3D-QSAR and molecular docking study of LRRK2 kinase inhibitors by CoMFA and CoMSIA methods

Three-dimensional quantitative structure–activity relationship (3D-QSAR) modelling was conducted on a series of leucine-rich repeat kinase 2 (LRRK2) antagonists using CoMFA and CoMSIA methods. The data set, which consisted of 37 molecules, was divided into training and test subsets by using a hierarchical clustering method. Both CoMFA and CoMSIA models were derived using a training set on the basis of the common substructure-based alignment. The optimum PLS model built by CoMFA and CoMSIA provided satisfactory statistical results (q² = 0.589 and r² = 0.927 and q² = 0.473 and r² = 0.802, respectively). The external predictive ability of the models was evaluated by using seven compounds. Moreover, an external evaluation set with known experimental data was used to evaluate the external predictive ability of the porposed models. The statistical parameters indicated that CoMFA (after region focusing) has high predictive ability in comparison with standard CoMFA and CoMSIA models. Molecular docking was also performed on the most active compound to investigate the existence of interactions between the most active inhibitor and the LRRK2 receptor. Based on the obtained results and CoMFA contour maps, some features were introduced to provide useful insights for designing novel and potent LRRK2 inhibitors.     

Identification and in vitro antioxidant activities of phenolic compounds isolated from Cynoglossum cheirifolium L.

In an extensive search for bioactive compounds from plant sources, the quantitative and qualitative characterisation of the compounds present in Cynoglossum cheirifolium extracts was studied. Total phenolic and flavonoid contents were determined by spectrophotometric techniques. In vitro antioxidant and radical scavenging profiling was determined through DPPH^? scavenging activity and Ferric reducing antioxidant power (FRAP). Our study showed that leaves produce more phenolic compounds, followed by flowering aerial part. The butanolic fraction obtained from leaves extract exhibited the highest total phenolics (78.65 ± 3.58 mg GAE/g DW) and flavonoids (22.15 ± 4.66 mg CE/g DW). In contrast, this fraction displayed the highest DPPH^? scavenging ability with IC₅₀ values of 0.06 ± 0.003 mg/mL. The RP-HPLC-PDA analysis of phenolic compounds from leaves of C. cheirifolium lets to identify: rosmarinic acid, ferulic acid, caffeic acid, p-coumaric acid, syringic acid, sinapic acid and rutin. The obtained results indicate that this plant represent a valuable source of natural antioxidants.     

Cross fitted partial least squares (CF‐PLS): an alternative algorithm for a more reliable PLS

This paper presents a modified version of the NIPALS algorithm for PLS regression with one single response variable. This version, denoted a CF‐PLS, provides significant advantages over the standard PLS. First of all, it strongly reduces the over‐fit of the regression. Secondly, R² for the null hypothesis follows a Beta distribution only function of the number of observations, which allows the use of a probabilistic framework to test the validity of a component. Thirdly, the models generated with CF‐PLS have comparable if not better prediction ability than the models fitted with NIPALS. Finally, the scores and loadings of the CF‐PLS are directly related to the R², which makes the model and its interpretation more reliable. Copyright © 2011 John Wiley & Sons, Ltd.     

Determination of polyphenols in oats by near-infrared spectroscopy (NIRS) and two-dimensional correlation spectroscopy

Two-dimensional correlation spectroscopy (2DCOS) and near-infrared spectroscopy (NIRS) were used to determine the polyphenol content in oat grain. A partial least squares (PLS) algorithm was used to perform the calibration. A total of 116 representative oat samples from four locations in China were prepared and the corresponding near-infrared spectra were measured. Two-dimensional correlation spectroscopy was employed to select wavelength bands for the PLS regression model for the polyphenol determination. The number of PLS components and intervals was optimized according to the coefficients of determination (R²) and root mean square error of cross validation (RMSECV) in the calibration set. The performance of the final model was evaluated using the correlation coefficient (R) and the root mean square error of validation (RMSEV) in the prediction set. The results showed the band corresponding to the optimal calibration model was between 1350 and 1848?nm and the optimal spectral preprocessing combination was second derivative with second smoothing. The optimal regression model was obtained with an R² of 0.8954 and an RMSECV of 0.06651 in the calibration set and R of 0.9614 and RMSEV of 0.04573 in the prediction set. These measurements reveal the calibration model had qualified predictive accuracy. The results demonstrated that the 2DCOS with PLS was a simple and rapid method for the quantitative determination of polyphenols in oats.     

QSAR modeling of antiradical and antioxidant activities of flavonoids using electrotopological state (E-State) atom parameters

In the present paper QSAR modeling using electrotopological state atom (E-state) parameters has been attempted to determine the antiradical and the antioxidant activities of flavonoids in two model systems reported by Burda et al. (2001). The antiradical property of a methanolic solution of 1, 1-diphenyl-2-picrylhydrazyl (DPPH) and the antioxidant activity of flavonoids in a β-carotenelinoleic acid were the two model systems studied. Different statistical tools used in this communication are stepwise regression analysis, multiple linear regressions with factor analysis as the preprocessing step for variable selection (FA-MLR) and partial least squares analysis (PLS). In both the activities the best equation is obtained from stepwise regression analysis, considering, both equation statistics and predictive ability (antiradical activity: R ² = 0.927, Q² = 0.871 and antioxidant activity: R ² = 0.901, Q² = 0.841).      

Cytotoxicity and 2D-QSAR study of some heterocyclic compounds

Herein we have studied the cytotoxicity and quantitative structure–activity relationship (QSAR) of heterocyclic compounds containing cyclic urea and thiourea nuclei. A set of 22 hydantoin and thiohydantoin related heterocyclic compounds were investigated with respect to their LC₅₀ values (Log of LC₅₀) against brine shrimp lethality bioassay in order to derive the 2D-QSAR models using MLR, PLS and ANN methods. The best predictive models by MLR, PLS and ANN methods gave highly significant square correlation coefficient (R²) values of 0.83, 0.81 and 0.91 respectively. The model also exhibited good predictive power confirmed by the high value of cross validated correlation coefficient Q² (0.74).     

On estimation of multivariate prediction regions in partial least squares regression

The estimation of the prediction region of partial least squares (PLS) is necessary in many engineering applications. However, research in this area focuses on the estimation of prediction intervals only. In this work, a new recursive formulation of PLS is proposed to facilitate the calculation of the Jacobian matrix of the estimated coefficient matrix. Furthermore, the computational complexity analysis indicates that the proposed algorithm is O(m²N + mpN + mpN² + mN³ + mpN⁴) per number of component. The prediction region of the multivariate PLS is obtained through local linearization. The new formulation provides one way to obtain the prediction region of the multivariate PLS. Simulation and near‐infrared spectra of corn case studies indicate the utility of the proposed method. Copyright © 2013 John Wiley & Sons, Ltd.     

Direct determination of polymerized triglycerides in deep-frying olive oil by attenuated total reflectance–Fourier transform infrared spectroscopy using partial least squares regression

A partial least squares (PLS) regression model based on attenuated total reflectance–Fourier transform infrared spectra of heated olive oil samples has been developed for the determination of polymerized triacylglycerides (PTGs) generated during thermal treatment of oil. Three different approaches for selection of the spectral regions used to build the PLS model were tested and compared: (1) variable selection based on expert knowledge, (2) uninformative variable elimination PLS, and (3) interval PLS. Each of the three variable selection methods provided PLS models from heated olive oil samples with excellent performance for the prediction of PTGs in fried olive oils with comparable model statistics. However, besides a high coefficient of determination (R ² of 0.991) and low calibration, validation, and prediction errors of 1.14%, 1.21%, and 1.40% w/w, respectively, variable selection based on expert knowledge gave additionally almost identical low calibration (−0.0017% w/w) and prediction (−0.0023% w/w) bias. Furthermore, it was verified that the determination of PTGs was not influenced by the type of foodstuff fried in the olive oil.     

The kinetics of condensation of phenolic polyflavonoid tannins with aldehydes

The rate constants and free energies of activation of the acid-and base-catalyzed reactions of floroglucinolic and resorcinolic flavonoid A rings of pine and wattle tannins, respectively, as well as the model compounds resorcinol, floroglucinol, and catechol, with formaldehyde, acetaldehyde, propionaldehyde, n-butyraldehyde, isobutyraldehyde, and furfural, were obtained. Second-order kinetics were found to fit these reactions. Indication and proof of the existence of unstable aldehyde ether bridges and their fast rearrangement at ambient temperature to alkyl bridges for fast-reacting phenols or phenolic compounds, such as tannins, were obtained for the first time. The dependence of the reaction kinetics on the concentration of OH- catalyst was investigated. Anomalies in the behavior of wattle tannin with aldehydes and n-butyraldehyde with phenols were observed and partially explained. The results led to a slightly different interpretation of the wattle tannin flavonoid structure.