Semiempirical molecular dynamics is used to study the collision of C60 and C+60. Particles are propagated classically using forces calculated from the modified neglect of differential overlap (MNDO) Hamiltonian. By assigning different collision energies (Ec) and impact parameters (b) to the Buckminster fullerenes (buckyballs), we simulated six collision events: four head on collisions with impact parameter b=0 and collisions energies of 100, 150, 200, and 400 eV, and two collisions with b=1.5 Rb (Rb=buckyball radius) and Ec=100 and 400 eV. The head on collisions show that at 100 eV the two buckyballs scatter off one another and at 200 and 400 eV they fuse, while at 150 eV they either scatter or form a metastable dimer depending on how the simulation is prepared. This barrier is consistent with recent experiments. In addition, we observe tetrahedral bonding in the C+120 structure formed in the 200 eV, b=0 collision, while at 400 eV, b=0 we see large rings and chains of carbon atoms. The off center collisions also display interesting structural features. In the 100 eV b=1.5 Rb collision, the buckyballs graze one another, distorting their cage structure and scattering at an angle relative to their incident velocities. The buckyballs in the 400 eV, b=1.5 Rb collision also scatter, but in contrast to the 100 eV, b=1.5 Rb collision, the individual buckyballs are severely distorted, forming what we refer to as an ‘‘open mouth’’ structure.
Chromatographic and non-chromatographic purification of biopharmaceuticals depend on the interactions between protein molecules and a solid-liquid interface. These interactions are dominated by the protein-surface properties, which are a function of protein sequence, structure, and dynamics. In addition, protein-surface properties are critical for in vivo recognition and activation, thus, purification strategies should strive to preserve structural integrity and retain desired pharmacological efficacy. Other factors such as surface diffusion, pore diffusion, and film mass transfer can impact chromatographic separation and resin design. The key factors that impact non-chromatographic separations (e.g., solubility, ligand affinity, charges and hydrophobic clusters, and molecular dynamics) are readily amenable to computational modeling and can enhance the understanding of protein chromatographic. Previously published studies have used computational methods such as quantitative structure-activity relationship (QSAR) or quantitative structure-property relationship (QSPR) to identify and rank order affinity ligands based on their potential to effectively bind and separate a desired biopharmaceutical from host cell protein (HCP) and other impurities. The challenge in the application of such an approach is to discern key yet subtle differences in ligands and proteins that influence biologics purification. Using a relatively small molecular weight protein (insulin), this research overcame limitations of previous modeling efforts by utilizing atomic level detail for the modeling of protein-ligand interactions, effectively leveraging and extending previous research on drug target discovery. These principles were applied to the purification of different commercially available insulin variants. The ability of these computational models to correlate directionally with empirical observation is demonstrated for several insulin systems over a range of purification challenges including resolution of subtle product variants (amino acid misincorporations). Broader application of this methodology in bioprocess development may enhance and speed the development of a robust purification platform.
Developing a theory for the long time dynamics of polypeptides requires not only a proper choice of the relevant dynamic variables, but also a meaningful definition of friction coefficients for the individual atoms or groups of atoms in the reduced system. We test various aspects of the optimized Rouse–Zimm model for describing the long time rotational dynamics of a peptide fragment. The necessary equilibrium input information is constructed from a 1 ns molecular dynamics simulation for the solvated peptide by using a parallel Cray version of CHARMm, whose new features are described here. The simulations also provide time autocorrelation functions for comparisons with both theoretical predictions and with experiment. Two atomic friction models (van der Waals radii and accessible surface area) are chosen, and tests are made of the applicability of two combining rules for calculating the group friction coefficients. While the rotational dynamics of the peptide is insensitive to the friction models used, the combining rules are found to impact profoundly upon the theoretical descriptions for the behavior of the peptide dynamics for the reduced descriptions with fewer variables. The calculations study the role of the memory functions, neglected in this dynamical theory, and the interatomic hydrodynamic interactions in constructing the group friction coefficients. While the 1 ns trajectory is longer than customarily used for very complex systems, there are nontrivial influences of the duration of the molecular dynamics trajectory on the description of the dynamics.
Molecules, such as conjugated polymers, whose electronic structure is significantly altered by conformational changes can be shown to have cooperative conformational transitions. In an isolated polymer, this long ranged cooperativity can be analyzed by representing the polymer as a one-dimensional gas of simple conformational defects that interact with a nearest-neighbor attraction. For a condensed phase, it is suggested that the same analysis remains valid but that the relevant defects become more complex. The resulting "thermodynamics" of the defects, along with their predicted spatial distribution, have experimental consequences for the UV Ivisible and Raman spectra of conjugated polymers-some aspects of which are discussed.
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