Biomedical subjects

Nihal Tugcu

Publications and source records attributed to Nihal Tugcu.

5 recordsLinked to original sources

PubMed2004

Parallel screening of selective and high-affinity displacers for proteins in ion-exchange systems.

This paper employs a parallel batch screening technique for the identification of both selective and high-affinity displacers for a model binary mixture of proteins in a cation-exchange system. A variety of molecules were screened as possible displacers for the proteins ribonuclease A (RNAseA) and alpha-chymotrypsinogen A (alpha-chyA) on high performance Sepharose SP. The batch screening data for each protein was used to select leads for selective and high-affinity displacers and column experiments were carried out to evaluate the performance of the selected leads. The data from the batch displacements was also employed to generate quantitative structure-efficacy relationship (QSER) models based on a support vector machine regression approach. The resulting models had high correlation coefficients and were able to predict the behaviour of molecules not included in the training set. The descriptors selected in the QSER models for both proteins were examined to provide insights into factors influencing displacer selectivity in ion-exchange systems. The results presented in this paper demonstrate that this parallel batch screening-QSER approach can be employed for the identification of selective and high-affinity displacers for protein mixtures.

Cation Exchange Resins↗

PubMed2003

Identification of chemically selective displacers using parallel batch screening experiments and quantitative structure efficacy relationship models.

Parallel batch screening experiments were carried out to examine how displacer chemistry and salt counterions affect the selectivity of batch protein displacements in anion exchange chromatographic systems. The results indicate that both salt type and displacer chemistry can have a significant impact on the amount of protein displaced. Importantly, the results indicate that, by changing the displacer, salt counterion, or both, one can induce significant selectivity changes in the relative displacement of two model proteins. This indicates that highly selective separations can be developed in ion exchange systems by the appropriate selection of displacer chemistry and salt counterion. The experimental batch screening data were also used in conjunction with various molecular descriptors to generate quantitative structure efficacy relationship (QSER) models based on a support vector machine feature selection and regression tool. The models resulted in good correlations and successful predictions for an external test set of displacers. A star plot approach was shown to be a powerful tool to aid in the interpretation of the QSER models. These results indicate that this modeling approach can be employed for the a priori prediction of displacer efficacy as well as for providing insight into displacer design and the selection of proper mobile-phase conditions for highly selective separations.

Algorithms↗

PubMed2003

Prediction of the effect of mobile-phase salt type on protein retention and selectivity in anion exchange systems.

This study examines the effect of different salt types on protein retention and selectivity in anion exchange systems. Particularly, linear retention data for various proteins were obtained on two structurally different anion exchange stationary-phase materials in the presence of three salts with different counterions. The data indicated that the effects are, for the most part, nonspecific, although various specific effects could also be observed. Quantitative structure retention relationship (QSRR) models based on support vector machine feature selection and regression models were developed using the experimental chromatographic data in conjunction with various molecular descriptors computed from protein crystal structure geometries. Star plots for each descriptor used in the final model were generated to aid in interpretation. The resulting QSRR models were predictive, with cross-validated r2 values of 0.9445, 0.9676, and 0.8897 for Source 15Q and 0.9561, 0.9876, and 0.9760 for Q Sepharose resins in the presence of three different salts. The predictive power of these models was validated using a set of test proteins that were not used in the generation of these models. Interpretation of the models revealed that particular trends for proteins and salts could be captured using QSRR techniques.

Algorithms↗

PubMed2002

Stationary phase effects on the dynamic affinity of low-molecular-mass displacers.

In this paper, the selectivity of a variety of cation-exchange stationary phases was investigated using a homologous series of displacer molecules based on pentaerythritol. These displacers were derived from pentaerythritol and contained either four trimethyl ammonium groups [pentaerythrityl-(trimethylammonium chloride)4, PE(TMA)4], benzene rings [pentaerythrityl-(benzyl dimethylammonium chloride)4, PE(DMABzCl)4], heptyl groups [pentaerythrityl-(heptyl dimethylammonium iodide)4, PE(DMAHepI)4] or cyclohexyl groups [pentaerythrityl-(cyclohexyl dimethylammonium iodide)4, PE(DMACyI)4]. This series enabled us to probe the secondary interactions that can play a role in the affinity of low-molecular-mass displacers for different stationary phases. The relative affinities of these displacers were examined using a displacer ranking plot based on the steric mass action (SMA) isotherm model. While hydrophobicity and aromaticity played important roles in generating the affinity to the hydrophilized polystyrene-divinylbenzene (Source 15S) and polymethacrylate-based (Toyopearl 650M) resins, these secondary interactions had a minimal impact on the selectivity in agarose resins coated with dextran (SP Sepharose XL), "gel in a shell" (S Ceramic HyperD F), and monolithic (Bio-Rad Uno S6) cation-exchange materials. Further, the results with a tentacular stationary phase (Fractogel EMD) suggest that the alkyl chains on PE(DMAHepI)4 play an important role in increasing the affinity, possibly because of strong interactions between the alkyl moiety and the polymer matrix as well as between the charged groups and the polyelectrolyte tentacles. The results of this study provide insight into the design of high affinity, low-molecular-mass displacers for different cation-exchange stationary phase materials.

Cation Exchange Resins↗

PubMedDate not supplied

Prediction of protein retention times in anion-exchange chromatography systems using support vector regression.

Quantitative Structure-Retention Relationship (QSRR) models are developed for the prediction of protein retention times in anion-exchange chromatography systems. Topological, subdivided surface area, and TAE (Transferable Atom Equivalent) electron-density-based descriptors are computed directly for a set of proteins using molecular connectivity patterns and crystal structure geometries. A novel algorithm based on Support Vector Machine (SVM) regression has been employed to obtain predictive QSRR models using a two-step computational strategy. In the first step, a sparse linear SVM was utilized as a feature selection procedure to remove irrelevant or redundant information. Subsequently, the selected features were used to produce an ensemble of nonlinear SVM regression models that were combined using bootstrap aggregation (bagging) techniques, where various combinations of training and validation data sets were selected from the pool of available data. A visualization scheme (star plots) was used to display the relative importance of each selected descriptor in the final set of "bagged" models. Once these predictive models have been validated, they can be used as an automated prediction tool for virtual high-throughput screening (VHTS).

Anion Exchange Resins↗