Sample query

Molecular similarity searching provides the possibility of finding unrelated but functionally analogous molecules. This is a very nice feature because many distinct structures in contact with a CSP often share the same active sites. The compounds which have a structure similar to the structure of the sample query can be displayed automatically in order of their similarity. The degree of similarity is measured by a numerical value on a scale of 0 to 100 that may be included in the output form. An example of a similarity search is shown in Fig. 4-3. In this example, a search is being performed for the AZT with a similarity value >65 %. 

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 ... 

The third module. Samples, queries the user for how many samples will be taken and the fourth. Concentration, for the expected range of probable concentration values. The choices of probable concentration values are (1) high [ > 10,000 parts-per-billion (ppb) ] (2) Medium [10-10,000 ppb] or (3) Low [< 10 ppb]. The fifth module. Detector, queries the user for the detector that will be used in conjunction with the GC analysis (Figure 2). 

In the next window, write from what sample and how many of them do you want to assign as Training and press OK. Repeat the process to select the internal Validation samples and the test samples (Query). It may be observed in the spreadsheet how the training samples are highlighted in blue, how the internal validation samples are highlighted in green and the test ones in red. 

Sample query find a dataset(s) that have specified characteristics from among a repository of many datasets. Other standard database operations, such as insert and delete, are useful for maintaining and using repositories. 

For the first sample query, a detailed examination of the search routine againsi the records for n-glucose and L-glucose will be described in order to show how nicely the hyperstructure configurations allow differentiation between anomers. A query and the compounds retrieved are given for three test cases a substructure... 

English-language commands. This sample SQL query says, "Give me all sample request data containing John Smith as the customer."... 

Molecule queries (one or two associated molecules) for sample, CSP or solvent ... 

CHIRBASE provides integrated responses from single questions, as well as from combinatorial questions constructed on the basis of any specific query corresponding to one or several field(s) occurring in the database. With the molecular structure of a sample in hand, the search can be conducted interactively from the query menu form. 

By clicking the appropriate buttons on the form, the user can combine molecular structure queries of sample, CSP and solvent, using operators AND, OR, NOT with data queries in one search. A query for the search of chiral separations of alpha-aromatic acids on any polysaccharide phases coated on silica gel providing an alpha value superior to 1.2 is shown in Eig. 4-4. 

S/D (Single/Double bonds) query bond features added if tautomers can be built from sample structure. 

The four queries were examined against a list of samples tested on Whelk CSP that constitutes our search domain. Search results are summarized in Table 4-3. Of the 616 3D structures in this database list, 370 fit at least one of the query (one sample may fit more than one query) and 335 are given as resolved according to chromatographic data or information reported in the field comment. Query 2 retrieved the largest number of compounds with a high percentage of resolved samples in the hit list. While the number of hits retrieved with Query 1 is lower, this query provided a similar proportion of resolved samples (93 %). 

From these preliminary results, we can assume that such enantiophore queries could be used to search in a database of compounds with unknown enantioselectiv-ities. With respect to the percentage of resolved samples that are retrieved in CHIRBASE, the resulting list should contain a similar yield of compounds providing favorable specific interactions with the CSP receptor binding sites. 

Fig. 4-9. Four examples of sample respeetively fitting the queries 1, 2, 3 and 4 of Fig. 4-8.

This method represents the most common and traditional application of computational tools to rational drug design. From a list of molecules of known activity, one can establish a 3D-pharmacophore hypothesis that is then transformed into a 3D-search query. This query is then used to search a 3D database for structures that fit the hypothesis within a certain tolerance. If the yield of active molecules is significant, then the query can be used to predict activities on novel compounds. In our situation, the enantiophore is built from the superposition of a list of sample molecules, which are all well separated on a given CSR Hence, the common features of this series of molecules can become a good enantiophore hypothesis for the enantiores-olution on this CSR... 

Starting from a collection of samples remarkably well resolved (alpha > 6) on Chiralcel OD (Cellulose tris(3,5-dimethylphenylcarbamate) coated on aminopropyl silica), a putative three-point enantiophore for binding to CSR was derived (Fig. 4-10). This enantiophore query was used to search (CFS 3D search) within a list comprising 4203 compounds tested on Chiralcel OD. From this search domain of CHIRBASE 3D, 191 structures were found to match the enantiophore. 

In Fig. 4-11, two different samples are displayed in their original conformations and conformations fitted to the query as they are highlighted by the CFS search process. The CFS process rotates single bonds between two atoms to find the maximum and minimum difference possible with the distance and angle constraints. Then, using a torsional fitter, it attempts to minimize in those conformations the deviations between measured values of 3D constraints and the values that are specified in the 3D-search query. 

Today, the use of CHIRBASE as a tool in aiding the chemist in the identification of appropriate CSPs has produced impressive and valuable results. Although recent developments diminish the need for domain expertise, today the user must possess a certain level of knowledge of analytical chemistry and chiral chromatography. Nevertheless, further refinements will notably reduce this required level of expertise. Part of this effort will include the design of an expert system which will provide rule sets for each CSP in a given sample search context. The expert system will also be able to query the user about the specific requisites for each sample (scale, solubility, etc.) and generate rules which will indicate a ranked list of CSPs as well their most suitable experimental conditions (mobile phase, temperature, pH, etc.). 

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