Computational techniques description

The study of slow protein dynamics is a fascinating field with still many unknowns. We have presented a number of computational techniques that are currently being used to tackle those questions. Most promising for our case seems the development of methods that combine an implicit solvent description with techniques to induce conformational transitions. 

The vibrational states of a molecule are observed experimentally via infrared and Raman spectroscopy. These techniques can help to determine molecular structure and environment. In order to gain such useful information, it is necessary to determine what vibrational motion corresponds to each peak in the spectrum. This assignment can be quite difficult due to the large number of closely spaced peaks possible even in fairly simple molecules. In order to aid in this assignment, many workers use computer simulations to calculate the vibrational frequencies of molecules. This chapter presents a brief description of the various computational techniques available. 

We have chosen to cover a large number of topics, with an emphasis on when and how to apply computational techniques rather than focusing on theory. Each chapter gives a clear description with just the amount of technical depth typically necessary to be able to apply the techniques to computational problems. When possible, the chapter ends with a list of steps to be taken for difficult cases. 

In what follows, we use simple mean-field theories to predict polymer phase diagrams and then use numerical simulations to study the kinetics of polymer crystallization behaviors and the morphologies of the resulting polymer crystals. More specifically, in the molecular driving forces for the crystallization of statistical copolymers, the distinction of comonomer sequences from monomer sequences can be represented by the absence (presence) of parallel attractions. We also devote considerable attention to the study of the free-energy landscape of single-chain homopolymer crystallites. For readers interested in the computational techniques that we used, we provide a detailed description in the Appendix. ... 

The terminology of computational techniques is descriptive, but one needs to know what is being described. Table 7.1 lists some common terms with a definition relative to mass transport. Most computational techniques in fluid transport are described with control volume elements, wherein the important process to be computed is the transport across the interfaces of small control volumes. The common control volumes are cubes, cylindrical shells, triangular prisms, and trapezoidal prisms, although any shape can be used. We will present the control volume technique. 

A full description of computational techniques in microdosimetry is beyond the charter of this chapter and the interested reader may consult the textbook by Rossi and Zaider [17]. Briefly, the calculation proceeds along the following lines ... 

The completely reliable computational technique that we have developed is based on interval analysis. The interval Newton/generalized bisection technique can guarantee the identification of a global optimum of a nonlinear objective function, or can identify all solutions to a set of nonlinear equations. Since the phase equilibrium problem (i.e., particularly the phase stability problem) can be formulated in either fashion, we can guarantee the correct solution to the high-pressure flash calculation. A detailed description of the interval Newton/generalized bisection technique and its application to thermodynamic systems described by cubic equations of state can be found... 

The use of semi-empirical or even force field methods, which are generally used for problems of this size, is nevertheless not apt for the description of these systems [3]. On the other hand, the application of ab initio methods requires a considerable computational effort so that attempts to improve the efficiency of computational techniques are well worthwhile. 

The electron densities of local regions of both small and large molecules can be studied in detail using some of the macromolecular quantum chemical computational techniques developed recently. The shape analysis of host-guest systems and the comparison of the electron densities of interacting and noninteracting molecular regions provide measures and detailed descriptions of these interactions. 

The three-dimensional shape of this fuzzy body of the electronic distribution has many important features not revealed by the simple, skeletal ball and stick model. One of the most important tasks of topological shape analysis of molecules is the precise analysis and concise description of the three-dimensional electronic charge distributions, such as that illustrated by the selected MIDCO s of allyl alcohol in Figure 1.2. Various methods and computational techniques of such topological shape analyses are discussed in detail in this book. 

The next section gives a brief overview of the main computational techniques currently applied to catalytic problems. These techniques include ab initio electronic structure calculations, (ab initio) molecular dynamics, and Monte Carlo methods. The next three sections are devoted to particular applications of these techniques to catalytic and electrocatalytic issues. We focus on the interaction of CO and hydrogen with metal and alloy surfaces, both from quantum-chemical and statistical-mechanical points of view, as these processes play an important role in fuel-cell catalysis. We also demonstrate the role of the solvent in electrocatalytic bondbreaking reactions, using molecular dynamics simulations as well as extensive electronic structure and ab initio molecular dynamics calculations. Monte Carlo simulations illustrate the importance of lateral interactions, mixing, and surface diffusion in obtaining a correct kinetic description of catalytic processes. Finally, we summarize the main conclusions and give an outlook of the role of computational chemistry in catalysis and electrocatalysis. 

Going deeper into the comparison and classification of chemical structures, a set of computational techniques are available. This section is organized to present a brief description of currently used methodologies, namely molecular similarity, pharmacophore modeling, molecular docking, and QSAR followed by application of these methods to food-related components. 

Details of the neutralization process following radiation-induced primary charge separation may be examined via the medium of ultrafast techniques now employed in studies of luminescence decay processes. As an example, the form of luminescence decay curves of dilute organic scintillator in aliphatic hydrocarbon solution excited by x-ray pulses of about 0.5-1.0 nsec, duration is attributed (in previous papers) to neutralization processes involving ions. The relation, t cc r3, for the time required for neutralization of an ion pair of initial separation r, when applied to such curves, leads to a distribution function of ion-pair separations. A more appropriate and desirable approach involves solution of a diffusion equation (which includes a Coulomb interaction term) for various initial conditions. Such solutions are obtained by computer techniques employed in analogy to corresponding electrical networks. The results indicate that the tocr3 law affords a fair description of the decay if the initial distribution can be assumed to be broad. 

---