Chemical structure, representation algorithmic

Our intention in this chapter is to examine the challenges of extracting identihers from chemistry-related documents and the conversion of those identihers into chemical structures. The authors of this work each have well over a decade of experience in chemical structure representation and systematic nomenclature. We have been deeply involved in the development of software algorithms and software for the generation of systematic names and the conversion of chemical identihers into chemical structures.9 Although we have our own biases concerning approaches to the problem of N2S conversion, we have done our utmost to be objective in our review of the subject and comparison of approaches and performance. 

Wisniewski, J.L. (2003) Chemical nomenclature and structure representation algorithmic generation and conversion, in Handbook of Chemoinformatics, Vol. 1 (ed. J. Gasteiger), Wiley-VCH Verlag GmbH, Weinheim, Germany, pp. 51-79. 

Eakin [13] describes the chemical structure information system at Imperial Chemical Industries Ltd., where registration is based on Wiswesser Line Notation. For connection tables, the unique, unambiguous representation is derived automatically, i.e., a single, invariant numbering of the connection table is algorithmically derived. 

Substantial attention and progress has been made in the development of procedures to effect conversion between chemical substance representations. Zamora and Davis [26] describe an algorithm to convert a coordinate representation of a chemical substance (derived from input by a chemical typewriter) to a connection table. An approach for interactive input of a structure diagram and conversion of this representation to a connection table suitable for substructure searching is discussed by Feldmann [27]. The conversion of systematic nomenclature to connection tables offers a powerful editing tool as well as a potential mechanism for conversion of name files to connection tables this type of conversion is described by Vander Stouw [28]. 

In order to calculate a physicochemical property, the structure of a molecule must be entered in some manner into an algorithm. Chemical structure notations for input of molecules into calculation software are described in Chapter 2, Section VII and may be considered as either being a 2D string, a 2D representation of the structure, or (very occasionally) a 3D representation of the structure. Of this variety of methods, the simplicity and elegance of the 2D linear molecular representation known as the Simplified Molecular Line Entry System (SMILES) stands out. Many of the packages that calculate physicochemical descriptors use the SMILES chemical notation system, or some variant of it, as the means of structure input. The use of SMILES is well described in Chapter 2, Section VII.B, and by Weininger (1988). There is also an excellent tutorial on the use of SMILES at www.daylight.com/dayhtml/smiles/smiles-intro.html. 

Connection tables are the predominant form of internal representation of chemical structures in computer memory. That is, they form the data structures to which various processing algorithms can be applied. Many external connection table file formats also exist for disk storage and exchange of structure representations. 

In the near future, registration systems will need to move beyond their traditional domain of small molecules into the realm of larger biological entities such as proteins, plasmids and vaccines. Although technically still chemical structures, their size and complexity will require the development of new representations and algorithms that permit rapid searching and novelty checking. 

As a general rule, in the representation of chemical structures, the hydrogen atoms are not coded at all. If necessary, for example, for graphical representation of a molecule, hydrogen atoms can be added by a suitable algorithm automatically. 

Canonization Important for the representation of a chemical structure as matrix or table is the unique assignment (canonization) of atoms in the structure. This can be calculated, for example, by Morgan s algorithm. 

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