Adsorption properties and inhibition of mild steel corrosion in hydrochloric solution by some newly synthesized diamine derivatives: Experimental and theoretical investigations

New diamine derivatives, namely 2-[{2-[bis-(2-hydroxyethyl)amino]ethyl}(2-hydroxyethyl)amino]ethanol (DAME) and 2-[{2-[bis-(2-hydroxyethyl)amino]ethyl}(2-hydroxyethyl)amino]propanol (DAMP) were synthesised and their inhibitive action against the corrosion of mild steel in 1 M HCl solution were investigated at 308 K. The detailed study of DAME is given using gravimetric measurements and polarization curves method. Results show that DAME is a good inhibitor and inhibition efficiency reaches 91.7% at 10⁻³ M. Tafel polarization study revealed that DAME acts as a mixed-type inhibitor. The inhibitor adsorption process in mild steel/DAME/hydrochloric acid system was studied at different temperatures (308-353 K) by means of weight loss measurements. The adsorption of DAME on steel surface obeyed Langmuir’s adsorption isotherm. The kinetic and thermodynamic parameters for mild steel corrosion and inhibitor adsorption, respectively, were determined and discussed. The comparative study of inhibitive performance of the two diamine derivatives revealed that DAME is more effective than DAMP. Quantitative Structure-Activity Relationship (QSAR) approach has been conducted in attempt to correlate the corrosion inhibition properties of these diamine derivatives with their calculated quantum chemical parameters.     

二芳甲酰基肼类(DAH)昆虫生长调节剂的构效关系及作用机理研究概述

介绍了二芳甲酰基肼类昆虫生长调节剂的构效关系和作用机理。     

Inroads to Predict in Vivo Toxicology-An Introduction to the eTOX Project

There is a widespread awareness that the wealth of preclinical toxicity data that the pharmaceutical industry has generated in recent decades is not exploited as efficiently as it could be. Enhanced data availability for compound comparison ("read-across"), or for data mining to build predictive tools, should lead to a more efficient drug development process and contribute to the reduction of animal use (3Rs principle). In order to achieve these goals, a consortium approach, grouping numbers of relevant partners, is required. The eTOX ("electronic toxicity") consortium represents such a project and is a public-private partnership within the framework of the European Innovative Medicines Initiative (IMI). The project aims at the development of in silico prediction systems for organ and in vivo toxicity. The backbone of the project will be a database consisting of preclinical toxicity data for drug compounds or candidates extracted from previously unpublished, legacy reports from thirteen European and European operation-based pharmaceutical companies. The database will be enhanced by incorporation of publically available, high quality toxicology data. Seven academic institutes and five small-to-medium size enterprises (SMEs) contribute with their expertise in data gathering, database curation, data mining, chemoinformatics and predictive systems development. The outcome of the project will be a predictive system contributing to early potential hazard identification and risk assessment during the drug development process. The concept and strategy of the eTOX project is described here, together with current achievements and future deliverables.     

Poisson parameters of antimicrobial activity: a quantitative structure-activity approach

A contingency of observed antimicrobial activities measured for several compounds vs. a series of bacteria was analyzed. A factor analysis revealed the existence of a certain probability distribution function of the antimicrobial activity. A quantitative structure-activity relationship analysis for the overall antimicrobial ability was conducted using the population statistics associated with identified probability distribution function. The antimicrobial activity proved to follow the Poisson distribution if just one factor varies (such as chemical compound or bacteria). The Poisson parameter estimating antimicrobial effect, giving both mean and variance of the antimicrobial activity, was used to develop structure-activity models describing the effect of compounds on bacteria and fungi species. Two approaches were employed to obtain the models, and for every approach, a model was selected, further investigated and found to be statistically significant. The best predictive model for antimicrobial effect on bacteria and fungi species was identified using graphical representation of observed vs. calculated values as well as several predictive power parameters.     

手性拓扑电荷指数和构效关系研究

对拓扑电荷指数进行了扩展,得到了含电负性的手性拓扑电荷指数。将其与Julián-Qrtiz 等人对该指数的扩展结果相比较,结果表明,新的拓扑指数能够得到更好的QSAR 模型。进一步运用人工神经网络法构造了数学模型,该模型能够更好地预测手性化合物的活性。     

二磺酰胺类内皮素受体拮抗剂的构效关系研究

应用量子化学方法计算了34个二磺酰胺类化合物的结构参数,并用BP神经网络对34个二磺酰胺类化合物的结构参数与ETs受体拮抗活性进行了定量构效关系分析,获得了一个预测能力较好的QSAR神经网络模型。研究表明：二磺酰胺类化合物与ETs受体之间存在直接的电荷迁移作用,电子结构、疏水性是影响其活性的主要因素。本文建立的二磺酰胺类化合物分子结构与ETs受体拮抗活性之间的定量构效关系,为设计合成新的此类内皮素受体拮抗剂提供了参考。     

黄酮类化合物抗肿瘤活性的构效关系研究

应用分子力学MM 和半经验量子化学AM1法对18种黄酮类化合物进行了几何优化,并计算了各化合物的电子结构,根据其电子结构,结合它们在体外抑制60-Cellline人体肿瘤细胞的活性数据(IC50)进行讨论,得出了黄酮类化合物抗肿瘤活性的定量构效关系。结果表明：B环和C环对黄酮类化合物抗肿瘤活性影响大;且B环负电性越高,活性越强,而C环正电性越高,活性越强。     

Pharmacophore Synergism in Diverse Scaffold Clinches in Aurora Kinase B

Aurora kinase B (AKB) is a crucial signaling kinase with an important role in cell division. Therefore, inhibition of AKB is an attractive approach to the treatment of cancer. In the present work, extensive quantitative structure–activity relationships (QSAR) analysis has been performed using a set of 561 structurally diverse aurora kinase B inhibitors. The Organization for Economic Cooperation and Development (OECD) guidelines were used to develop a QSAR model that has high statistical performance (R²_tr = 0.815, Q²_LMO = 0.808, R²_ex = 0.814, CCC_ex = 0.899). The seven-variable-based newly developed QSAR model has an excellent balance of external predictive ability (Predictive QSAR) and mechanistic interpretation (Mechanistic QSAR). The QSAR analysis successfully identifies not only the visible pharmacophoric features but also the hidden features. The analysis indicates that the lipophilic and polar groups—especially the H-bond capable groups—must be present at a specific distance from each other. Moreover, the ring nitrogen and ring carbon atoms play important roles in determining the inhibitory activity for AKB. The analysis effectively captures reported as well as unreported pharmacophoric features. The results of the present analysis are also supported by the reported crystal structures of inhibitors bound to AKB.     

结构多样性化合物沸点QSPR模型研究

在定量结构-性质/活性关系(QSPR/QSAR)研究中,分子结构的数值化和建立良好预测的数学模型是2个重要的问题.建立具有良好适应性有实际应用价值的模型是进行QSPR/QSAR的最终目标.本文针对148种来自不同植物挥发油的具有结构多样性化合物,分别采用主成分回归(PCR)、偏最小二乘(PLS)和遗传算法(GA)对其沸点与结构之间的定量结构性能关系进行了研究,用拓扑指数建立了沸点预测模型.结果表明,PLS模型的预测能力最佳,模型训练集的平均相关系数为0.996,平均训练偏差为7.05,检验集的平均相关系数为0.986,平均检验偏差为12.91.