Peak Capacity Optimization of Peptide Separations in Reversed-Phase Gradient Elution Chromatography: Fixed Column Format
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- 作者：Xiaoli Wang ; Dwight R. Stoll ; Adam P. Schellinger ; and Peter W. Carr
- 刊名：Analytical Chemistry
- 出版年：2006
- 出版时间：May 15, 2006
- 年：2006
- 卷：78
- 期：10
- 页码：3406 - 3416
- 全文大小：252K
- 年卷期：v.78,no.10(May 15, 2006)
- ISSN：1520-6882
文摘
The optimization of peak capacity in gradient elutionRPLC is essential for the separation of multicomponentsamples such as those encountered in proteomic research. In this work, we study the effect of gradient time(tG), flow rate (F), temperature (T), and final eluentstrength (
rs/phi.gif" BORDER=0 >final) on the peak capacity of separations ofpeptides that are representative of the range in peptidesfound in a tryptic digest. We find that there are very stronginteractions between the individual variables (e.g., flowrate and gradient time) which make the optimization quitecomplicated. On a given column, one should first set thegradient time to the longest tolerable and then set thetemperature to the highest achievable with the instrument.Next, the flow rate should be optimized using a reasonablebut arbitrary value of rs/phi.gif" BORDER=0 >final. Last, the final eluent strengthshould be adjusted so that the last solute elutes as closeas possible to the gradient time. We also develop an easilyimplemented, highly efficient, and effective Monte Carlosearch strategy to simultaneously optimize all the variables. We find that gradient steepness is an importantparameter that influences peak capacity and an optimumrange of gradient steepness exists in which the peakcapacity is maximized.
rs/phi.gif" BORDER=0 >final) on the peak capacity of separations ofpeptides that are representative of the range in peptidesfound in a tryptic digest. We find that there are very stronginteractions between the individual variables (e.g., flowrate and gradient time) which make the optimization quitecomplicated. On a given column, one should first set thegradient time to the longest tolerable and then set thetemperature to the highest achievable with the instrument.Next, the flow rate should be optimized using a reasonablebut arbitrary value of rs/phi.gif" BORDER=0 >final. Last, the final eluent strengthshould be adjusted so that the last solute elutes as closeas possible to the gradient time. We also develop an easilyimplemented, highly efficient, and effective Monte Carlosearch strategy to simultaneously optimize all the variables. We find that gradient steepness is an importantparameter that influences peak capacity and an optimumrange of gradient steepness exists in which the peakcapacity is maximized.