Molecular modelling field-based techniques

In a broad sense, the term computational chemistry includes several fields such as quantum chemistry, statistical molecular mechanics, molecular modeling, approaches based on graph invariants, molecular graphics and visualization, evaluation of experimental data in X-ray crystallography, NMR spectroscopy, and, in general, spectroscopic techniques moreover, in this broad sense, analysis, exploration, and modeling performed by chemometrics on experimental data, searching for structure-response correlations, information retrieval from chemical databases, and expert chemical systems are also included in computational chemistry, as constitutive parts of —> chemoinformatics. 

More detailed aspects of protein function can be obtained also by force-field based approaches. Whereas protein function requires protein dynamics, no experimental technique can observe it directly on an atomic scale, and motions have to be simulated by molecular dynamics (MD) simulations. Also free energy differences (e.g. between binding energies of different protein ligands) can be characterised by MD simulations. Molecular mechanics or molecular dynamics based approaches are also necessary for homology modelling and for structure refinement in X-ray crystallography and NMR structure determination. 

A potentially much more adaptable technique is force-field vibrational modeling. In this method, the effective force constants related to distortions of a molecule (such as bond stretching) are used to estimate unknown vibrahonal frequencies. The great advantage of this approach is that it can be applied to any material, provided a suitable set of force constants is known. For small molecules and complexes, approximate force constants can often be determined using known (if incomplete) vibrational specha. These empirical force-field models, in effect, represent a more sophisticated way of exhapolating known frequencies than the rule-based method. A simple type of empirical molecular force field, the modified Urey-Bradley force field (MUBFF), is introduced below. 

Another approach is based on the combination of molecular interaction fields using the 3D-QSAR technique CoMFA and soft independent modeling of class analogy (SIMCA) [33], Predictions were made for h % ranges by using the data sets from Refs [19, 27], with about 60% correctly classified. 

Two levels of theory are commonly used in the design of the nickel-based catalysts shown in Figure 11 Density Functional Theory (B3LYP functional used with effective core potentials for Ni and 6-3IG for everything else in the complex) and molecular mechanics (both the UFF (4) and reaction force field, RFF (85,86) are used) (87). All these methods are complementary, and the experiments are guided from the results of several calculations using different molecular modeling techniques. 

The role of CI2 and monochloroacetic acid in the selective chlorination is a difficult problem to understand from the experimental studies. There are several possible orientations for the reactant, product and promoter molecules inside the complex structure of zeolite-L. In this context, it is pertinent to note that molecular modelling techniques are contributing in considerable amount to understand the reaction mechanisms. Molecular modelling includes force field based calculations [3] such as energy minimisation, Monte Carlo, and molecular dynamics calculations and quantum chemical calculations [4 ] such as EHMO, CNDO/INDO, MOPAC, Hartree-Fock and density functional theory calculations. In this study, we have attempted to apply the combination of molecular graphics, force field calculations and quantum chemical calculations to understand the mechanism of selective chlorination of DCB to TCB over zeolite K-L promoted by monochloroacetic acid. 

Our aim in this chapter will be to establish the basic elements of those quantum mechanical methods that are most widely used in molecular modelling. We shall assume some familiarity with the elementary concepts of quantum mechanics as found in most general physical chemistry textbooks, but little else other than some basic mathematics (see Section 1.10). There are also many excellent introductory texts to quantum mechanics. In Chapter 3 we then build upon this chapter and consider more advanced concepts. Quantum mechanics does, of course, predate the first computers by many years, and it is a tribute to the pioneers in the field that so many of the methods in common use today are based upon their efforts. The early applications were restricted to atomic, diatomic or highly symmetrical systems which could be solved by hand. The development of quantum mechanical techniques that are more generally applicable and that can be implemented on a computer (thereby eliminating the need for much laborious hand calculation) means that quantum mechanics can now be used to perform calculations on molecular systems of real, practical interest. Quantum mechanics explicitly represents the electrons in a calculation, and so it is possible to derive properties that depend upon the electronic distribution and, in particular, to investigate chemical reactions in which bonds are broken and formed. These qualities, which differentiate quantum mechanics from the empirical force field methods described in Qiapter 4, will be emphasised in our discussion of typical applications. 

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