Query structure

First, a quei y must be drawn using the MOL" ISIS/Draw program. By using this reaction query, a eurrent reaction search " can be performed. This type of reaction retrieval compares the starting material and the product of the reaction query with all the reactions in the CIRX database. Both query structures must match exactly, including the implicit hydrogen atoms not shown in the reaction query. In this case, one hit is found in the CIRX databases. 

The next abstraction level of reaction retrieval is a so-called reaction substructure search in which both query structures arc considered as substructures. In the case of a reaction substructure search, no hydrogen atoms arc added internally during the execution of the search. Atoms which have their valencies not completely saturated are considered as open sites, where any hind ofelement could be bonded. 

A number of other software packages are available to predict NMR spectra. The use of large NMR spectral databases is the most popular approach it utilizes assigned chemical structures. In an advanced approach, parameters such as solvent information can be used to refine the accuracy of the prediction. A typical application works with tables of experimental chemical shifts from experimental NMR spectra. Each shift value is assigned to a specific structural fragment. The query structure is dissected into fragments that are compared with the fragments in the database. For each coincidence, the experimental chemical shift from the database is used to compose the final set of chemical shifts for the... 

A useful empirical method for the prediction of chemical shifts and coupling constants relies on the information contained in databases of structures with the corresponding NMR data. Large databases with hundred-thousands of chemical shifts are commercially available and are linked to predictive systems, which basically rely on database searching [35], Protons are internally represented by their structural environments, usually their HOSE codes [9]. When a query structure is submitted, a search is performed to find the protons belonging to similar (overlapping) substructures. These are the protons with the same HOSE codes as the protons in the query molecule. The prediction of the chemical shift is calculated as the average chemical shift of the retrieved protons. 

The similarity of the retrieved protons to those of the query structure, and the distribution of chemical shifts among protons with the same HOSE codes, can be used as measures of prediction reliability. When common substructures cannot be found for a given proton (within a predefined number of bond spheres) interpolations are applied to obtain a prediction proprietary methods are often used in commercial programs. 

The database approaches are heavily dependent on the size and quality of the database, particularly on the availability of entries that are related to the query structure. Such an approach is relatively fast it is possible to predict the H NMR spectrum of a molecule with 50-100 atoms in a few seconds. The predicted values can be explained on the basis of the structures that were used for the predictions. Additionally, users can augment the database with their own structures and experimental data, allowing improved predictions for compounds bearing similarities to those added. 

Figure 10.2-S. Procedure for spectra simulation the query structure is coded, a training set of structure-spectra pairs is selected from the database, and the counterpropagation network is trained.

The TcIcSpcc system offens two ways of reading in a query structure. The structure can be input cither directly as a SMILES string (cf. Section 2,3.3) or via a molecule editor which converts the graphical input into the SMILES string. Figure 10.2-10 gives the input form of TeleSpec. 

Data Query using simple query structures (filters) can be built on field values or on coded and decoded information. 

To address these issues regarding adequate structural searching in CHIRBASE, some facilities have been recently added to the user interface. The result is the automatic generation and search of strategic 2D query structures defined with the help of the following commands (Fig. 4-5) ... 

Auto Build This application has been built upon the knowledge and experiences of our working group in order that beginner has access to all pertinent information. Auto Build automatically adds in the sample query structure the appropriate atom and bond query features. Then clicking on SSS button initiates a substructure search. Some examples of the query features, which may be added to a query structure, are ... 

Fig. 4-5. Use of the Auto Build command to create a query structure. A any atoms Ch chain bond Rn ring bond [S,0] oxygen or sulfur atom.

Lazar (http //lazar.in silico.de/predict) is a k-nearest-neighbor approach to predict chemical endpoints from a training set based on structural fragments [43]. It derives predictions for query structures from a database with experimentally determined toxicity data [43]. Model provides prediction for four endpoints Acute toxicity to fish (lethality) Fathead Minnow Acute Toxicity (LC50), Carcinogenicity, Mutagenicity, and Repeated dose toxicity. 

The importance of an appropriate transformation of mass spectra has also been shown for relationships between the similarity of spectra and the corresponding chemical structures. If a spectra similarity search in a spectral library is performed with spectral features (instead of the original peak intensities), the first hits (the reference spectra that are most similar to the spectrum of a query compound) have chemical structures that are highly similar to the query structure (Demuth et al. 2004). Thus, spectral library search for query compounds—not present in the database—can produce useful structure information if compounds with similar structures are present. 

If one s purpose is to determine only the presence or absence in a data base of a specific structure, this can be accomplished with the search option IDENT , as is shown in Figure 11. This program hash-encodes the query structure connection table and searches through a file of hash-encoded connection table for an exact match. The search, which is very fast by substructure search standards, has been designed specifically for those users who, to comply with the Toxic Substances Control Act [26l have to determine the presence or absence of specific compounds in Environmental Protection Agency files. 

Finally, if one has completed ring probe and fragment probe searches for a specific query structure and is still confronted with a sizeable file of compounds that satisfy the criteria that were nominated, a sub-structure search through this file may be carried out. This involves an atom-by-atom, bond-by-bond comparison of every struc-... 

Fig. 4. (A) The other asymmetric Tversky similarity index, S VC, has a value of 0.69. Exchanging the roles of the query and target molecules (Q<=>T) gives (B), which shows that smaller target molecules are more likely to be retrieved from a large query structure using the asymmetric Tversky similarity index than the Tanimoto similarity index.

---