User:Fireandice90210

Antibody-Nanoparticle Computational Modeling--Fireandice90210 (talk) 04:36, 11 June 2008 (UTC)

The conjugation of antibodies and nanoparticles with high affinity & specificity through receptor-ligand recognition modes is of paramount importance in the development of vehicles which can be used for diagnosis, treatment of cancer and various other diseases, application of immudiagnostic nano-biosensors etc. The bio-nanocomplex formed by an artificial nanomaterial (nanoliposomes, nanoparticles ) and a biological entity such as an antibody is brought about by the formation of covalent bonds based on their specific chemical and structural properties such as water solubility, biocompatibility, and biodegradability. [5]. There is a requirement of a comprehensive understanding of the relationship of the thermodynamic & kinetic aspects of antibody-membrane association, translational, rotational mobilities of membrane bound antibodies, interactions with the diverse cell surface , circulating molecules and various artificial nanomolecules as well as the conformation. These details are of great importance in the development, application of various nanoscale immunodiagnostic devices. The association of antibodies with cell surfaces is a key molecular event in antibody-mediated immune mechanisms such as phagocytosis, antibody mediated immune dependent cell-mediated cytotoxicity.[6]. The interfacial properties, especially the dynamic, thermodynamic, and mechanical properties, at different spatial and temporal resolutions of these bio-nano systems can be readily investigated with the aid of computer simulations, which consist of studies of interactions of the proteins as well as those of various nanomaterials with organic biological molecules such as proteins, nucleic acids, membrane lipids, and water and of significance importance is the study of the interactions of nanoparticles in the protein binding sites and optimization of the same for improved bio-nano recognition. [4]. Recently it has been noted that there exists certain natural proteins, antibodies, that can recognize specific nanoparticles. For example, a specific antibody from the mouse immune system can specifically recognize derivatized C60 fullerenes with a binding affinity of about 25 nM [5]. From the studies carried out by Noon et al, it is hypothized that the fullerene-binding site is formed at the interface of the light and heavy chains lined with a cluster of shape-complementary hydrophobic amino acid residues. As the covalent modifications of the functionalized fullerenes, occupy only a small fraction of the particle surface area, the largely unoccupied surface would be free to interact with the antibody. Therefore, in order to gain in-depth understanding of the detailed interactions of the nps and the antibody, molecular dynamics simulation is carried out using molecular dynamics simulation; the purpose of our theoretical modeling studies is to be able to identify the energetically favorable binding modes. [4]. For the modeling study, the initial coordinates of the antibody can be made available from the Protein Data Bank (PDB). [5], [7]. The coordinates of the nanoparticle in this case, would be obtained from the AFM, TEM studies carried out at the AMERI and Nano-biotechnology laboratory, FIU, Miami. The CHARMm (Chemistry at HARvard Macromolecular Mechanics) an Unix-based commercialized software using Fortran 77 source codes uses set of force fields for molecular dynamics for simulation and analysis.[3]. The basic assumptions, as a first approximation, during the modeling study would be that the hydrophilic derivatizations do not play a critical role in the predominantly hydrophobic nanomaterial-antibody interactions and that the electronic structure remains undisturbed during the conjugation. The nanoparticle is docked into a suggested binding site from the previously done literature studies.[5]. Polar-hydrogen potential function (PARAM19) and a modified TIP3P water solvent model for the protein is used.[1]. The simulation involves approximately about 300 steps of minimization, using the Steepest Descent and the Newton Raphson method. To reduce the necessary simulation time, a highly efficient method for simulating the localized interactions in the active site of a protein, the stochastic boundary molecular dynamics (SBMD) is used. The reference point for partitioning the system in SBMD was chosen to be near the center of the nanomaterials, which is assumed to be an unifom sphere. The complex nano-bio system can be assumed to be separated into spherical reservoir and reaction zones; the latter is further sub-divided into a reaction region and a buffer region. The atoms in the reaction region are propagated by molecular dynamics, whereas those in the buffer region involve Langevin dynamics are retained using harmonic restoring forces.

References: 1.	http://www.ocms.ox.ac.uk/mirrored/xplor/manual/htmlman/node65.html 2.	Brunger et al. “Trypsinogen-Trypsin Transition: A Molecular Dynamics Study of Induced Conformational Change in the Activation  Domain” 3.	Brooks BR, Bruccoleri RE, Olafson BD, States DJ, Swaminathan S, Karplus M (1983). “CHARMM: A program for macromolecular energy, minimization, and dynamics calculations“. J Comp Chem 4: 187–217. 4.	Noon et al “Molecular dynamics analysis of a buckyball-antibody complex” 5.	Braden et al. “X-ray crystal structure of an anti-Buckminsterfullerene antibody Fab fragment: Biomolecular recognition of C60 “ (2000) Proc. Natl. Acad. Sci. USA 97, 12193-12197 6.	Pisarchick et al. “Binding of a monoclonal antibody and its Fab fragment to supported phospholipid monolayers measured by total internal reflection fluorescence microscopy”. 7.	http://www.rcsb.org/pdb/home/home.do