Molecular systems real” system properties

Once the model of a ligand-receptor complex is built, its stability should be evaluated. Simple molecular mechanics optimization of the putative ligand-receptor complex leads only to the identification of the closest local minimum. However, molecular mechanics optimization of molecules lacks two crucial properties of real molecular systems temperature and, consequently, motion. Molecular dynamics studies the time-dependent evolution of coordinates of complex multimolecular systems as a function of inter- and intramolecular interactions (see Chapter 3). Because simulations are usually performed at nonnal temperature (—300 K), relatively low energy barriers, on the order of kT (0.6 kcal), can... 

Computer simulations therefore have several inter-related objectives. In the long term one would hope that molecular level simulations of structure and bonding in liquid crystal systems would become sufficiently predictive so as to remove the need for costly and time-consuming synthesis of many compounds in order to optimise certain properties. In this way, predictive simulations would become a routine tool in the design of new materials. Predictive, in this sense, refers to calculations without reference to experimental results. Such calculations are said to be from first principles or ab initio. As a step toward this goal, simulations of properties at the molecular level can be used to parametrise interaction potentials for use in the study of phase behaviour and condensed phase properties such as elastic constants, viscosities, molecular diffusion and reorientational motion with maximum specificity to real systems. Another role of ab initio computer simulation lies in its interaction... 

We will delay a more detailed discussion of ensemble thermodynamics until Chapter 10 indeed, in this chapter we will make use of ensembles designed to render the operative equations as transparent as possible without much discussion of extensions to other ensembles. The point to be re-emphasized here is that the vast majority of experimental techniques measure molecular properties as averages - either time averages or ensemble averages or, most typically, both. Thus, we seek computational techniques capable of accurately reproducing these aspects of molecular behavior. In this chapter, we will consider Monte Carlo (MC) and molecular dynamics (MD) techniques for the simulation of real systems. Prior to discussing the details of computational algorithms, however, we need to briefly review some basic concepts from statistical mechanics. 

Spectroscopic methods are very useful for determining molecular properties. Time-resolved spectroscopic methods are useful for monitoring the evolution of the molecular properties in real time. Moreover, time-resolved spectroscopic techniques have the best time resolution available among all kinds of time-resolved experimental techniques. Thus, very often time-resolved spectroscopic methods reveal the dynamics of a molecular system in the non-equilibrium regime. In this section, the density matrix method is applied to calculate the spectroscopic properties of molecular systems. These include the linear and non-linear optical processes, in equilibrium or non-equilibrium cases. The approach is based on the susceptibility theory. 

Some applications are listed to illustrate these potentials. They may be classified in various ways. The most direct approach consists in working with labelled (deuterated), model systems. Real materials (designed for industrial applications and processed at a large scale) are often multicomponent, complex systems, which may be relatively ill defined at the molecular scale. Thus, working with chemically well defined, labelled materials (which, however, often have relatively poor mechanical properties by themselves) is a way to isolate and study the various parameters which play a role in rubber properties. Studies are done both in the relaxed state and in constrained (uniaxially deformed) states. This approach is illustrated in Section 15.3. Examples of studies performed in model, single component networks are presented. However, even in this case, the sensitivity of the method is such that it may detect the presence of a few percent of molecular defects. 

Molecular modelling is not strictly an analytical tool that can be used directly. It is, however, a valuable way of visualizing supramolecular systems and predicting structures. The most sophisticated methods are able to predict properties associated with the model that can usefully be compared to data gathered on the real system. This is useful when several different interpretations of an experiment arise as one model may be shown to fit the data best and so be the most probable explanation. The main limitations of molecular modelling, and computational techniques in general, are the accuracy of the output and the the size of simulation that can usefully be attempted without recourse to a supercomputer or massively parallel facility. 

Let us now summarize some of the results for the real systems investigated so far in terms of the molecular orbital and quasi-particle properties of the core and valence levels. Starting from a HF MO picture, one can have the following sequence of characteristics ... 

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