Oligomers of Poly(Ethylene Oxide): Molecular Dynamics with a Polarizable Force Field

Structures of Linear Poly(ethylene oxide) Compounds and Potassium Complexes in Dichloromethane

The H-1 NMR spectra of a series of linear poly(ethylene oxides) compounds (POE compounds) were measured in dichloromethane-d2 at 25 degrees C, where the POE compounds (HO-(CH2CH2O-)n-R) were unsubstituted POE, HEOn (R=H, n=3, 4, 6), and alkyl-substituted POE, DEOn (R=C12H25, n=4, 6, 8) and MeEO6 (R=CH3, n=6). All the peaks of H-1 NMR signals were assigned to each methylene proton of POE. The chemical shifts and coupling constant between vicinal protons were evaluated by a complete spin analysis. The spectral changes of POE compounds by the addition of potassium ion were measured at various metal-to-POE ratios. The chemical shift change of each methylene proton by the formation of the complex was evaluated. The downfield shift of methylene protons caused by the complex formation indicates that the ethylene oxide that the ethylene oxide moiety is coordinating to surround the potassium ion in the same manner as the cyclic crown ether complexes. The results of spin lattice relaxation time measurements of DEO6 suggest that all the methylenes of the ethylene oxides are immobilized by the coordination to the metal ion. Thus, it was confirmed that all oxygens of POE are participating in the complex formation.

Synthetic Polymers and Biomembranes. How Do They Interact?: Atomistic Molecular Dynamics Simulation Study of PEO in Contact with a DMPC Lipid Bilayer

The understanding of interactions of poly(ethylene glycol) (PEG) or poly(ethylene oxide) (PEO) with biological interfaces has important technological application in industry and in medicine. In this paper, structural and dynamical properties of PEO at the dimyristoylphospatidylcholine (DMPC) bilayer/water interface have been investigated by molecular dynamics (MD) and steered molecular dynamics (SMD) simulations. The structural properties of a PEO chain in bulk water, at the water/vacuum interface, and in the presence of the membrane were compared with available experimental data. The presence of a barrier for the PEO penetration into the DMPC bilayer has been found. A qualitative estimation of the barrier provided a value equal to approximately 19 kJ/mol, that is, 7 times the value of kT at 310 K.

Development of a polarizable force field for proteins via ab initio quantum chemistry: first generation model and gas phase tests

We present results of developing a methodology suitable for producing molecular mechanics force fields with explicit treatment of electrostatic polarization for proteins and other molecular system of biological interest. The technique allows simulation of realistic-size systems. Employing high-level ab initio data as a target for fitting allows us to avoid the problem of the lack of detailed experimental data. Using the fast and reliable quantum mechanical methods supplies robust fitting data for the resulting parameter sets. As a result, gas-phase many-body effects for dipeptides are captured within the average RMSD of 0.22 kcal/mol from their ab initio values, and conformational energies for the di- and tetrapeptides are reproduced within the average RMSD of 0.43 kcal/mol from their quantum mechanical counterparts. The latter is achieved in part because of application of a novel torsional fitting technique recently developed in our group, which has already been used to greatly improve accuracy of the peptide conformational equilibrium prediction with the OPLS-AA force field.1 Finally, we have employed the newly developed first-generation model in computing gas-phase conformations of real proteins, as well as in molecular dynamics studies of the systems. The results show that, although the overall accuracy is no better than what can be achieved with a fixed-charges model, the methodology produces robust results, permits reasonably low computational cost, and avoids other computational problems typical for polarizable force fields. It can be considered as a solid basis for building a more accurate and complete second-generation model.