"Sweet space" strategy for solvent system selection in countercurrent chromatography: A case study on separation of polyunsaturated fatty acids from borage oil.

This study presents a comprehensive strategy for the selection and optimization of solvent systems in countercurrent chromatography (CCC) for the effective separation of compounds. With a focus on traditional organic solvent systems, the research introduces a "sweet space" strategy that merges intuitive understanding with mathematical accuracy, addressing the significant challenges in solvent system selection, a critical bottleneck in the widespread application of CCC. By employing a combination of volume ratios and graphical representations, including both regular and trirectangular tetrahedron models, the proposed approach facilitates a more inclusive and user-friendly strategy for solvent system selection. This study demonstrates the potential of the proposed strategy through the successful separation of gamma-linolenic acid, oleic acid, and linoleic acid from borage oil, highlighting the strategy's effectiveness and practical applicability in CCC separations.

Nuclear magnetic resonance-based solvent system selection for counter-current chromatography separation of compounds present in the same high-performance liquid chromatography peak: Flavonoids in barley seedlings as an example.

Partition coefficient is a key parameter for counter-current chromatography separation. High-performance liquid chromatography (HPLC) is the most commonly used tool for the screening of partition coefficients. However, HPLC technology is not applicable to the compounds present in the same chromatographic peak. Nuclear magnetic resonance (NMR) technology could easily distinguish compounds according to their characteristic absorption even if they exist in the same HPLC peak. In this study, two flavonoids present in the same HPLC peak were successfully purified by counter-current chromatography with a solvent system screened by NMR to show the great potential of NMR technology in the screening of the partition coefficient of co-efflux compounds. Through NMR screening, an optimized ethyl acetate/n-buthanol/water (7:3:10, v/v/v) system was applied in this study. As a result, two flavonoids, including 4.8 mg of 3'-methoxyl-6'''-O-feruloylsaponarin and 9.8 mg of 6'''-O-feruloylsaponarin were separated from 15 mg of the mixture. There is only one methoxy group difference between the two flavonoids. This study provides a new strategy for the screening of counter-current chromatography solvent systems and broadens the application scope of counter-current chromatography.

Ab initio calculation based solvent system selection in silico for counter-current chromatography: Separation of resibufogenin glycosylation products.

In this study, a strategy based on COSMO-RS (Conductor-like Screening Model for Real Solvents) with a constrained optimization calculation was developed for ab initio calculation based solvent system selection in silico for counter-current chromatography. The separation of resibufogenin glycosylation products was selected as an example to show its practicability. The selected solvent system in silico gave the K values consistent with the experimentally measured data (RMSD=0.2861) and the glycosylation products, namely Resibufogenin-3-O-ß-D-glucoside (R-G) and Resibufogenin-3-O-ß-D-glucosyl (1→2)-ß-D-glucoside (R-2G), were successfully separated by HSCCC.

Sweet spot matching: A thin-layer chromatography-based countercurrent solvent system selection strategy.

TLC-based strategies were proposed in 1979 (Hostettmann et al.) and 2005 (Friesen & Pauli; GUESS method) to minimize the number of partitioning experiments required for countercurrent separation (CCS) solvent system selection. As semi-empirical approaches, both proposed that the K values defining the sweet spot of optimal CCS corresponded to a matching Rf value range from the silica gel TLC plate developed in the organic phase of a biphasic or a corresponding monophasic solvent system. Despite their simplicity, there has been an absence of theoretical support and a deficiency of reported experimental evidence. The present study explores the theory required to develop correlations between Rf and K. All theoretical models surmise that the optimal Rf value range should be centered at 0.5. In order to validate the feasibility of the concept of matching Rf and K values, 43 natural products and six solvent system families were investigated. Out of 62 correlations, 45 resulted in matched Rf and K values. Based on this study, practical guidelines for the TLC-based prediction strategy are provided. These approaches will equip CCS users with an updated understanding of how to apply the TLC-based solvent system selection strategy to accelerate a targeted selection of CCS conditions.

Enhancing silymarin fractionation using the conductor-like screening model for real solvents.

A significant hurdle for discovery of plant-derived products is the numerous trial-and-error experiments required to develop an effective purification strategy. To overcome the experimental burden, a quantum mechanics-based molecular modeling approach - known as the COnductor-like Screening Model for Real Solvents (COSMO-RS) - was used to predict a suitable two-phase solvent system to purify six silymarins from an aqueous mixture. Silymarins, a class of flavonolignans found in milk thistle (Silybum marianum L.), are well suited for assessing the use of a molecular modeling approach to predict partitioning in a countercurrent chromatography (CCC) separation because they are well characterized and previous studies report low purity fractionation in liquid-liquid solvent systems. They also present an opportunity to evaluate the use of COSMO-RS in predicting the partitioning of structurally similar isomeric compounds that are present together in an aqueous solution upon extraction from their native source. The COSMO-RS model results predicted the partition coefficients in: three traditional ARIZONA solvent systems (composed of heptane, ethyl acetate, methanol, and water), nine additional variations of this quaternary solvent system, and two chloroform, methanol, and water solvent systems. Predicted results were concise but not accurate when compared to experimental results determined by the shake flask method. The 1:4:3:5 n-heptane:ethyl acetate:methanol:water (v/v/v/v) system was identified to be an improvement on the 1:4:3:4 system previously reported. The present study verified the ability of COSMO-RS to hone in on one or two solvent systems that will yield the best fractionation using CCC.

Systematic and practical solvent system selection strategy based on the nonrandom two-liquid segment activity coefficient model for real-life counter-current chromatography separation.

Solvent system selection is the first step toward a successful counter-current chromatography (CCC) separation. This paper introduces a systematic and practical solvent system selection strategy based on the nonrandom two-liquid segment activity coefficient (NRTL-SAC) model, which is efficient in predicting the solute partition coefficient. Firstly, the application of the NRTL-SAC method was extended to the ethyl acetate/n-butanol/water and chloroform/methanol/water solvent system families. Moreover, the versatility and predictive capability of the NRTL-SAC method were investigated. The results indicate that the solute molecular parameters identified from hexane/ethyl acetate/methanol/water solvent system family are capable of predicting a large number of partition coefficients in several other different solvent system families. The NRTL-SAC strategy was further validated by successfully separating five components from Salvia plebeian R.Br. We therefore propose that NRTL-SAC is a promising high throughput method for rapid solvent system selection and highly adaptable to screen suitable solvent system for real-life CCC separation.

Using quantitative structure activity relationship models to predict an appropriate solvent system from a common solvent system family for countercurrent chromatography separation.

Countercurrent chromatography (CCC) is a form of liquid-liquid chromatography. It works by running one immiscible solvent (mobile phase) over another solvent (stationary phase) being held in a CCC column using centrifugal force. The concentration of compound in each phase is characterised by the partition coefficient (Kd), which is the concentration in the stationary phase divided by the concentration in the mobile phase. When Kd is between approximately 0.2 and 2, it is most likely that optimal separation will be achieved. Having the Kd in this range allows the compound enough time in the column to be separated without resulting in a broad peak and long run time. In this paper we report the development of quantitative structure activity relationship (QSAR) models to predict logKd. The QSAR models use only the molecule's 2D structure to predict the molecular property logKd.

Using nonrandom two-liquid model for solvent system selection in counter-current chromatography.

Selection of an appropriate solvent system is of great importance for a successful counter-current chromatography separation. In this work, the nonrandom two-liquid (NRTL) model, a thermodynamic method, was used for predicting the partition coefficient based on a few measured partition coefficients. The NRTL method provides quite satisfactory results for model solutes in first correlating measured partition coefficient in a few representative biphasic liquid systems and then successfully predicting partition coefficient in other two-phase liquid systems. According to the predicted partition coefficient, a suitable solvent system can be screened. Assisted with the NRTL method, the solvent system composed of hexane/ethyl acetate/methanol/water (1:4:1:4, v/v) was rapidly screened for the successful separation of two major compounds with high purity from Malus hupehensis leaves. The results demonstrated that the NRTL model can offer a simple and practical strategy to estimate partition coefficients in support of CCC solvent system selection, which will significantly minimize the experimental efforts and cost involved in solvent system selection.

Correlation and prediction of partition coefficient using nonrandom two-liquid segment activity coefficient model for solvent system selection in counter-current chromatography separation.

Selection of a suitable solvent system is the first and foremost step for a successful counter-current chromatography (CCC) separation. In this paper, a thermodynamic model, nonrandom two-liquid segment activity coefficient model (NRTL-SAC) which uses four types of conceptual segments to describe the effective surface interactions for each solvent and solute molecule, was employed to correlate and predict the partition coefficients (K) of a given compound in a specific solvent system. Then a suitable solvent system was selected according to the predicted partition coefficients. Three solvent system families, heptane/methanol/water, heptane/ethyl acetate/methanol/water (Arizona) and hexane/ethyl acetate/methanol/water, and several solutes were selected to investigate the effectiveness of the NRTL-SAC model for predicting the partition coefficients. Comparison between experimental results and predicted results showed that the NRTL-SAC model is of potential for estimating the K value of a given compound. Also a practical separation case on magnolol and honokiol suggests the NRTL-SAC model is effective, reliable and practical for the purpose of predicting partition coefficients and selecting a suitable solvent system for CCC separation.