Prediction of Electrophoretic Mobilities. 1. Monoamines

Fu, Shilin; Lucy, Charles A.

doi:10.1021/ac9706638

Cited by 61 publications

(65 citation statements)

References 31 publications

(44 reference statements)

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“…Only three poorly-resolved Fig. 5 illustrates the isocratic CEC separation of peaks were obtained by this method (data not q is the net charge of the peptide calculated using the Henderson-Hasselbach equation [36] and adjusted pK values for associated amino acids [37], and M is a r the molecular mass [37,38]. The predicted migration order was normalized as described above for the predicted retention order.…”

Section: Separation Of Basic Bioactive Peptidesmentioning

confidence: 99%

Rapid Ultrasensitive Chemical-Fingerprint Detection of Chemical and Biochemical Warfare Agents

Ashby¹,

Shepodd²,

Yelton³

et al. 2002

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Vibrational spectra can serve as chemical fingerprints for positive identification of chemical and biological warfare molecules. The required speed and sensitivity might be achieved with surface-enhanced Raman spectroscopy (SERS) using nanotextured metal surfaces. Systematic and reproducible methods for preparing metallic surfaces that maximize sensitivity have not been previously developed. This work sought to develop methods for forming highefficiency metallic nanostructures that can be integrated with either gas or liquidphase chem-lab-on-a-chip separation columns to provide a highly sensitive, highly selective microanalytical system for detecting current and future chem/bio agents. In addition, improved protein microchromatographic systems have been made by the creation of acrylate-based porous polymer monoliths that can serve as protein preconcentrators to reduce the optical system sensitivity required to detect and identify a particular protein, such as a bacterial toxin. 6 Executive SummaryUnambiguous identification of chemicals and biochemicals usable as chem/ bio weapons (CBW) is essential at nanomolar levels with short analysis times (<5 min.) Vibrational spectra can serve as chemical fingerprints for positive identification of CBW molecules. The required speed and sensitivity might be achieved with surface-enhanced Raman spectroscopy (SERS) using nanotextured metal surfaces. Although ordinary SERS produces sensitivity enhancements on the order of 10 3 vs. normal Raman spectroscopy, a properly nanotextured metal surface can increase sensitivity up to 10 14 -fold.Systematic and reproducible methods for preparing stationary metallic surfaces that maximize sensitivity have not been previously developed. This LDRD program was to investigate the integration of chemical-fingerprint identification of CBW molecules using SERS as the detector in the chip-scale microseparation columns developed under the Sandia MicroChemLab program. To this end, this program was to develop methods for forming high-efficiency metallic nanostructures that could be integrated with either gas or liquid-phase chem-lab-on-a-chip separation columns to provide a highly sensitive, highly selective microanalytical system for detecting current and future chem/bio agents. In addition to speed and sensitivity, the chemical fingerprinting provided by SERS would enable rapid identification of new, non-standard CBW agents that might be introduced to avoid detection by established sensor systems.Improved methods for on-chip separation of biomolecules, such as proteins, were a prerequisite for the application of SERS as a detector in microchromatograpic systems. Chromatographic separation media based on porous polymer monoliths were to be developed in this program to insure efficient separation and purification of proteins, such as biotoxins, prior to their detection and identification using SERS.The goals of this LDRD were three-fold: 1) Development of a manufacturable surface that possessed a very high density of metallic nanostructure...

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Section: Separation Of Basic Bioactive Peptidesmentioning

confidence: 99%

Rapid Ultrasensitive Chemical-Fingerprint Detection of Chemical and Biochemical Warfare Agents

Ashby¹,

Shepodd²,

Yelton³

et al. 2002

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“…Based on the published reports, two principal methods can be summarized, i.e., the mechanistic and the statistical methods. The mechanistic models are closely related to the mechanism of electrophoretic separation [2][3][4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Quantitative structure–mobility relationship study of a diverse set of organic acids using classification and regression trees and adaptive neuro‐fuzzy inference systems

Jalali‐Heravi

Shahbazikhah

2008

Electrophoresis

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A quantitative structure-mobility relationship was developed to accurately predict the electrophoretic mobility of organic acids. The absolute electrophoretic mobilities (mu(0)) of a diverse dataset consisting of 115 carboxylic and sulfonic acids were investigated. A set of 1195 zero- to three-dimensional descriptors representing various structural characteristics was calculated for each molecule in the dataset. Classification and regression trees were successfully used as a descriptor selection method. Four descriptors were selected and used as inputs for adaptive neuro-fuzzy inference system. The root mean square errors for the calibration and prediction sets are 1.61 and 2.27, respectively, compared with 3.60 and 3.93, obtained from a previous mechanistic model.

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“…8 In addition, a number of methods of predicting µep have been reported. [9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28] The molecular weights (MW) have been reported to correspond to the µep values for amides. [9][10][11][12][13][14] In addition, for some organic and metal complex ions, the MWs correspond to the µep values.…”

Section: Introductionmentioning

confidence: 99%

“…[24][25][26] The effects of the µep values on the friction coefficients for small charged molecules to oligomers with carboxylate and sulfonate groups have also been reported. 27 The friction coefficients of carboxylate and sulfonate groups similarly contributed to the µep values, since the electric charge was thought to more heavily influence the µep values than the The capillary electrophoretic behavior of 44 aromatic organic ions was investigated.…”

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confidence: 98%

Relation between Electrophoretic Behavior and Molecular Shapes of Aromatic Anions

et al. 2004

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Capillary electrophoresis (CE) has been applied to the separation of various analyte ions. [1][2][3][4][5][6] Theoretically, the capillary electrophoretic mobility (µep) is calculated bywhere q, η and r are the electric charge of the ionized solute, the buffer viscosity and the solute radius, respectively. 7 Therefore, the CE separation of analyte ions is primarily dependent on the ionic charge and the ionic radius, unless there are any other interactions in the analyte ions, such as those with the capillary wall or counterions. When the ionic shape is not spherical, it is difficult to predict µep from Eq. (1). In addition, the Stokes radius of the ion is necessary in order to determine the r-value. However, the observed µep values of non-spherical ions are expected to provide some information regarding the ionic shapes.Factors affecting the selectivity of inorganic anions have been reviewed. 8 In addition, a number of methods of predicting µep have been reported. [9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28] The molecular weights (MW) have been reported to correspond to the µep values for amides. [9][10][11][12][13][14] In addition, for some organic and metal complex ions, the MWs correspond to the µep values. 15 The MW value is thought to depend on the molecular volume; therefore, it could be used as an index of molecular size. However, the separation of a number of aminonaphthalenesulfonate ions having the same molecular weight and electric charge at pH 9.2 has been accomplished. 16 Moreover, empirically good linear relationships between the µep values and MW -2/3 have been reported. [10][11][12][13][14] The MW 1/3 value indirectly corresponds to the third power of the molecular volume, that is, the r-value, because the MW value generally depends on the molecular volume. Therefore, the MW -2/3 value indirectly corresponds to r -2. In other words, the r -2 -values show a good linear relationship with the µep values. A correlation between the µep values for the localized electric charge of non-spherical aromatic anions with the MW -2/3 and r -2 -values has yet to be reported. Accordingly, the MW -2/3 and r -2 -values were evaluated as the indexes to determine whether or not they would be a useful means of predicting the µep values of these anions.A simulation of the µep values with the pH of the buffer has been reported for phenolic acids. 17,18 In addition, a simulation of the µep values with the pH and the 2-hydroxyisobutyric acid (HIBA) concentration of the buffer has been reported for metal HIBA complex ions. 19The effects of the µep values on a number of water-soluble organic solvents (such as methanol) for aromatic carboxylates with various functional groups (such as hydroxyl groups) have been reported. [20][21][22][23] These results showed that the differing viscosities of the buffers and the differing pKas for phenolic acids and aromatic carboxylates largely influenced the µep values. Although it has been reported that the change in the Walden product (µepη) value is de...

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Prediction of Electrophoretic Mobilities. 1. Monoamines

Cited by 61 publications

References 31 publications

Rapid Ultrasensitive Chemical-Fingerprint Detection of Chemical and Biochemical Warfare Agents

Rapid Ultrasensitive Chemical-Fingerprint Detection of Chemical and Biochemical Warfare Agents

Quantitative structure–mobility relationship study of a diverse set of organic acids using classification and regression trees and adaptive neuro‐fuzzy inference systems

Relation between Electrophoretic Behavior and Molecular Shapes of Aromatic Anions

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