An evaluation of experimental design in QSAR modelling utilizing the k‐medoid clustering

A reliable selection of a representative subset of chemical compounds has been reported to be crucial for numerous tasks in computational chemistry and chemoinformatics. We investigated the usability of an approach on the basis of the k‐medoid algorithm for this task and in particular for experimental design and the split between training and validation set. We therefore compared the performance of models derived from such a selection to that of models derived using several other approaches, such as space‐filling design and D‐optimal design. We validated the performance on four datasets with different endpoints, representing toxicity, physicochemical properties and others. Compared with the models derived from the compounds selected by the other examined approaches, those derived with the k‐medoid selection show a high reliability for experimental design, as their performance was constantly among the best for all examined datasets. Of all the models derived with all examined approaches, those derived with the k‐medoid approach were the only ones that showed a significantly improved performance compared with a random selection, for all datasets, the whole examined range of selected compounds and for each dimensionality of the search space. Copyright © 2012 John Wiley & Sons, Ltd.     

Progress on the development of DNA-mediated metal nanomaterials for environmental and biological analysis

This review summarized the recent progress on the synthesis, morphologies and properties of DNA-mediated metal nanomaterials including nanoparticles and nanoclusters. Moreover, their applications to environmental and biological analysis were introduced with the developing prospect in analytical chemistry.     

Preparation and Biosafety Evaluation of the Peptide Dendron Functionalized Mesoporous Silica Nanohybrid

Mesoporous silica nanoparticles (MSNs) have been extensively studied and proposed as promising candidates for numerous biomedical applications.In this study,we report the design,preparation,characterization and biosafety evaluation of peptide dendron functionalized mesoporous silica nanohybrid.This nanohybrid was prepared by surface modification of MSNs via click reaction of azido-MSNs with alkynyl peptide dendrons,and characterized by TEM,SEM,TGA,dynamic light scattering (DLS).In vitro cytotoxicity of the nanohybrid was evaluated against different cell lines by CCK-8 assay.The in vivo toxicity evaluation was measured by body weight shift,blood routine test and histological analysis,suggesting that the peptide functionalized nanohybrid possessed good biocompatibility due to the non-observed significant side effects to normal organs of healthy mice.Overall,considering our results we believe that the peptide dendron functionalized mesoporous silica nanohybrid is very promising in further biomedical applications.     

Parallel co-ordinate geometry and principal component analysis for the interpretation of large multi-response experimental designs

In the evaluation of large or complex data sets the use of visualization methods can be of great benefit. In this paper, the use of parallel co-ordinate geometry (PCG) plots, principal component analysis (PCA) and N-way PCA as visualization procedures for large multi-response experimental designs was compared with the more traditional approach of calculating factor effects by multiple linear regression. PCG plots are a recent addition to the visualization tools and offer a possibility to visualize multi-dimensional data in two dimensions while no calculations are required. It was found that PCA and PCG each have their own benefits and disadvantages. Both methods can be used to some extent to select optimal conditions. Moreover, it was possible to use the PCA score plot as a Pareto optimality plot that allowed to select the experiments considered to be Pareto optimal. Therefore, the examined visualization methods can be useful and complementary aids in the interpretation of large multi-response experimental design data and they add a multivariate dimension to the more classical univariate analysis of such data.     

High antibacterial activity and low toxicity of pyridoxal derivatives of chitosan and their nanoparticles

The pyridoxal derivatives of chitosan with various degrees of substitution (DS) were synthesized from low-, moderate- and high-molecular-weight chitosans by their reaction with pyridoxal followed by treatment with NaBH₄. The derivative of moderate molecular weight and high DS demonstrated a maximum antibacterial activity against S. aureus and E. coli. The nanoparticles of this derivative obtained by ionic gelation are nontoxic, and they exhibit a high in vitro antibacterial effect, which slightly exceeds that of ampicillin and gentamicin.     

Comparative study of the alignment method on experimental and simulated chromatographic data

One of the major problems in the signal comparison of chromatographic data is the variability of response caused by instrumental drifts and others instabilities. Measures of quality control and evaluation of conformity are inherently sensitive to shift. It is essential to be able to compare test samples to reference samples in an evolutionary analytical environment by offsetting the inevitable drift. Therefore, prior to any multivariate analysis, the alignment of analytical signals is a compulsory preprocessing step. During recent years, many researchers have taken a greater interest in the study of the alignment. The present paper is an updated review on the alignment algorithms, methods, and improvements used in chromatography. The study is dedicated to one‐dimensional signals. Several of the exposed methods have common theoretical bases and can differ through their optimization methods. The main issue for the operator is to choose the appropriate method according to the type of signals to be processed.     

Multiple QSAR and molecular modelling for identification of potent human adenovirus inhibitors

This study has investigated docking-based 2D- and 3D-quantitative structure-activity relationships (QSARs) for a range of 53 hydroxybenzamide analogues as anti- Human adenoviruses (HAdVs). The best 3D-QSAR (Schrodinger, LLC, NY, 2020) and 2D-QSAR models were obtained for the training set and were found to be statistically significant, with cross-validated coefficients (q²) of 0.6775 and 0.7875, and coefficients of determination (r²) of 0.8106 and 0.8122, respectively. Our in-silico docking and virtual screening studies revealed significant higher binding affinity of dataset molecule 34 (-141.444 ​kcal/mol) and hit ZINC01088642 (-114.357 ​kcal/mol) with 4PIE protein than the standard drugs. In in-silico ADME/toxicity studies, molecule 34 and proposed hit ZINC01088642 were found safe with good intestinal absorption, aqueous solubility, medium blood–brain barrier (BBB), no eye corrosion, no skin irritancy, and non-mutagenic profiles. Molecular dynamics analysis showed good stability of complex, hit ZINC01088642 with protein, 4PIE over the simulation period of 20 ns. We believe that further experimental, as well as in-vitro investigation, will shed more lights on the identification of ZINC01088642 as a potential human adenovirus agent.     

On the construction of experimental designs for a given task by jointly optimizing several quality criteria: Pareto-optimal experimental designs

Experimental designs for a given task should be selected on the base of the problem being solved and of some criteria that measure their quality. There are several such criteria because there are several aspects to be taken into account when making a choice. The most used criteria are probably the so-called alphabetical optimality criteria (for example, the A-, E-, and D-criteria related to the joint estimation of the coefficients, or the I- and G-criteria related to the prediction variance). Selecting a proper design to solve a problem implies finding a balance among these several criteria that measure the performance of the design in different aspects. Technically this is a problem of multi-criteria optimization, which can be tackled from different views.     

Heavy metal determinations in algae and clams and their possible employment for assessing the sea water quality criteria

An empirical criterion for a possible classification of sea water quality is proposed. It is based on the knowledge of metal content in algae (Ulva Rigida) and clams (Tapes Philippinarum), two species present in marine ecosystems. The elements considered are Hg, Cu, Pb, Cd, Zn. The analytical technique employed is Differential Pulse Anodic Stripping Voltammetry (DPASV) in the case of Cu, Pb, Cd, Zn, while the determination of mercury is obtained by the Cold Vapour Atomic Absorption Spectroscopy (CV-AAS) technique with SnCl2 as reducing agent. The analytical procedure has been verified on three standard reference materials: Sea Water BCR-CRM 403, Ulva Lactuca BCR-CRM 279 and Mussel Tissue BCR-CRM 278. For all the elements, in addition to detection limits, accuracy and precision are given: the former, expressed as relative error (e), and the latter, expressed as relative standard deviation (Sr), were in all cases lower than 6%.     

掺杂比例和光敏剂对上转换纳米材料性能的影响

以NaYF_4材料为基质的上转换纳米颗粒(UCNPs)是最早报道的、应用范围最广的上转换材料之一。掺杂了稀土离子的颗粒不但可以在不同激发条件下发射出不同波长和强度的荧光,而且可以与多种光敏分子搭配使用,通过荧光共振能量转移产生单线态氧,实现生物医学成像或诊疗方面的应用。但是其形貌和荧光性能均受制备方法和工艺条件的影响较大。本文通过水热法合成了两类掺杂不同稀土离子的十种NaYF_4 UCNPs,在保持掺杂离子的终浓度不变的条件下,探究离子类型与比例对纳米材料的结构和上转换发光性能的影响。在此基础上,探索了多种卟啉类光敏剂分子与NaYF_4 UCNPs发生能量转换及单线态氧的产生能力。本工作可为基于NaYF_4材料的上转换颗粒的规模化制备和工艺升级提供数据支撑和理论参考。     

Evaluation and improvement of QSAR predictions of skin sensitization for pesticides

In vivo skin sensitization assays have to be provided by applicants to the competent authorities in the European Union for the approval of active substances (AS) in pesticides. This study aimed to test the practicability of in silico predictions for AS by freely available (Q)SAR tools to evaluate their use as a time- and cost-effective alternative to animal testing in the context of the 3R concept. Predictions of skin sensitization for 48 selected sensitizing and non-sensitizing AS by the software programs CAESAR, Toxtree, OECD (Q)SAR Toolbox, CASE Ultra, Leadscope and SciQSAR were collected and compared. Different data evaluation methodologies (score definition, mean, weighted mean, threshold score definition) were applied to optimize the predictions. The calculation methods were internally cross-validated and further validated with an additional validation set of 80 AS. Although the presented calculation methodologies are not suitable as a stand-alone method, this study has shown weaknesses and strengths of some prominent (Q)SAR programs and diverse combinatorial options in the prediction of skin sensitization by pesticidal AS. The present study will help to foster discussions on in silico alternatives to animal testing in the pesticide area.     

QSAR models based on isomorphic and nonisomorphic data fusion for predicting the blood brain barrier permeability

A QSAR model for predicting the blood brain barrier permeability (BBBP) in a large and heterogeneous variety of compounds (136 compounds) has been developed using approximate similarity (AS) matrices as predictors and PLS as multivariate regression technique. AS values fuse information of both the isomorphic similarity and nonisomorphic dissimilarity with the purpose of achieving an accurate predictive space. In addition to the fact of applying AS values to heterogeneous data sets, a new concept on graph isomorphism based on the extended maximum common subgraph (EMCS) is defined for the building of AS spaces considering the atoms and bonds, which are bridges between the isomorphic and nonisomorphic substructures. This new isomorphism detection has as objective to take into account the position and nature of the nucleus substituents, thus allowing the development of accurate models for large and diverse sets of compounds. After an outliers study, the training and test stages were made and the results obtained using several AS approaches were compared. Several validation processes were carried out by means of employing several test sets, and high predictive ability was obtained for all the cases (Q(2) = 0.81 and standard error in prediction, SEP = 0.29).     

中学化学教师实验素养的结构、评价与提升

分析素质、素养、修养等概念,提出化学教师实验素养可界定为2个方面:实验素质与实验修养。探查Y市化学教师的实验理论素质及操作素质考查概况,并进行归因分析。根据现有条件,提出化学教师实验素养提升的2个视角:教师维度和顶层设计。