2004
DOI: 10.1021/cc049914y
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Prediction of HPLC Conditions Using QSPR Techniques:  an Effective Tool to Improve Combinatorial Library Design

Abstract: The purification and characterization of compounds resulting from parallel synthesis or combinatorial chemistry has not yet been optimized to operate as a completely automated high-throughput process. Liquid chromatography/mass spectroscopy (LC/MS) is most commonly employed to carry out the characterization and identification of combinatorial compounds. This desired level of automation can only be accomplished if the separation conditions for every compound in the combinatorial array are known prior to the ana… Show more

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Cited by 31 publications
(15 citation statements)
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References 27 publications
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“…Taking into account, that the correlation parameters related to these descriptors are also positive, one can conclude that the compound having higher value of one of these descriptors will be retained in the stationary phase longer. The review of literature revealed that this observation is in agreement with the QSRR results of various authors [12,43].…”
Section: Resultssupporting
confidence: 90%
See 1 more Smart Citation
“…Taking into account, that the correlation parameters related to these descriptors are also positive, one can conclude that the compound having higher value of one of these descriptors will be retained in the stationary phase longer. The review of literature revealed that this observation is in agreement with the QSRR results of various authors [12,43].…”
Section: Resultssupporting
confidence: 90%
“…This can be achieved by combination of chemometric techniques and analytical routine with emerging instruments, such as high resolution mass spectrometry. For the above purpose the quantitative structure-retention relationship (QSRR) modeling, seems to be one of the best choices from the variety of chemometric methods [11][12][13].…”
Section: Introductionmentioning
confidence: 99%
“…Larger values of the ClogP will result in longer retention times of the molecules. It is not surprising that ClogP was selected as a significant feature since the partitioning of a compound between liquid aqueous and organic phases is related to the solute's partition equilibrium between analytes and immobilized artificial membrane [31]. From the above discussion, it can be seen that all the descriptors involved in the model have physical and chemical meanings, and these descriptors can account for the structural features responsible for the retention behavior of the drugs in IAM chromatography.…”
Section: Discussion Of the Selected Descriptorsmentioning
confidence: 99%
“…It usually produces correlations two to five times faster than other methods, such as principal component analysis (PCA), genetic algorithm (GA) with comparable quality (Consonni et al, 2002;Jackson, 1991;Schefzick et al, 2004). The HM can either quickly give a good estimation about what quality of correlation to expect from the data, or derive several best regression models.…”
Section: Theory Of Hmmentioning
confidence: 99%