoretical and experimental techniques.

Experimental results for the antibody known as immunoglobulin G - IgG interacting with phenobarbital were obtained via atomic force microscopy (AFM) and thereafter investigated using computer simulation modeling tools. Using molecular dynamics simulation and docking calculations, the energetically stable configurations of an immobilized antibody over a silicon surface were searched. Six stable configurations of the immobilized antibody over the silicon nitride surface covered by linker molecules were found. Although, only three of them (P1, P2, P5) maintained the Fragment antigen binding available for antigen interaction. Therefore, these configurations were equilibrated after reaching 100 ns molecular dynamics trajectory. The average interaction energy between the surface and the immunoglobulin G - IgG antibody in the P1, P2 and P5 configurations were -62.4 ±â€¯2.4 kcal/mol; -54.3 ±â€¯5.7 kcal/mol, and -360.9 ±â€¯4.2 kcal/mol respectively. Phenobarbital was docked within the Fab domain of P1, P2, and P5 immobilized configurations and equilibrated with molecular dynamics for binding energy estimation. Then, steered molecular dynamics was performed to evaluate unbinding energy pathway between phenobarbital and IgG in each of the three-oriented IgG configurations. No significant differences were observed in the rupture force values (EP1 = 591 ±â€¯13 pN, EP2 = 605 ±â€¯18 pN, and EP5 = 610 ±â€¯45 pN). In comparison, the average AFM experimental results were (641.6 ±â€¯363.3 pN). Therefore, it is worth noting that P5 is the configuration with highest protein-surface interaction. Therefore, the force value calculated for the P5 orientation is statistically more favorable and it is the one to be compared to the experimental data. The agreement between experimental and theoretical results indicates a favorable presented for this study opening new perspectives for antigen-antibody evaluation.

Modeling the coverage of an AFM tip by enzymes and its application in nanobiosensors.

A stochastic simulation of adsorption processes was developed to simulate the coverage of an atomic force microscope (AFM) tip with enzymes represented as rigid polyhedrons. From geometric considerations of the enzyme structure and AFM tip, we could estimate the average number of active sites available to interact with substrate molecules in the bulk. The procedure was exploited to determine the interaction force between acetyl-CoA carboxylase enzyme (ACC enzyme) and its substrate diclofop, for which steered molecular dynamics (SMD) was used. The theoretical force of (1.6±0.5) nN per enzyme led to a total force in remarkable agreement with the experimentally measured force with AFM, thus demonstrating the usefulness of the procedure proposed here to assist in the interpretation of nanobiosensors experiments.