Three-dimensional Quantitative Structure-property Relationship Research Articles

Exploring 3D-QSPR models of human skin permeability for a diverse dataset of chemical compounds

The control of permeation is vital not only for the topical application of lotions, creams, and ointments but also for the toxicological and risk assessment of materials from environmental and occupational hazards. To understand the effects of physicochemical properties of a variety of 211 compounds on skin permeability, we developed a three-dimensional quantitative structure-property relationship (3 D-QSPR) model. Alignment free GRid-INdependent Descriptors (GRINDs), which were derived from molecular interaction fields (MIFs) contributed to the regression models. Kennard–Stone algorithm was employed to split data set to a training set of 159 molecules and a test set of 52 molecules. Fractional factorial design (FFD), genetic algorithm (GA) and successive projection algorithm (SPA) were applied to select the most relevant 3 D molecular descriptors. The descriptors selected using various feature selection were correlated with skin permeability constants by partial least squares (PLS) and support vector machine (SVM). SPA-SVM model gave prominent statistical values with the correlation coefficient of = 0.96, Q2= 0.73 and R2pred=0.76. According to the analysis results, the hydrogen bonding donor and acceptor properties of the investigated compounds can influence the penetration into the human skin. Furthermore, it was found that permeability was enhanced by increasing the hydrophobicity and was diminished by increasing the molecular weight. In addition, the presence of hydrophobic groups in the target molecule, as well as their shape and position, can affect the skin permeability.

Catalytic performance of bis(imino)pyridine Fe/Co complexes toward ethylene polymerization by 2D‐/3D‐QSPR modeling

The two-dimensional and three-dimensional quantitative structure-property relationship (2D- and 3D-QSPR) approaches are applied to investigate the catalytic performance for a total data set of 55 bis(imino)pryridine iron and cobalt complexes, including the catalytic activity, molecular weight, and melting temperature of the product. The obtained models for the catalytic performance of interest exhibit good results by both 2D- and 3D-QSPR modeling, meanwhile higher predictive and validation powers observed in the 3D type. The modeling results indicate that the bulky substituents on ortho-position of the singular side phenyl ring and positive charge on para-position of the phenyl ring within the ligand are favorable to catalytic activity, while unfavorable to the molecular weight of product. Based on the obtained QSPR models, four new complexes are designed and predicted with good catalytic activity and very high molecular weight, which are in good agreement with our recent experimental report. © 2019 Wiley Periodicals, Inc.

Synthesis, Spectra, and Theoretical Investigations of 1,3,5-Triazines Compounds as Ultraviolet Rays Absorber Based on Time-Dependent Density Functional Calculations and three-Dimensional Quantitative Structure-Property Relationship.

A series of 1,3,5-triazines were synthesized and their UV absorption properties were tested. The computational chemistry methods were used to construct quantitative structure-property relationship (QSPR), which was used to computer aided design of new 1,3,5-triazines ultraviolet rays absorber compounds. The experimental UV absorption data are in good agreement with those predicted data using the Time-dependent density functional theory (TD-DFT) [B3LYP/6-311 + G(d,p)]. A suitable forecasting model (R > 0.8, P < 0.0001) was revealed. Predictive three-dimensional quantitative structure-property relationship (3D-QSPR) model was established using multifit molecular alignment rule of Sybyl program, which conclusion is consistent with the TD-DFT calculation. The exceptional photostability mechanism of such ultraviolet rays absorber compounds was studied and confirmed as principally banked upon their ability to undergo excited-state deactivation via an ultrafast excited-state proton transfer (ESIPT). The intramolecular hydrogen bond (IMHB) of 1,3,5-triazines compounds is the basis for the excited state proton transfer, which was explored by IR spectroscopy, UV spectra, structural and energetic aspects of different conformers and frontier molecular orbitals analysis.

Comparative molecular field analysis of chromatographic hydrophobicity indices for some coumarin analogs.

The chromatographic hydrophobicity index (CHI) is an HPLC-based parameter that provides reliable guidance in optimization of pharmacological efficiency and adsorption, distribution, metabolism and exertion (ADME) profile of drug candidates. In the present work, classical and three-dimensional quantitative structure-property relationship (QSPR) models were developed for prediction of CHI values of some 4-hydroxycoumarin analogs on immobilized artificial membrane column. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) as 3D-QSPR methods were performed to gain insight into the key structural factors affecting on the chromatographic hydrophobicity of interested chemicals. The calculated parameters of Q2 , R2 and standard error were 0.545, 0.996 and 0.773 for CoMFA model and 0.815, 0.986 and 1.44 for CoMSIA model, respectively. The contour maps for steric fields of the CoMFA model illustrate that the hydrophobicity of chemicals will be higher when the positions of R6, R7 and R8 in the 4-hydroxycuomarin ring are substituted by alkyl groups. Moreover, by the analysis of the plots of electrostatic fields, it was concluded that the CHI value greatly increases if one hydrogen on coumarin ring is substituted by the F, Cl, Br, OH or OCH3 group.

Predicting Human Serum Albumin Affinity of Interleukin-8 (CXCL8) Inhibitors by 3D-QSPR Approach

A novel class of 2-(R)-phenylpropionamides has been recently reported to inhibit in vitro and in vivo interleukin-8 (CXCL8)-induced biological activities. These CXCL8 inhibitors are derivatives of phenylpropionic nonsteroidal antiinflammatory drugs (NSAIDs), high-affinity ligands for site II of human serum albumin (HSA). Up to date, only a limited number of in silico models for the prediction of albumin protein binding are available. A three-dimensional quantitative structure-property relationship (3D-QSPR) approach was used to model the experimental affinity constant (K(i)) to plasma proteins of 37 structurally related molecules, using physicochemical and 3D-pharmacophoric descriptors. Molecular docking studies highlighted that training set molecules preferentially bind site II of HSA. The obtained model shows satisfactory statistical parameters both in fitting and predicting validation. External validation confirmed the statistical significance of the chemometric model, which is a powerful tool for the prediction of HSA binding in virtual libraries of structurally related compounds.

Three-dimensional quantitative structure-property relationship (3D-QSPR) models for prediction of thermodynamic properties of polychlorinated biphenyls (PCBs): enthalpies of fusion and their application to estimates of enthalpies of sublimation and aqueous solubilities.

Comparative Molecular Field Analysis (CoMFA) has been used to develop three-dimensional quantitative structure-property relationship (3D-QSPR) models for the fusion enthalpy at the melting point (Delta(fus)H(m)(T(fus))) of a representative set of polychlorinated biphenyls (PCBs). Various alignment schemes, such as inertial, as is, atom fit, and field fit, were used in this study to evaluate the predictive capabilities of the models. The CoMFA models have also been derived using partial atomic charges calculated from the electrostatic potential (ESP) and Gasteiger-Marsili (GM) methods. The combination of atom fit alignment and GM charges yielded the greatest self-consistency (r(2) = 0.955) and internal predictive ability (r(cv)(2) = 0.783). This CoMFA model was used to predict Delta(fus)H(m)(T(fus)) of the entire set of 209 PCB congeners, including 193 PCB congeners for which experimental values are unavailable. The CoMFA-predicted values, combined with previous estimations of vaporization and sublimation enthalpies, were used to construct a thermodynamic cycle that validated the internal self-consistency of the predictions for these three thermodynamic properties. The CoMFA-predicted values of fusion enthalpy were also used to calculate aqueous solubilities of PCBs using Mobile Order and Disorder Theory. The agreement between calculated and experimental values of solubility at 298.15 K, characterized by a standard deviation of +/- 0.41 log units, demonstrates the utility of CoMFA-predicted values of fusion enthalpies to calculate aqueous solubilities of PCBs.

Three-dimensional quantitative structure-property relationship (3D-QSPR) models for prediction of thermodynamic properties of polychlorinated biphenyls (PCBs): enthalpy of vaporization.

Three-dimensional Quantitative Structure-Property Relationship (QSPR) models have been derived using Comparative Molecular Field Analysis (CoMFA) to correlate the vaporization enthalpies of a representative set of polychlorinated biphenyls (PCBs) at 298.15 K with their CoMFA-calculated physicochemical properties. Various alignment schemes, such as inertial, as is, and atom fit, were employed in this study. The CoMFA models were also developed using different partial charge formalisms, namely, electrostatic potential (ESP) charges and Gasteiger-Marsili (GM) charges. The most predictive model for vaporization enthalpy (Delta(vap)H(m)(298.15 K)), with atom fit alignment and Gasteiger-Marsili charges, yielded r2 values 0.852 (cross-validated) and 0.996 (conventional). The vaporization enthalpies of PCBs increased with the number of chlorine atoms and were found to be larger for the meta- and para-substituted isomers. This model was used to predict Delta(vap)H(m)(298.15 K) of the entire set of 209 PCB congeners.

A generalized formalism of three-dimensional quantitative structure-property relationship analysis for flexible molecules using tensor representation.

A general formalism, based upon tensor representation of multidimensional data blocks, is presented to express relationships between dependent properties and independent molecular feature measures. The solutions to these data set problems are three-dimensional quantitative structure-property relationships, 3D-QSPRs. The molecular features are partitioned into the intrinsic molecular shape tensor, the molecular field tensor, a nonshape/field feature tensor, and an experimental feature tensor. The intrinsic molecular shape tensor contains information on the shape of a molecule within the contact surface while the molecular field tensor contains information outside of the contact surface. Molecular features not directly related to molecular shape are put into the nonshape/field tensor. Experimental measures not being used as dependent variables can be considered as independent molecular features in the experimental feature tensor. The 3D-QSPR is realized by constructing the transformation tensor which optimizes the statistical significance between the dependent and independent variables. Use of partial least squares (PLS) regression permits the unfolding of the composite feature tensor and the identification of the optimum transformation tensor. It is pointed out that a variety of fragment, whole-molecule, two-dimensional, and/or three-dimensional features can be placed into a nonshape/field tensor.