Structural feature

Structural keys describe the chemical composition and structural motifs of molecules represented as a Boolean array. If a certain structural feature is present in a molecule or a substructure, a particular bit is set to 1 (true), otherwise to 0 (false). A bit in this array may encode a particular functional group (such as a carboxylic acid or an amidelinkage), a structural element (e.g., a substituted cyclohexane), or at least n occurrences of a particular element (e.g., a carbon atom). Alternatively, the structural key can be defined as an array of integers where the elements of this array contain the frequency of a specific feature in the molecule. 

The structural feature that Figures 3 2 and 3 3 illustrate is the spatial relationship between atoms on adjacent carbons Each H—C—C—H unit m ethane is characterized by a torsion angle or dihedral angle which is the angle between the H—C—C plane 

The structural features of methane ethane and propane are summarrzed rn Ergure 2 7 All of the carbon atoms have four bonds all of the bonds are srngle bonds and the bond angles are close to tetrahedral In the next sectron we 11 see how to adapt the valence bond model to accommodate the observed structures 

The structural features especially the very polar nature of the carbonyl group point clearly to the kind of chemistry we will see for aldehydes and ketones in this chapter The partially positive carbon of C=0 has carbocation character and is electrophilic The planar arrangement of its bonds make this carbon relatively uncrowded and susceptible to attack by nucleophiles Oxygen is partially negative and weakly basic 

The structural features of the carboxyl group are most apparent m formic acid Formic acid IS planar with one of its carbon-oxygen bonds shorter than the other and with bond angles at carbon close to 120° 

Certain structural features can sometimes help us determine by inspection whether a mol ecule IS chiral or achiral For example a molecule that has a plane of symmetry or a cen ter of symmetry is superimposable on its mirror image and is achiral 

Certain structural features can make the keto-enol equilibrium more favorable by stabi hzmg the enol form Enolization of 2 4 cyclohexadienone is one such example 

Determination of structural features. The ultraviolet spectrum has been of value in the determination of the structure of several vitamins. Thus the presence of an a-naphthoquinone system in vitamin K was first detected by this means. Also the 4-methylthiazole and the 2 5-dimethyl-6-aminopyridine system was first identified in vitamin Bj (thiamine), a- and /3-Ionones can be distinguished since the former contains two conjugated chromophores and the latter three conjugated chromophores. 

It is possible to identify particular spectral features in the modulated reflectivity spectra to band structure features. For example, in a direct band gap the joint density of states must resemble that of critical point. One of the first applications of the empirical pseudopotential method was to calculate reflectivity spectra for a given energy band. Differences between the calculated and measured reflectivity spectra could be assigned to errors in the energy band 

The two most important structural features that stabilize the enol of a (3 dicarbonyl compound are 

We have considered the following structural features affecting the choice of antitheticaf steps starting from simple target molecules  

The structure in the reflectivity can be understood in tenns of band structure features i.e. from the quantum states of the crystal. The nonnal incident reflectivity from matter is given by 

Figure 1.8 Optimization discards many structural features, leaving an optimized structure.

Recognition of functional groups or gross structural features. 

At this point It s useful to compare some structural features of alkanes alkenes and alkynes Table 9 1 gives some of the most fundamental ones To summarize as we progress through the series m the order ethane ethylene acetylene 

Descriptors have to be found representing the structural features which are related to the target property. This is the most important step in QSPR, and the development of powerful descriptors is of central interest in this field. Descriptors can range from simple atom- or functional group counts to quantum chemical descriptors. They can be derived on the basis of the connectivity (topological or 

In this example addition to the double bond of an alkene converted an achiral mol ecule to a chiral one The general term for a structural feature the alteration of which introduces a chirality center m a molecule is prochiral A chirality center is introduced when the double bond of propene reacts with a peroxy acid The double bond is a prochi ral structural unit and we speak of the top and bottom faces of the double bond as prochiral faces Because attack at one prochiral face gives the enantiomer of the com pound formed by attack at the other face we classify the relationship between the two faces as enantiotopic 

Thus with dihalocarbenes we have the interesting case of a species that resem bles both a carbanion (unshared pair of electrons on carbon) and a carbocation (empty p orbital) Which structural feature controls its reactivity s Does its empty p orbital cause It to react as an electrophile s Does its unshared pair make it nucleophilic s By compar mg the rate of reaction of CBi2 toward a series of alkenes with that of typical electrophiles toward the same alkenes (Table 14 4) we see that the reactivity of CBi2 

Two approaches to quantify/fQ, i.e., to establish a quantitative relationship between the structural features of a compoimd and its properties, are described in this section quantitative structure-property relationships (QSPR) and linear free energy relationships (LFER) cf. Section 3.4.2.2). The LFER approach is important for historical reasons because it contributed the first attempt to predict the property of a compound from an analysis of its structure. LFERs can be established only for congeneric series of compounds, i.e., sets of compounds that share the same skeleton and only have variations in the substituents attached to this skeleton. As examples of a QSPR approach, currently available methods for the prediction of the octanol/water partition coefficient, log P, and of aqueous solubility, log S, of organic compoimds are described in Section 10.1.4 and Section 10.15, respectively. 

This case history presents only a simple account of one of R.B. Woodward s adventures based on ingenious undentanding of structural features and experimental findings described in the literature. The hydrogenation of porphyrins is still one of the most active subjects in heterocyclic natural products chemistry, and the interested reader may find some modem developments in the publications of A. Eschenmoser (C.Angst, 1980 J.E. Johansen, 1980). 

Alternative superstructures to those in Figs. 16.26 and 16.27 can be developed. On the one hand, it is desirable to include many structural options to ensure that all features which are candidates for an optimal solution have been included. On the other hand, including more and more structural features increases the computational load dramatically. Thus care should be taken not to include unnecessary features in the superstructure. 

A series of monographs and correlation tables exist for the interpretation of vibrational spectra [52-55]. However, the relationship of frequency characteristics and structural features is rather complicated and the number of known correlations between IR spectra and structures is very large. In many cases, it is almost impossible to analyze a molecular structure without the aid of computational techniques. Existing approaches are mainly based on the interpretation of vibrational spectra by mathematical models, rule sets, and decision trees or fuzzy logic approaches. 

Reactions can be considered as composite systems containing reactant and product molecules, as well as reaction sites. The similarity of chemical structures is defined by generalized reaction types and by gross structural features. The similarity of reactions can be defined by physicochemical parameters of the atoms and bonds at the reaction site. These definitions provide criteria for searching reaction databases [23], 

Spectral features and their corresponding molecular descriptors are then applied to mathematical techniques of multivariate data analysis, such as principal component analysis (PCA) for exploratory data analysis or multivariate classification for the development of spectral classifiers [84-87]. Principal component analysis results in a scatter plot that exhibits spectra-structure relationships by clustering similarities in spectral and/or structural features [88, 89]. 

The first widely used molecular mechanics pro gram was developed by Professor N L Allinger of the University of Georgia and was known in its various versions as MM2 MM3 and so on They have been re fined to the extent that many structural features can be calculated more easily and more accurately than they can be measured experimentally 

Because so many factors contribute to the net intermolecular attractive force it is not always possible to predict which of two compounds will have the higher boiling point We can however use the boiling point behavior of selected molecules to inform us of the relative importance of various intermolecular forces and the structural features that influence them 

On the other hand, techniques like Principle Component Analysis (PCA) or Partial Least Squares Regression (PLS) (see Section 9.4.6) are used for transforming the descriptor set into smaller sets with higher information density. The disadvantage of such methods is that the transformed descriptors may not be directly related to single physical effects or structural features, and the derived models are thus less interpretable. 

---