Spectrum prediction database retrieval

RDF descriptors exhibit a series of unique properties that correlate well with the similarity of structure models. Thus, it would be possible to retrieve a similar molecular model from a descriptor database by selecting the most similar descriptor. It sounds strange to use again a database retrieval method to elucidate the structure, and the question lies at hand Why not directly use an infrared spectra database The answer is simple. Spectral library identification is extremely limited with respect to about 28 million chemical compounds reported in the literature and only about 150,000 spectra available in the largest commercial database. However, in most cases scientists work in a well-defined area of structural chemistry. Structure identification can then be restricted to special databases that already exist. The advantage of the prediction of a descriptor and a subsequent search in a descriptor database is that we can enhance the descriptor database easily with any arbitrary compound, whether or not a corresponding spectrum exists. Thus, the structure space can be enhanced arbitrarily, or extrapolated, whereas the spectrum space is limited. 

Spectroscopic databases are a very valuable tool for the identification of known and unknown substances. In most spectroscopic laboratories they are available and frequently used. Retrieval of data and spectra similarity searches are established tools for the fast identification of unknown compounds. The spectroscopic information stored in the databases offers the generation of structure-spectra correlations, which can be used for predicting spectral features of new compounds. Effective spectrum prediction tools are available for C NMR and H NMR, and will become available for IR spectroscopy in the near future. The prediction of mass spectra is still a challenge. 

The most common approaches to predicting spectra are based on empirical modeling, linear additivity, database retrieval, rule sets, and semiempirical methods. The availability of large spectral libraries has proved to be a valuable resource in these studies. Although ab initio theory relating to spectrum prediction is well advanced, the theoretical equations necessary for application to real-world structures are large and complex... 

FIGURE 6.4 (continued) (c) Derivation of the 3D structure of a compound from its infrared spectrum. After training, the query infrared spectrum is used to predict the RDF descriptor, and a structure database is searched for the most similar descriptor. The corresponding structure is retrieved as the initial model. 

Database Approach is a specific method for deriving the molecular structure from an infrared spectrum by predicting a molecular descriptor from an artificial neural network and retrieving the structure with the most similar descriptor from a structure database. 

---