Searching chemical substructure

Granito, Charles E., "CHEMTRAN and the Interconversion of Chemical Substructure Search Systems," Journal of Chemical Documentation, 1 3(2), 72-74 (1973). 

Brit. 6, 420 (1970) Citations in Chemistry (SIC) Cawkell, A. E., Chem. Brit. 6, 414 (1970). Other relevant articles in this issue include Hyams, M., Chemical patents information, p. 416 and Polton, D. J., lUPAC notation in chemical substructure searching, p. 430. 

Downs GM, Lynch MF, Willett P, Manson GA, Wilson GA. Transputer implementations of chemical substructure searching algorithms. Tetrahedron Comput Methodol 1988 1 207-217. 

Adamson GW, Clinch YA, Cressey SE, Lynch MF. Distributions of fragment representations in a chemical substructure search screening system. J Chem Doc 1974 14 72— 74. 

Gannon MT, Willett P. Sampling considerations in the selection of fragment screens for chemical substructure search systems. J Chem Inf Comput Sci 1979 19 251-255. 

The chemical connectivity tables are, of course, a formalized representation of 2D chemistry, and, in some situations, rules must be applied in creating the table. These rules must be known to the user when a chemical substructure search query is being formulated and are further discussed in Section 3.7.4. 

Fig. 3.5. Example of a chemical substructure search in the CSD System (see text)...

Two methods are commonly applied for library searches. Identity or retrieval searches assume that the spectrum of the unknown compound is present in the reference library, and only experimental variability prevents a perfect match of the unknown and reference spectra. When no similar spectra are retrieved the only information provided is that the unknown spectrum is not in the library. Similarity or interpretive searches assume that the reference library does not contain a spectrum of the unknown compound, and are designed to produce structural information from which identity might be inferred. Interpretive methods typically employ a predetermined set of spectral features, designed to correlate with the presence of chemical substructures. Searching identifies the library spectra that have features most similar to those of the unknown spectrum. The frequency of occurrence of a substructure in the hit list is used to estimate the probability that it is present in the unknown compound. Two well-developed interpretative search algorithms are SISCOM (Search of Identical and Similar Compounds) and STIRS (the Self-Training Interpretive and Retrieval System) [174-177]. Normally a retrieval search is performed first, and when the results are inconclusive, an interpretive search is implemented. In both cases, success depends on the availability of comprehensive libraries of high-quality reference spectra [178]. 

Graphics-based chemical substructure search system. 

Gillet, V.J. Welford, S.M. Lynch, M.F. Willett, P. Barnard, J.M. Downs, G.M. Manson, G. Thompson, J. Computer Storage and Retrieval of Generic Chemical Structures in Patents. 7. Parallel Simulation of a Relaxation Algorithm for Chemical Substructure Search. J. Chem. Inf. Comput. Sci. 1986, 26, 118-26. 

Relaxation Algorithm for Chemical Substructure Search . J. Chem. Inf. Comput. Sci. 1986,26, 118-126. 

L- Hodes,/. Chem. Inf. Comput. Set., 16, 88 (1976). Selection of Descriptors According to Discrimination and Redundancy. Application to Chemical Substructure Searching. 

Dunn, R. G., Fisanlck, W., and Zamora, A., "A Chemical Substructure Search System Based on Chemical Abstracts Index Nomenclature", J. Chem. Inf. Computer. Sci., ]J (4),... 

---