Molecular modeling goals

Equation (2.14) has the advantage of simplicity its drawback is that we learn nothing about either the nature of viscosity or the nature of the sample from the result. In the next few sections we shall propose and develop a molecular model for the flow process. The goals of that development will be not only to describe the data, but also to do so in terms of parameters which have some significance at the molecular level. Before turning to this, it will be helpful if we consider a bit further the form of Eq. (2.14). 

One tool for working toward this objective is molecular mechanics. In this approach, the bonds in a molecule are treated as classical objects, with continuous interaction potentials (sometimes called force fields) that can be developed empirically or calculated by quantum theory. This is a powerful method that allows the application of predictive theory to much larger systems if sufficiently accurate and robust force fields can be developed. Predicting the structures of proteins and polymers is an important objective, but at present this often requires prohibitively large calculations. Molecular mechanics with classical interaction potentials has been the principal tool in the development of molecular models of polymer dynamics. The ability to model isolated polymer molecules (in dilute solution) is well developed, but fundamental molecular mechanics models of dense systems of entangled polymers remains an important goal. 

The dissection of a molecular model into those components that are deemed to be essential for the understanding of the stereochemistry of the whole may be termed factorization (9). The first and most important step toward this goal was taken by van t Hoff and Le Bel when they introduced the concept of the asymmetric carbon atom (10a, 1 la) and discussed the achiral stereoisomerism of the olefins (10b,lib). We need such factorization not only for the enumeration and description of possible stereoisomers, important as these objectives are, but also, as we have seen, for the understanding of stereoselective reactions. More subtle differences also giving rise to differences in reactivity with chiral reagents, but referable to products of a different factorization, will be taken up in Sect. IX. 

This paper describes a new approach to building molecular models using methods of expert systems. We are applying symbolic reasoning to a problem previously only approached numerically. The goals of this project were to develop a rapid model builder that mimicked the manual process used by chemists. A further aim was to provide a justification for the model as a chemist would justify a particular conformation. The AIMS algorithm reported here is extremely fast and has a complexity that increases linearly with the number of atoms in the model. 

Molecular modeling serves many purposes. Here we are interested in an optimization of the geometry of specific molecules given known bond lengths, bond angles and energy data. The goal is to find a structure most consistent with ideal structural features. Each type of atom, and each kind of bond must be parameterized from experimental data. 

The ultimate goal of quantum mechanical calculations as applied in molecular modeling is the a priori compulation of properties of molecules with the highest possible accuracy (rivaling experiment), hut utilizing the fewest approximations in the description of the wave-function. Al> initio. or from first principles, calculations represent the current state of the an ill this domain. Ah i/tirio calculations utilize experimental data on atomic systems to facilitate the adjustment of parameters such as the exponents ol the Gaussian functions used to describe orbitals within the formalism. 

A familiarity with intermolecular forces is crucial to building insight into matter. We saw in Chapter 4 that a major goal in chemistry is to trace the connection between individual atoms and molecules and the bulk substances they form. There we dealt with gases, in which intermolecular forces play only a minor role. Here we deal with liquids and solids, for which the forces that hold molecules together are of crucial importance. Individual water molecules, for instance, are not wet, but bulk water is wet. Individual water molecules neither freeze nor boil, but bulk water does. We have to refine our atomic and molecular model of matter to see how properties like these, which we observe when we examine samples consisting of huge numbers of molecules, can be interpreted in terms of the properties of individual molecules, such as their size, shape, and polarity. 

In this chapter, I will discuss the strengths and limitations of molecular models obtained by X-ray diffraction. My aim is to help you to use crystallographic models wisely and appropriately, and realize just what is known, and what is unknown, about a molecule that has yielded up some of its secrets to crystallographic analysis. To demonstrate how you can draw these conclusions for yourself with regard to a particular molecule of interest, I will conclude this chapter by discussing a recent structure determination, as it appeared in a biochemical journal. Here my goals are (1) to help you learn to extract criteria of model quality from published structural reports and (2) to review some basic concepts of protein crystallography. 

My main goal, as outlined in the Preface to the First Edition, which appears herein, is the same as before to help you see the logical thread that connects those mysterious diffraction patterns to the lovely molecular models you can display and play with on your personal computer. An equally important aim is to inform you that not all crystallographic models are perfect and that cartoon models do not exhaust the usefulness of crystallographic analysis. Often there is both less and more than meets the eye in a crystallographic model. 

Mastery Goal Quiz Molecular Model Problems... 

Physical Properties and Molecular Structure 2.7 Introduction to Functional Groups Mastery Goal Quiz Molecular Model Problems... 

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