Wensheng Cai

A Toolkit for the Analysis of Free-Energy Perturbation Calculations.

As computational power inexorably continues to grow, harnessing the capabilities of novel processing units and architectures, free-energy calculations are progressively brought to the level of routine modeling tools for exploring the thermodynamic properties of increasingly larger molecular assemblies. Within these premises, free-energy perturbation (FEP) arguably represents the most commonly chosen approach for tackling transformations of a chemical nature between thermodynamic states. To augment the accuracy, the precision, and, hence, the reliability of these calculations, a number of good practices have been established. In the present contribution, a new toolkit, coined ParseFEP, is proposed to follow these prescriptions in a user-friendly environment. Written as a Tcl plugin, it allows FEP calculations carried out using the popular molecular-dynamics package NAMD to be analyzed seamlessly within the visualization platform VMD. The potential of the toolkit is probed through a number of illustrative examples, which demonstrate cogently how pathological cases, often related to convergence issues, can be detected and remedied by means of a pictorial approach.

An improved boosting partial least squares method for near-infrared spectroscopic quantitative analysis

Boosting partial least squares (PLS) has been used for regression to improve the predictive accuracy of PLS models, however, there are still problems when the outliers exist in the calibration dataset. To make the method robust and enhance its prediction ability, an improved boosting PLS is proposed and applied in quantitative analysis of near-infrared (NIR) spectral datasets. In the method, a robust step is added to weaken the effect of the outliers on the model. On the other hand, the loss function defined with relative errors is suggested for updating the sampling weight during the boosting procedure. In addition, the ensemble prediction by the weighted mean of the models in the boosting series is found to be more effective than the commonly used weighted median. The performance of the improved method is tested with two large NIR datasets of industrial production. The method was found to have a marked superiority in robustness and prediction ability, particularly when outliers exist.

Multivariate calibration methods in near infrared spectroscopic analysis

Near infrared (NIR) spectroscopy has been demonstrated as a powerful technique for both qualitative and quantitative analysis of complex systems in various fields. Calibration, however, is one of the important techniques needed to ensure the quality and practicability of the analyses. In this mini-review, recent developments in multivariate calibration methods for NIR spectroscopic analysis, including non-linear approaches and ensemble techniques, are briefly summarized. The advantages and disadvantages of these methods are compared and discussed critically.

Rapid and nondestructive analysis of pharmaceutical products using near-infrared diffuse reflectance spectroscopy

Near-infrared diffuse reflectance spectroscopy (NIRDRS) was applied to classification and quantification of azithromycin tablets with the aid of chemometric multivariate analysis. Repeatability was investigated by repeated measurements, and the effect of morphology was examined by preparing the tablets in four forms, i.e. tablet product, tablet without coating, powder of tablet without coating, and powder of tablet. Furthermore, baseline elimination by continuous wavelet transform (CWT) and wavenumber selection was discussed for improving the repeatability and accuracy of the method. The results show that the spectra of the samples in the four forms can be measured with an acceptable repeatability, and classification of manufacture sites and quantitative analysis of the active pharmaceutical ingredient (API) can be achieved by principal component analysis (PCA) and partial least squares (PLS) regression, respectively. More importantly, baseline elimination and wavenumber selection can significantly simplify the calculation and improve the results.

Simultaneous determination of heavy metal ions in water using near-infrared spectroscopy with preconcentration by nano-hydroxyapatite

A method for simultaneous determination of metal ions in river water was developed by using preconcentration and near-infrared diffuse reflectance spectroscopy (NIRDRS). An inorganic biomaterial, nano-hydroxyapatite (HAP) was used as a high-efficient adsorbent for gathering the ions from water samples. After adsorbing the analytes onto the adsorbent, NIRDRS was measured and partial least squares (PLS) models were established for fast and simultaneous quantitative prediction. With the samples prepared by river water, determination of Pb(2+), Zn(2+), Cu(2+), Cd(2+) and Cr(3+) was investigated. The calibration models of Cu(2+), Cr(3+) and total content were proven to be efficient enough for precise prediction. The determination coefficients (R(2)) of the independent validation were found as high as 0.9924, 0.9869 and 0.9273 for Cu(2+), Cr(3+) and total content, respectively. Therefore, the feasibility of NIRDRS for microanalysis of heavy metal ions in waste water was demonstrated.

Standardization of near infrared spectra measured on multi-instrument

Calibration model transfer is essential for practical applications of near infrared (NIR) spectroscopy because the measurements of the spectra may be performed on different instruments and the difference between the instruments must be corrected. An approach for calibration transfer based on alternating trilinear decomposition (ATLD) algorithm is proposed in this work. From the three-way spectral matrix measured on different instruments, the relative intensity of concentration, spectrum and instrument is obtained using trilinear decomposition. Because the relative intensity of instrument is a reflection of the spectral difference between instruments, the spectra measured on different instruments can be standardized by a correction of the coefficients in the relative intensity. Two NIR datasets of corn and tobacco leaf samples measured with three instruments are used to test the performance of the method. The results show that, for both the datasets, the spectra measured on one instrument can be correctly predicted using the partial least squares (PLS) models built with the spectra measured on the other instruments.

Quantitative determination by temperature dependent near-infrared spectra.

Near-infrared (NIR) spectra are sensitive to the variation of experimental conditions, such as temperature. In this work, the relationship between NIR absorption spectra and temperature was quantitatively analyzed and applied to the quantitative determination of the compositions in mixtures. It was found that, for the solvents such as water and ethanol, a quantitative spectra-temperature relationship (QSTR) model between NIR spectra and temperature can be established by using partial least squares (PLS) regression. Therefore, the temperature of a solution can be predicted by using the model and NIR spectrum. Furthermore, it was also found that the difference between the predicted results of different solutions is a quantitative reflection of concentration. The variation of intercept in the relationship of the predicted and measured temperature can be used to determine the concentration of the compositions. The mixtures of water, methanol, ethanol and ethylenediamine in a concentration range of 5-80% (v/v) were studied. The calibration curves are found to be reliable with the correlation coefficients (R) higher than 0.99. Both the QSTR and calibration model may extend the application of NIR spectroscopy and provide novel techniques for analytical chemistry.

Adsorption behavior of hydrophobin proteins on polydimethylsiloxane substrates.

The design of a bioactive surface with appropriate wettability for effective protein immobilization has attracted much attention. Previous experiments showed that the adsorption of hydrophobic protein HFBI onto a polydimethylsiloxane (PDMS) substrate surface can reverse the inherent hydrophobicity of the surface, hence making it suitable for immobilization of a secondary protein. In this study, atomistic molecular dynamics simulations have been conducted to elucidate the adsorption mechanism of HFBI on the PDMS substrate in an aqueous environment. Nine independent simulations starting from three representative initial orientations of HFBI toward the solid surface were performed, resulting in different adsorption modes. The main secondary structures of the protein in each mode are found to be preserved in the entire course of adsorption due to the four disulfide bonds. The relative binding free energies of the different adsorption modes were calculated, showing that the mode, in which the binding residues of HFBI fully come from its hydrophobic patch, is most energetically favored. In this favorable binding mode, the hydrophilic region of HFBI is fully exposed to water, leading to a high hydrophilicity of the modified PDMS surface, consistent with experiments. Furthermore, a set of residues consisting of Leu12, Leu24, Leu26, Ile27, Ala66, and Leu68 were found to play an important role in the adsorption of HFBI on different hydrophobic substrates, irrespective of the structural features of the substrates.

Structural characterization of micelles formed of cholesteryl-functionalized cyclodextrins.

Amphiphilic cholesteryl 2,6-di-O-methyl-β-cyclodextrins (chol-DIMEB) can self-aggregate into spherical micelles of noteworthy potential for drug delivery. All-atom molecular dynamics simulations of chol-DIMEB micelles consisting of 3-24 monomers have been performed in aqueous solution. chol-DIMEB exhibits a pronounced tendency to self-assemble into core-shell structures. van der Waals interactions within the cholesteryl nucleus constitute the main driving force responsible for the formation of the micelle. The calculated radii of the hydrophobic core and of the hydrophilic shell for the micellar structure formed by 24 monomers agree well with the experiment. The cyclodextrin moieties are found to be exposed toward the aqueous medium and possess the appropriate flexibility to capture drugs in an effective fashion. Analysis of the solvent accessible surface area and hydration number indicates that the micelles are highly hydrosoluble species and can, therefore, enhance significantly the aqueous solubility of lipophilic drugs. In addition, the spatial structure of the micelles is suggestive of multiple potential drug binding sites. The present contribution unveils how micelles endowed with specific characteristics can form, while opening exciting perspectives for the design of novel micellar nanoparticles envisioned to be drug carriers of high potential.

Sonoporation at Small and Large Length Scales: Effect of Cavitation Bubble Collapse on Membranes

Ultrasound has emerged as a promising means to effect controlled delivery of therapeutic agents through cell membranes. One possible mechanism that explains the enhanced permeability of lipid bilayers is the fast contraction of cavitation bubbles produced on the membrane surface, thereby generating large impulses, which, in turn, enhance the permeability of the bilayer to small molecules. In the present contribution, we investigate the collapse of bubbles of different diameters, using atomistic and coarse-grained molecular dynamics simulations to calculate the force exerted on the membrane. The total impulse can be computed rigorously in numerical simulations, revealing a superlinear dependence of the impulse on the radius of the bubble. The collapse affects the structure of a nearby immobilized membrane, and leads to partial membrane invagination and increased water permeation. The results of the present study are envisioned to help optimize the use of ultrasound, notably for the delivery of drugs.