Substructure-subspectra databases

Nuclear magnetic resonance (NMR) spectroscopy is the most informative analytical technique and is widely applied in combinatorial chemistry. However, an automated interpretation of the NMR spectral results is difficult (3,4). Usually the interpretation can be supported by use of spectrum calculation (5-18) and structure generator programs (8,12,18-21). Automated structure validation methods rely on NMR signal comparison using substructure/ subspectra correlated databases or shift prediction methods (8,15,22,23). We have recently introduced a novel NMR method called AutoDROP (Automated Definition and Recognition of Patterns) to rapidly analyze compounds libraries (24-29). The method is based on experimental data obtained from the measured ID or 2D iH,i C correlated (HSQC) spectra. 

Research laboratories synthesize new compounds which are not contained in the library. In this second case, information about the structure of the new compound can be drawn from similarity searches, resulting in substructures assumed to be part of the query structure. The search algorithm is tuned to detect subspectra and the corresponding substructures. Techniques of this type can only be applied if structure-oriented databases exist. In the case of a similarity search the use of filter functions for accelerating the search speed is dangerous important information may be lost if relevant subspectra are filtered out. 

The knowledge base (subspectra-substructure correlation library. Figure 16) of the system has been derived from a Structure-oriented C NMR database with more than 200000... 

In contrast to CHEMICS, CISOC-SES. and SESAMI. the.se programs are database dependent (see Sections 3.2 and 4.2). Output is limited to those structures that can be constructed from the substructure library of each program. The.se systems are, nonetheless, powerful, in particular In laboratory settings where the classes of compounds studied are limited. For example, the dedicated subspectra-substructure correlation library of SpecSolv currently consists of more than 400000 three-sphere fragments and 100000 two-sphere fragments derived from 200000 C NMR spectra. SpecSolv does not require a molecular formula. 

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