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Technical Information

Generic methods are chromatographic methods that are designed to provide adequate resolution for simple tasks like structure verification by LC/MS for a wide variety of compounds. The advantage of these techniques is that they eliminate a need to create a special method for each compound. They are typically fast gradient methods. A plate of compounds from parallel synthesis can be studied in a very short time. Often, multiple generic methods will be applied to each sample. In this case, methods are designed to be complementary; the sample that cannot be adequately separated by one method will work with one of the other methods.

Selecting a Method

A. Samples with one known compound

While the generic methods are applicable to a wide variety of compounds, there are reasons why it is advisable to choose between a series of generic methods rather than simply attempt one or all of them—to eliminate the possibility of a compound precipitating on the column walls, to avoid inadequate peak shape, or to prevent the retention time from exceeding the pre-set time window. All of these challenges can be addressed by the effective selection between a few standard complementary methods.

B. Samples with multiple known compounds

In cases where several compounds are known to be present in the sample, effective prediction can also be used to decide if resolution will be sufficient. This task requires accurate prediction algorithms that are available through ACD/ChromGenius.

How ACD/ChromGenius predictions work:

Compound Verification or Elucidation

In a high-throughput environment, molecular weight by LC/MS is typically used for structure verification purposes. This is obviously an oversimplification. Isomers can't be differentiated by this technique. Accurate prediction of retention time is an additional criterion for verification. And the best part is that the knowledge is already there; no additional data is to be collected.

Retention time can be used as an additional filter for a series of candidate compounds in structure elucidation. Once again, since the data has been collected already as a part of the MS file, this filter is accomplished without additional experimentation.

With the advent of LC-NMR, users may have two generic chromatographic experiments to study. In these situations, the filters can be used concurrently in order to further reduce the number of candidate structures.

The Basis and Accuracy of Prediction

ACD/ChromGenius bases retention time prediction on physicochemical parameters that are calculated for a set of "training" compounds that have been measured previously, and are stored in a knowledge base. These physicochemical parameters are used to model the chromatographic method, and a prediction equation is created. Parameters are calculated for the new structures, and fit to the equation to produce a predicted retention time.

Among the parameters used to create a chromatographic model for a particular method are: logP, logD, MW, MV, MR, PSA, NA, and ND. Use of logD, octanol-water distribution ratio calculated from the chemical structure using pKa and logP values, provides an insight into pH-dependent chromatographic behavior of the compound. For more information on algorithms for calculation of physicochemical properties, please refer to the technical documentation for ACD/Labs' PhysChem products.

ACD/ChromGenius' accuracy of prediction is further enhanced due to the wide variety and number of structures available for customized training. One of the advantages of high-throughput chromatography under generic conditions is that, within a short time frame, retention times are measured for a large number of compounds. ChromGenius uses Structure Similarity Search to select the library of compounds that are most similar to the compound under consideration. The more similar the structure, the more similar the retention mechanism should be. Since liquid chromatography retention mechanisms are very complex, the ACD/LC Simulator model for retention time prediction is necessarily a simplification. However, high-throughput chemistry tends to be done on sets of similar compounds. This large body of information regarding similar compounds makes this simplification valid and highly effective.

Self-Teaching Tool

The tendency of high-throughput chemistry and chromatography to work with similar compounds gives ACD/ChromGenius an added advantage in predicting effective methods and accurate retention times. ChromGenius can use new experimental data to enhance the prediction for subsequent compounds.

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