Representation chemical compound

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... 

Representation of Chemical Compounds 21 Structure diagram Condensed formula... 

Representation of Chemical Compounds 29 Table 2-3. Basic SLN syntax without description of attributes and macro atoms. 

The theme of this book has a strong emphasis on the structure of chemical compounds, its representation, and its correlation with properties. However, there are compounds whose structure is either unknown or ill-defincd. This is true, for example, for many polymers, particularly those that have been prepared from several components, or for many technical materials, such as glues, washing powder, etc. 

Infrared spectra are strongly dependent on the 3D structure of a compound, as reflected by the success of attempts to simulate infrared spectra from 3D structure representations (see Section 10.2.5). Infrared spectra should therefore be taken as representations of a chemical compound for modeling properties that are suspected to be dependent on the 3D structure of a compound NMR spectra also depend on... 

The Chemical Abstracts Service has institutionalized the use of graphic representations for identification of and retrieval of information about chemical compounds through their Graphical Data Stmcture (GDS) and connection table (CT). Two information packages. Messenger and STN Express, are the basis for this on-line retrieval system (42). 

As a starting point in the description of the solid intermetallic phases it is useful to recall that their identification and classification requires information about their chemical composition and structure. To be consistent with other fields of descriptive chemistry, this information should be included in specific chemical and structural formulae built up according to well-defined rules. This task, however, in the specific domain of the intermetallic phases, or more generally in the area of solid-state chemistry, is much more complicated than for other chemical compounds. This complexity is related both to the chemical characteristics (formation of variable composition phases) and to the structural properties, since the intermetallic compounds are generally non-molecular in nature, while the conventional chemical symbolism has been mainly developed for the representation of molecular units. As a consequence there is no complete, or generally accepted, method of representing the formulae of intermetallic compounds. 

The need to limit the number of parameters becomes especially evident if molecular shape, which decisively influences the biological properties of chemical compounds, must be considered. Principally, shape can be precisely accounted for by the coordinates of all the atoms in the molecule. Even with rather small molecules (e.g. 20 atoms) one would need a prohibitive amount of parameters (e.g. 60) alone for representation of steric properties. Again, simplifying assumptions are made to reduce the number of parameters. Thus, one can for example assume that only the steric bulk in a certain position determines the biological properties, in which case a one-parameter representation may suffice, e.g. MR or van der Waals volume of the respective substituent. 

Computer-Aided Property Estimation Computer-aided structure estimation requires the structure of the chemical compounds to be encoded in a computer-readable language. Computers most efficiently process linear strings of data, and hence linear notation systems were developed for chemical structure representation. Several such systems have been described in the literature. SMILES, the Simplified Molecular Input Line Entry System, by Weininger and collaborators [2-4], has found wide acceptance and is being used in the Toolkit. Here, only a brief summary of SMILES rules is given. A more detailed description, together with a tutorial and examples, is given in Appendix A. 

Representation, Quantification, and Comparison of the Volumes and Shapes of Chemical Compounds. 

The DARC notation (see, for example, ref. 228) is a system of computer representation of chemical compounds rather than a system for the input of molecules into the computer. It will thus not be discussed here. 

As a compound is represented by a square matrix having a number of rows and columns equal to its number of atoms, it is clear that such a representation cannot be used for input purposes, but is rather an internal representation of structures and reactions. Furthermore, as the numbering of the atoms in a chemical compound is a priori arbitrary, several connectivity tables can be deduced from a given compound. Thus, special algorithms are required to obtain a canonical connectivity table. For example, the Chemical Abstracts Services have recourse to an algorithm devised by Morgan [234]. 

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