Substructure search keys methods

Other common descriptors derived from substructure-based methods are discussed below. Among these, hash structural codes, structural keys, and fingerprints are mostly applied in virtual screening and substructure searching, whereas pharmacophore-based descriptors are more successful in similarity/diversity analysis and QSAR/QSPR studies. 

Several product-based approaches to library design that do not require full enumeration have been developed. Pickett et al. have described the design of a diverse amide library where diversity is measured in product space. The DIVSEL program is a DBCS method where dissimilarity is measured in three-point pharmacophore space [83]. Initially, 11 amines were selected based on maximum pharmacophore diversity. Then a total of 1100 carboxylic acids were identified following substructure searching. A set of 1100 pharmacophores keys was generated, where each key corresponds to one acid combined with the 11 amines. DIVSEL was used to select 100 acids based on the diversity of the products. The final library was found to cover 85% of the pharmacophores represented by the entire 12,100 virtual libraries. 

Specialized search engines. There are two major projects to index specifically structure-oriented chemical information on the Web. The full-text search engines provide only textual search capabilities and index only text data. Structure-oriented search methods such as substructure search are not possible with this approach. Chemical names as search keys are problematic because the lUPAC nomenclature is far from unique, complicated, and error-prone, and many compounds are not even named by the original authors. Additionally, trivial and commercial... 

Mass spectra of chemical compounds have a high information content. This article describes computer-assisted methods for extracting information about chemical structures from low-resolution mass spectra. Comparison of the measured spectrum with the spectra of a database (library search) is the most used approach for the identification of unknowns. Different similarity criteria of mass spectra as well as strategies for the evaluation of hitlists are discussed. Mass spectra interpretation based on characteristic peaks (key ions) is critically reported. The method of mass spectra classification (recognition of substructures) has interesting capabilities for a systematic structure elucidation. This article is restricted to electron impact mass spectra of organic compounds and focuses on methods rather than on currently available software products or databases. 

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