Molecular structures compounds

The carbaalanes [8, 9] possess clusters formed by aluminum and carbon atoms. They represent a new class of compounds which, in some respects, may be compared to the important class of carbaboranes. Usually, they were obtained by the reaction of aluminum alkynides with aluminum hydrides (hydroalumination) and the release of trialkylaluminum derivatives (condensation). The first carbaalane, (AlMe)g(CCH2Ph)5H 3 [10], was synthesized by the treatment of dimethylalumi-num phenylethynide with neat dimethylaluminum hydride. The idealized stoichiometric ratio of the components is given in Eq. (2), which also shows a schematic drawing of the molecular structure. Compound 3 was isolated in the form of colorless crystals in 60% yield. While 3 is only slightly air-sensitive, the less sterically shielded propynide derivative 4, also shown in Eq. (2), is highly pyrophoric [11],... 

Table 5 2PA properties of dipolar molecules as a function of donor/acceptor strengths. The solvent in which the measurement was performed is indicated in parenthesis after the molecular structure. Compounds d.3 and d.5 from Table 4 are repeated here to facilitate comparisons... 

Liquid Crystals Liquid-crystal phases may occur between the solid and the liquid phase. Cholesteryl myristate, for example, exists in a liquid-crystal phase between 71 and 85°C [6]. The appearance of liquid-crystal phases depends on the molecular structure. Compounds with elongated structures that are fairly rigid in the central part of the molecule are likely candidates for liquid crystals. The homologous series of p-alkoxybenzylidene-p-n-butylanilines is just one example for compounds with liquid-crystal phases. An excellent introduction to liquid crystals and their properties has been written by Collings [6]. 

In the reactions with A,A-dimethylacrylamide, for example, diastereomeric cycloaddncts were separated into pale yellow prisms and yellow blocks by fractional crystallization with dichloromethane and diethyl ether. These molecular structures (compounds 8.37, 8.38) were determined by X-ray structural analysis. The optically active phosphinoamides were isolated as both pure i -endo 8.39 ([a]365=-1-5.9) and S-endo 8.40 ([a]365=-5.7) forms, moreover, by treatment with aqueous potassium cyanide, as shown in Scheme 8.4 [23]. 

The entire Hving and material world consists of compounds and mixtures of compounds. Basic chemicals, such as ethylene, are produced in many millions of tons each year and are converted into a wide variety of other chemicals. Complicated molecular structures are synthesized by Mother Nature, or by chemists having taken up the challenge posed by Nature. However, we also have materials such as glues which are composed of mixtures of rather ill-defined polymers. 

In this book we shall deal largely with those compounds that can be described by a clearly defined molecular structure. The representation of polymers and of mixtures of compounds will only be mentioned in passing. 

Information if data are put into context with other data, we call the result information. The measurement of the biological activity of a compound gains in value if we also know the molecular structure of that compoimd. 

First, the objects of investigation, chemical compounds or chemical reactions, have to be represented. Chemical compoimds wUl mostly be represented by their molecular structure in various forms of sophistication. This task is addressed in Chapter 2. The representation of chemical reactions is dealt with in Chapter 3. The vast number of compounds known can only be managed by storing them... 

HMO theory is named after its developer, Erich Huckel (1896-1980), who published his theory in 1930 [9] partly in order to explain the unusual stability of benzene and other aromatic compounds. Given that digital computers had not yet been invented and that all Hiickel s calculations had to be done by hand, HMO theory necessarily includes many approximations. The first is that only the jr-molecular orbitals of the molecule are considered. This implies that the entire molecular structure is planar (because then a plane of symmetry separates the r-orbitals, which are antisymmetric with respect to this plane, from all others). It also means that only one atomic orbital must be considered for each atom in the r-system (the p-orbital that is antisymmetric with respect to the plane of the molecule) and none at all for atoms (such as hydrogen) that are not involved in the r-system. Huckel then used the technique known as linear combination of atomic orbitals (LCAO) to build these atomic orbitals up into molecular orbitals. This is illustrated in Figure 7-18 for ethylene. 

A challenging task in material science as well as in pharmaceutical research is to custom tailor a compound s properties. George S. Hammond stated that the most fundamental and lasting objective of synthesis is not production of new compounds, but production of properties (Norris Award Lecture, 1968). The molecular structure of an organic or inorganic compound determines its properties. Nevertheless, methods for the direct prediction of a compound s properties based on its molecular structure are usually not available (Figure 8-1). Therefore, the establishment of Quantitative Structure-Property Relationships (QSPRs) and Quantitative Structure-Activity Relationships (QSARs) uses an indirect approach in order to tackle this problem. In the first step, numerical descriptors encoding information about the molecular structure are calculated for a set of compounds. Secondly, statistical and artificial neural network models are used to predict the property or activity of interest based on these descriptors or a suitable subset. 

The Cahn-Ingold-Prelog (CIP) rules stand as the official way to specify chirahty of molecular structures [35, 36] (see also Section 2.8), but can we measure the chirality of a chiral molecule. Can one say that one structure is more chiral than another. These questions are associated in a chemist s mind with some of the experimentally observed properties of chiral compounds. For example, the racemic mixture of one pail of specific enantiomers may be more clearly separated in a given chiral chromatographic system than the racemic mixture of another compound. Or, the difference in pharmacological properties for a particular pair of enantiomers may be greater than for another pair. Or, one chiral compound may rotate the plane of polarized light more than another. Several theoretical quantitative measures of chirality have been developed and have been reviewed elsewhere [37-40]. 

An extensive series of studies for the prediction of aqueous solubility has been reported in the literature, as summarized by Lipinski et al. [15] and jorgensen and Duffy [16]. These methods can be categorized into three types 1 correlation of solubility with experimentally determined physicochemical properties such as melting point and molecular volume 2) estimation of solubility by group contribution methods and 3) correlation of solubility with descriptors derived from the molecular structure by computational methods. The third approach has been proven to be particularly successful for the prediction of solubility because it does not need experimental descriptors and can therefore be applied to collections of virtual compounds also. 

A relatively small training set of 744 NMR chemical shifts for protons from 1 20 molecular structures was collected from the literature. This set was designed to cover as many situations of protons in organic structures as possible. Only data from spectra obtained in CDCl, were considered. The collection was restricted to CH protons and to compounds containing the elements C, H, N, 0, S, F, Cl, Br. or I. 

Gavezzotti A 1991. Generation of Possible Crystal Structures from the Molecular Structure for Low-polarity Organic Compounds, journal of the American Chemical Society 113 4622-4629. 

There are now extensive databases of molecular structures and properties. There are some research efforts, such as drug design, in which it is desirable to hnd all molecules that are very similai to a molecule which has the desired property. Thus, there are now techniques for searching large databases of structures to hnd compounds with the highest molecular similarity. This results in hnding a collection of known structures that are most similar to a specihc compound. 

Like QSAR, molecular structures must be available for compounds that... 

Another technique employs a database search. The calculation starts with a molecular structure and searches a database of known spectra to find those with the most similar molecular structure. The known spectra are then used to derive parameters for inclusion in a group additivity calculation. This can be a fairly sophisticated technique incorporating weight factors to account for how closely the known molecule conforms to typical values for the component functional groups. The use of a large database of compounds can make this a very accurate technique. It also ensures that liquid, rather than gas-phase, spectra are being predicted. 

Once a number of lead compounds have been found, computational and laboratory techniques are very successful in rehning the molecular structures to yield greater drug activity and fewer side elfects. This is done both in the laboratory and computationally by examining the molecular structures to determine which aspects are responsible for both the drug activity and the side effects. These are the QSAR techniques described in Chapter 30. Recently, 3D QSAR has become very popular for this type of application. These techniques have been very successful in the rehnement of lead compounds. 

Material properties can be further classified into fundamental properties and derived properties. Fundamental properties are a direct consequence of the molecular structure, such as van der Waals volume, cohesive energy, and heat capacity. Derived properties are not readily identified with a certain aspect of molecular structure. Glass transition temperature, density, solubility, and bulk modulus would be considered derived properties. The way in which fundamental properties are obtained from a simulation is often readily apparent. The way in which derived properties are computed is often an empirically determined combination of fundamental properties. Such empirical methods can give more erratic results, reliable for one class of compounds but not for another. 

Analyzing an NMR spectrum m terms of a unique molecular structure begins with the mfor matron contained m Table 13 1 By knowing the chemical shifts characteristic of various proton environments the presence of a particular structural unit m an unknown compound may be inferred An NMR spectrum also provides other useful information including... 

The importance of linked scanning of metastable ions or of ions formed by induced decomposition is discussed in this chapter and in Chapter 34. Briefly, linked scanning provides information on which ions give which others in a normal mass spectrum. With this sort of information, it becomes possible to examine a complex mixture of substances without prior separation of its components. It is possible to look highly specifically for trace components in mixtures under circumstances in which other techniques could not succeed. Finally, it is possible to gain information on the molecular structures of unknown compounds, as in peptide and protein sequencing (see Chapter 40). 

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