Qualitative and quantitative structure–activity relationship modelling for predicting blood-brain barrier permeability of structurally diverse chemicals

In this study, structure–activity relationship (SAR) models have been established for qualitative and quantitative prediction of the blood–brain barrier (BBB) permeability of chemicals. The structural diversity of the chemicals and nonlinear structure in the data were tested. The predictive and generalization ability of the developed SAR models were tested through internal and external validation procedures. In complete data, the QSAR models rendered ternary classification accuracy of >98.15%, while the quantitative SAR models yielded correlation (r²) of >0.926 between the measured and the predicted BBB permeability values with the mean squared error (MSE) <0.045. The proposed models were also applied to an external new in vitro data and yielded classification accuracy of >82.7% and r² > 0.905 (MSE < 0.019). The sensitivity analysis revealed that topological polar surface area (TPSA) has the highest effect in qualitative and quantitative models for predicting the BBB permeability of chemicals. Moreover, these models showed predictive performance superior to those reported earlier in the literature. This demonstrates the appropriateness of the developed SAR models to reliably predict the BBB permeability of new chemicals, which can be used for initial screening of the molecules in the drug development process.     

A facile synthesis of novel 5‐substituted pyridine 2 carboxamide derivatives and their biological evaluation and 3D QSAR studies

A variety of novel 5‐substituted pyridine 2 carboxamides were designed and synthesized using both normal and solvent‐free microwave (MW) irradiation techniques. The results revealed that MW protocol proceeded smoothly under mild reaction conditions in short reaction times, thus avoiding the use of toxic organic solvents. Structural elucidation of the synthesized compounds was carried out on the basis of various spectroscopic methods, such as ¹H NMR, ¹³C NMR, LCMS, and IR. The synthesized compounds were evaluated for their in vitro antimicrobial activity (MIC) using the agar disk diffusion method. Among the various synthetic compounds, compound 3b showed higher potential activity against Escherichia coli than the other compounds. The order of activity against E. coli of the studied compounds is 3b > 3e > 3g > 3h > 3d > 3c > 3a > 3f . Additionally, 2D and 3D structural features of the synthesized derivatives were recognized by the 3D‐QSAR model. This validated model exhibited good internal (r², 0.924) and external prediction (r²pred, 0.851) correlation. The results of QSAR studies concluded that Alog P, the number of hydrogen bond acceptors, and the number of rotatable bonds were necessary features for the activity of the pyridine carboxamide derivatives.     

Impact assessment of the rational selection of training and test sets on the predictive ability of QSAR models

This study performed an analysis of the influence of the training and test set rational selection on the quality and predictively of the quantitative structure–activity relationship (QSAR) model. The study was carried out on three different datasets of Influenza Neuraminidase (H1N1) inhibitors. The three datasets were divided into training and test sets using three rational selection methods: based on k-means, Kennard–Stone algorithm and Activity and the results were compared with Random selection. Then, a total of 31,490 mathematical models were developed and those models that presented a determination coefficient higher than: r²_train > 0.8, r²_loo > 0.7, r²_test > 0.5 and minimum standard deviation (SD) and minimum root-mean square error (RMS) were selected. The selected models were validated using the internal leave-one-out method and the predictive capacity was evaluated by the external test set. The results indicate that random selection could lead to erroneous results. In return, a rational selection allows for obtaining more reliable conclusions. The QSAR models with major predictive power were found using the k-means algorithm and selection by activity.     

Complexing tendencies of UO 22+ and Th4+ in their mixed ligand complexes with aminopolycarboxylates and resorcinol or its derivatives

Formation contants (log K _MAL ^MA ) of mixed ligand complexes MAL, where M = UO ₂ ²⁺ or Th⁴⁺, A = IMDA, NTA, HEDTA, EDTA, CDTA or DTPA, and L = resorcinol (res), 2-methyl resorcinol (2-Me-res), 5-methyl resorcinol (5-Me-res) or 4-chloro resorcinol (4-Cl-res), have been determined pH-metrically by the Irving-Rossotti approach at 25°C and at an ionic strength,I = 0.2(moldm⁻³KNO₃). The observed stability sequences are IMDA > NTA > HEDTA > EDTA > CDTA > DTPA, and 4-Cl-res > 5-Me-res > 2-Me-res > res with respect to primary and secondary ligands, respectively. Th⁴⁺ forms more stable mixed complexes than UO ₂ ²⁺ . The A ΔlogK values are negative due mainly to the charge repulsion involved in the complexation MA + L⇋MAL.     

Developing 13C NMR quantitative spectrometric data-activity relationship (QSDAR) models of steroid binding to the corticosteroid binding globulin

We have developed four quantitative spectrometric data-activity relationship (QSDAR) models for 30 steroids binding to corticosteroid binding globulin, based on comparative spectral analysis (CoSA) of simulated ¹³C nuclear magnetic resonance (NMR) data. A QSDAR model based on 3 spectral bins had an explained variance (r ²) of 0.80 and a cross-validated variance (q ²) of 0.78. Another QSDAR model using the 3 atoms from the comparative structurally assigned spectral analysis (CoSASA) of simulated ¹³C NMR on a steroid backbone template gave an explained variance (r ²) of 0.80 and a cross-validated variance (q ²) of 0.73. Positions 3 and 14 from the steroid backbone template have correlations with the relative binding activity to corticosteroid binding globulin that are greater than 0.52. The explained correlation and cross-validated correlation of these QSDAR models are as good as previously published quantitative structure-activity relationship (QSAR), self-organizing map (SOM) and electrotopological state (E-state) models. One reason that the cross-validated variance of QSDAR models were as good as the other models is that simulated ¹³C NMR spectral data are more accurate than the errors introduced by the assumptions and approximations used in calculated electrostatic potentials, E-states, HE-states, and the molecular alignment process of QSAR modeling. The QSDAR models developed provide a rapid, simple way to predict the binding activity of a steroid to corticosteroid binding globulin.     

十二烷基磺酸钠-盐酸维拉帕米-联吡啶钌体系电化学发光及其应用

在十二烷基磺酸钠(SDS)中,考察了盐酸维拉帕米-Ru(bpy)3(2+)体系在金电极上的电化学及其发光行为.结果表明:SDS对体系的电化学反应和电化学发光强度具有显著的增敏作用.据此,建立了一种高效、简便的测定盐酸维拉帕米的电化学发光新方法.在最佳实验条件下,盐酸维拉帕米浓度在1.0×10(-4)～1.0×10(-2...     

Inclusion complexation of diclofenac with natural and modified cyclodextrins explored through phase solubility, 1H-NMR and molecular modeling studies

Guest–host interactions were examined for neutral diclofenac (Diclo) and Diclofenac sodium (Diclo sodium) with each of the cyclodextrin (CD) derivatives: α-CD, β-CD, γ-CD and 2-hydroxypropyl-β-cyclodextrin (HP-β-CD), all in 0.05 M aqueous phosphate buffer solution adjusted to 0.2 M ionic strength with NaCl at 20 °C, and with β-CD at different pHs and temperatures. The pH solubility profiles were measured to obtain the acid–base ionization constants (pK _as) for Diclo in the presence and absence of β-CD. Phase solubility diagrams (PSDs) were also measured and analyzed through rigorous procedures to obtain estimates of the complex formation constants for Diclo/CD and Diclo sodium/CD complexation in aqueous solutions. The results indicate that both Diclo and Diclo sodium form soluble 1:1 complexes with α-, β-, and HP-β-CD. In contrast, Diclo forms soluble 1:1 Diclo/γ-CD complexes, while Diclo sodium forms 1:1 and 2:1 Diclo/γ-CD, but the 1:1 complex saturates at 5.8 mM γ-CD with a solubility product constant (pK _sp = 5.5). Therefore, though overall complex stabilities were found to follow the decreasing order: γ-CD > HP-β-CD > β-CD > α-CD, some complex precipitation problems may be faced with aqueous formulations of Diclo sodium with γ-CD, where the overall concentration of the latter exceeds 5.8 mM γ-CD. Both ¹H-NMR spectroscopic and molecular mechanical modeling (MM⁺) studies of Diclo/β-CD indicate the possible formation of soluble isomeric 1:1 complexes in water.     

Development of an ecotoxicity QSAR model for the KAshinhou Tool for Ecotoxicity (KATE) system,March 2009 version

The KAshinhou Tool for Ecotoxicity (KATE) system, including ecotoxicity quantitative structure–activity relationship (QSAR) models, was developed by the Japanese National Institute for Environmental Studies (NIES) using the database of aquatic toxicity results gathered by the Japanese Ministry of the Environment and the US EPA fathead minnow database. In this system chemicals can be entered according to their one-dimensional structures and classified by substructure. The QSAR equations for predicting the toxicity of a chemical compound assume a linear correlation between its log P value and its aquatic toxicity. KATE uses a structural domain called C-judgement, defined by the substructures of specified functional groups in the QSAR models. Internal validation by the leave-one-out method confirms that the QSAR equations, with r ² > 0.7, RMSE ≤ 0.5, and n > 5, give acceptable q ² values. Such external validation indicates that a group of chemicals with an in-domain of KATE C-judgements exhibits a lower root mean square error (RMSE). These findings demonstrate that the KATE system has the potential to enable chemicals to be categorised as potential hazards.     

CO<Subscript>2</Subscript> adsorption and dehydration behavior of LiNaX,KNaX, CaNaX and CeNaX zeolites

In this study, NaX synthetic zeolite was modified by following the conventional cation exchange method at 70°C. 82, 81, 79 and 48% of sodium were exchanged with Li⁺, K⁺, Ca2⁺ and Ce3⁺, respectively. Thermal analysis data obtained by TG/DSC was used to evaluate the dehydration behavior of the zeolites. The strongest interaction with water and the highest dehydration enthalpy (ΔH) value were found for Li-exchanged form and compared with the other forms. The temperature required for complete dehydration increased with decreasing cation size (cation size: K⁺>Ce³⁺>Ca2⁺>Na⁺>Li⁺). CO₂ adsorption at 5 and 25°C was also studied and the virial model equation was used to analyze the experimental data to calculate the Henry’s law constant, K _o and isosteric heat of adsorption at zero loading Q _st. K _o values decreased with increasing temperature and the highest Qst was obtained for K rich zeolite. It was observed that both dehydration and CO₂ adsorption properties are related to cation introduced into zeolite structure.     

The crystal structure of ZnFe 2 3+ (SeO3)4

Summary The new synthetic compound ZnFe ₂ ³⁺ (SeO₃)₄ forms at low-hydrothermal conditions at 220 °C. It belongs to the monoclinic system; the structure was determined by single-crystal X-ray diffraction in the space group Pc. The unit cell data are:a=8.196(4) Å,b=7.997(4) Å,c=8.033(4) Å, =92.27(3)°,V=526.1 ų;Z=2. The structure of ZnFe ₂ ³⁺ (SeO₃)₄ contains two types of FeO₆ octahedra, one distorted ZnO₅ trigonal bipyramid, and four selenite groups. Formal clusters consisting of the ZnO₅ group, edge-linked with both FeO₆ groups and one SeO₃ pyramid, are connected by common corners, involving three further selenite groups to a framework structure.

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Die Kristallstruktur von ZnFe ₂ ³⁺ (SeO₃)₄

Zusammenfassung Die neue synthetische Verbindung ZnFe ₂ ³⁺ (SeO₃)₄ bildet sich bei niedrighydrothermalen Bedingungen (220°C). Die Kristallstruktur wurde mit Einkristallröntgenmethoden in der monoklinen Raumgruppe Pc gelöst. Die Zellparameter sind:a=8.196(4) Å,b=7.997(4) Å,c=8.033(4) Å, =92.27(3)°,V=526.1 ų;Z=2. Die Kristallstruktur von ZnFe ₂ ³⁺ (SeO₃)₄ weist zwei Arten von FeO₆-Oktaedern, eine verzerrte trigonale ZnO₅-Dipyramide sowie vier Selenitgruppen auf. Formal können Cluster, bestehend aus dem ZnO₅-Polyeder, kantenverknüpft mit den beiden FeO₆-Gruppen sowie einer SeO₃-Pyramide, beschrieben werden. Die Verknüpfung über Ecken zu einer Gerüststruktur erfolgt unter Beteiligung von drei weiteren Selenitgruppen.

     

Structural investigations of anthranilimide derivatives by CoMFA and CoMSIA 3D-QSAR studies reveal novel insight into their structures toward glycogen phosphorylase inhibition

In the present work, three-dimensional quantitative structure–activity relationship (3-D QSAR) studies on a set of 70 anthranilimide compounds has been performed using docking-based as well as substructure-based molecular alignments. This resulted in the selection of more statistically relevant substructure-based alignment for further studies. Further, molecular models with good predictive power were derived using CoMFA (r ^2?=?0.997; Q ^2?=?0.578) and CoMSIA (r ^2?=?0.976; Q ^2?=?0.506), for predicting the biological activity of new compounds. The so-developed contour plots identified several key features of the compounds explaining wide activity ranges. Based on the information derived from the CoMFA contour maps, novel leads were proposed which showed better predicted activity with respect to the already reported systems. Thus, the present study not only offers a highly significant predictive QSAR model for anthranilimide derivatives as glycogen phosphorylase (GP) inhibitors which can eventually assist and complement the rational drug-design attempts, but also proposes a highly predictive pharmacophore model as a guide for further development of selective and more potent GP inhibitors as anti-diabetic agents.