Simulations crystal structures

Our 2 ns CHARMM simulations of PDT025, lYTB and lAIS (without TFB), and the corresponding free TBPs, serve to reexamine the inferences on the nature and role of TBP dynamics with results from simulations of additional systems that are more completely described (e.g., Miaskiewicz and Omstein did not include the internal water molecules in the TBP structure, while our new calculations do include them [120]). In these new simulations we do not detect evidence for the collapse of the two subdomains of TBP caused by extreme bending. There are indeed oscillations in the distance between the tips of the stirrups of TBP [101] and twisting motions, but these oscillations never acquire such an amplitude as to cause the complete closing of the underside of TBP. This is true for the three free TBP crystal structures simulated as monomers (NP-unpublished results). 

To enable an atomic interpretation of the AFM experiments, we have developed a molecular dynamics technique to simulate these experiments [49], Prom such force simulations rupture models at atomic resolution were derived and checked by comparisons of the computed rupture forces with the experimental ones. In order to facilitate such checks, the simulations have been set up to resemble the AFM experiment in as many details as possible (Fig. 4, bottom) the protein-ligand complex was simulated in atomic detail starting from the crystal structure, water solvent was included within the simulation system to account for solvation effects, the protein was held in place by keeping its center of mass fixed (so that internal motions were not hindered), the cantilever was simulated by use of a harmonic spring potential and, finally, the simulated cantilever was connected to the particular atom of the ligand, to which in the AFM experiment the linker molecule was connected. 

The structure of the metallocene cation energy minimised with the Car-Parrinello method agrees well with the experimentally obtained crystal structures of related complexes. Typical features of the structure as obtained from X-ray diffraction on crystals of very similar neutral complexes (e.g., the dichlorides), such as small differences in distances between C atoms within a cyclopentadienyl (Cp) ring, as well as differences in distances between the C atoms of the Cp ring and the Zr atom, were revealed from the simulations. 

Colloidal crystals . At the end of Section 2.1.4, there is a brief account of regular, crystal-like structures formed spontaneously by two differently sized populations of hard (polymeric) spheres, typically near 0.5 nm in diameter, depositing out of a colloidal solution. Binary superlattices of composition AB2 and ABn are found. Experiment has allowed phase diagrams to be constructed, showing the crystal structures formed for a fixed radius ratio of the two populations but for variable volume fractions in solution of the two populations, and a computer simulation (Eldridge et al. 1995) has been used to examine how nearly theory and experiment match up. The agreement is not bad, but there are some unexpected differences from which lessons were learned. 

If structural information of the protein target is available, e.g., a crystal structure, in silico screening of huge virtual compound libraries can be conducted by the use of docking simulations. Based on identified primary hits, structural variations of the ligand can be evaluated by computational modeling of the ligand-protein complex. 

Molecular-dynamics simulations also showed that spherical gold clusters is stable in the form of FCC crystal structure in a size range of = 13-555 [191]. This is more likely a key factor in developing extremely high catalytic activity on reducible Ti02 as a support material. Thus, it controls the electronic structure of Au nanoparticles (e.g. band gap and BE shift of Au 4f7/2 band) and thereby the catalytic activity. 

There is great interest in the development of methods that allow the identification of a reasonably good structure with which to start the simulation of dense atomistically detailed polymer systems. The problem of generating dense polymer systems is formidable due to the high density and the connectivity of polymer systems. For crystal structures this can be systematically achieved [33,34] for amorphous structures, however, there is no generally satisfactory method available. Two recent developments in methods for generating amorphous packing (Santos, Suter) are reviewed in Section 3. 

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