Retention prediction of analytes in reversed-phase high-performance liquid chromatography based on molecular structure

Smith, Roger M.; Burr, Christina M.

doi:10.1016/s0021-9673(01)89664-3

Cited by 38 publications

(6 citation statements)

References 13 publications

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“…These included mainly aromatic derivatives such as phenols, anilines, phenones, halobenzenes, nitrobenzenes, alkylbenzenes, and esters and also several aliphatic compounds such as alkanes and alcohols. The p values for 152 compounds were calculated from retention data published by Smith and Burr, which were determined in a Spherisorb ODS-2 (100 × 5 mm) column using several acetonitrile−water mobile phases buffered at pH 7. − For other 63 compounds, p values were calculated from the data published by Hanai and Hubert obtained in ERC-1000 ODS (150 × 6 mm), Develosil ODS-5 (150 × 4.6 mm), or Unisil Q C 18 (150 × 4.1 mm) columns and acetonitrile−water mobile phases − and by Rosés and Bosch in a LiChrospher 100 RP-18 (100 × 5 mm) column, using acetonitrile−water mobile phases too . All these values were transferred to the Smith and Burr chromatographic system by linear regression .…”

Section: Data and Computational Methodsmentioning

confidence: 99%

“…Therefore, a reference chromatographic system to refer p values obtained in different column/mobile phase arrangements was established . This reference data set was selected from the retention measurements of Smith and Burr in a Spherisorb ODS-2 column and acetonitrile/water mobile phases. − Thus, a wide database of more than 200 compounds of a different nature is now available. , Equation 1 and the described polarity parameters have demonstrated to be able to transfer successfully retention data between solvent systems and between columns …”

Section: Introductionmentioning

confidence: 99%

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A QSPR Study of the p Solute Polarity Parameter to Estimate Retention in HPLC

Bosque¹,

Sales²,

Bosch³

et al. 2003

J. Chem. Inf. Comput. Sci.

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A Quantitative Structure-Property Relationship (QSPR) model is developed to calculate the solute polarity parameter p of a set of 233 compounds of a very different chemical nature. The proposed model, derived from multiple linear regression, contains four descriptors calculated from the molecular structure and the well-known hydrophobicity parameter log P(o/w). According to the statistics obtained with the prediction set, the model has a very good prediction capacity (R(2) = 0.954, F = 889, n = 45, and SD = 0.27). The study shows that log P(o/w) and hydrogen bond acidity of the solutes are the most relevant descriptors to predict p values. This p parameter is embodied in a general equation to predict retention in reversed-phase liquid chromatography (RP-HPLC). It describes analyte retention exclusively on the basis of mobile phase/analyte/stationary phase polar interactions. Equations and procedures to determine polarity of both chromatographic phases had been successfully developed previously. Therefore, the proposed QSPR model for p estimation becomes a very useful tool in RP-HPLC optimization of procedures and methods in the everyday analytical work.

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Section: Data and Computational Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A QSPR Study of the p Solute Polarity Parameter to Estimate Retention in HPLC

Bosque¹,

Sales²,

Bosch³

et al. 2003

J. Chem. Inf. Comput. Sci.

View full text Add to dashboard Cite

show abstract

“…In order for this approach to be useful as a method for predicting the variation of solute retention as a function of the percent ACN, it must be able to predict log k values for solutes whose retention data were not used in the derivation of UNIFAC-derived S and log k s/w values. To test this, predicted log k values for six solutes whose retention data were not used in the derivation of best-fit log k s/w values are plotted against experimental values [72][73][74] in Figure 7. While the number of data used for comparison is small, the agreement is on the whole satisfactory and shows that the method can be extended to solutes not in the training set.…”

Section: Correlation Of Best-fit Log K S/w With Uni-fac-based Log K S/wmentioning

confidence: 99%

Solvent Strength Parameters and Retention Factors in Pure Water Using UNIFAC-Predicted Activity Coefficients

Park

Jung

Vitha

et al. 2003

Ind. Eng. Chem. Res.

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It is well-known in reversed-phase liquid chromatography that the solute retention factor (k) in binary eluents is well modeled as a quasi-linear function of the eluent composition (Φ) by the equation log k ) log k s/w -SΦ, where the solute parameters k s/w and S are the retention factor in pure water and the solvent strength parameter, respectively, and Φ is the volume fraction of the organic component of the eluent. S is related to the free energy of the solute transfer from water to bulk organic liquid, which in turn is related to the infinite-dilution activity coefficients (γ ∞ ) of the solute in water and bulk organic liquid. We report that the γ ∞ values obtained from a γ ∞ prediction model, UNIFAC, can be used to predict S directly and also to aid in the determination of best-fit k s/w values for acetonitrile-water mobile-phase systems. More specifically, UNIFAC-based S values combined with experimentally determined k s/w values for a limited set of solutes can be used to predict the variations in retention as a function of mobile-phase composition in acetonitrile-water systems within the calibration range for solutes that were not in the original data set.

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“…The Quantitative Structure-Activity Relationship (QSAR) program implements expert system technology together with molecular and structural theories to predict trends of the target compounds in either biological activity, [77][78][79][80][81]132,158,159 or chromatographic behavior. 35,[82][83][84][85] Klopman et al have studied relationships between substructures and bioactivities. 132,77 The META program was developed to predict the sites of potential enzymatic attack and the nature of the chemicals formed by such metabolic transformations.…”

Section: Expert System Applications In the Chemistry Domainmentioning

confidence: 99%

“…79,80 The expert system CRIPES was developed to predict retention time properties of organic molecules in reversed-phase HPLC using indices based on an alkyl-aryl-ketone scale derived from empirical quadratic expressions. 84 Smart Chemical Database Systems. Traditional ways of using database systems only for data and information storage and retrieval can no longer satisfy the growing demand from real world situations.…”

Section: Expert System Applications In the Chemistry Domainmentioning

confidence: 99%

Expert Systems and Analytical Chemistry: Recent Progress in the ACexpert Project

Zhu

Stillman

1996

J. Chem. Inf. Comput. Sci.

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In this paper we discuss the application of expert system technology in the analytical chemistry domain and summarizes the progress made in the implementation of the ACexpert project. We start with a brief description of the software tools that are commonly used in construction of expert system applications as well as the inference mechanisms employed to search the knowledge base. A brief review of the achievements made world wide during the past five years in the development of expert systems for use in the chemistry domain follows. This paper particularly addresses the difficulties found in the knowledge acquisition process. An effective knowledge encoding scheme, named the knowledge domain matrix process (KDM), that has been developed in our laboratory as an knowledge encoding alternative, is described. In the final section, we describe the development of several stand-alone expert system modules based on implementation of the KDM scheme within the framework of the ACexpert project. The importance of the user interface in an expert system program is also emphasized, and graphical user interfaces featuring icons, pull-down menus, and graphical descriptions have been developed for the different modules in the ACexpert project to ensure a user-friendly and self-explanatory environment.

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Retention prediction of analytes in reversed-phase high-performance liquid chromatography based on molecular structure

Cited by 38 publications

References 13 publications

A QSPR Study of the p Solute Polarity Parameter to Estimate Retention in HPLC

A QSPR Study of the p Solute Polarity Parameter to Estimate Retention in HPLC

Solvent Strength Parameters and Retention Factors in Pure Water Using UNIFAC-Predicted Activity Coefficients

Expert Systems and Analytical Chemistry: Recent Progress in the ACexpert Project

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