Chemometric QSAR studies of antifungal azoxy compounds

Summary Quantitative structure-activity relationships (QSARs) for 16 azoxy compounds with antifungal activity have been studied by the combined approach of a partial least-squares method and factorial design. The PLS model equation suggested the structural requirements of two substituents, R₁ and R₂, for the antifungal activity. The sterically bulky and hydrophobic R₁ substituents and electron-withdrawing R₂ substituents are favorable for the activity. We propose candidate compounds which are more potent than the compounds based on QSAR data. In this study, we show that the chemometric approach is a powerful tool for QSAR studies and drug design.Abbreviations PLS partial least squares - FD factorial design - MLR multiple linear regression - PPs principal properties     

Using particle swarms for the development of QSAR models based on K-nearest neighbor and kernel regression

We describe the application of particle swarms for the development of quantitative structure-activity relationship (QSAR) models based on k-nearest neighbor and kernel regression. Particle swarms is a population-based stochastic search method based on the principles of social interaction. Each individual explores the feature space guided by its previous success and that of its neighbors. Success is measured using leave-one-out (LOO) cross validation on the resulting model as determined by k-nearest neighbor kernel regression. The technique is shown to compare favorably to simulated annealing using three classical data sets from the QSAR literature.     

A QSAR of the toxicity of amino-benzenes and their structures

The quantum chemical parameters and the topological indices have been calculated for the prediction of the toxicity of amino-benzenes in the environment, and work has been done on the multiple regression and neural networks. The combination of CoMFA with formation heat yields greatly improved results. A good model has been obtained which provides a basis for the studies of the toxic action mechanism.     

苯胺衍生物式电位的QSAR研究

以AM1量子化学半经验分子轨道方法计算22个苯胺衍生物的分子结构参数,用多元线性回归的方法研究了13个式电位已知的苯胺衍生物的氧化式电位与其分子结构参数之间的关系.苯胺衍生物式电位与离子化电势(Ip),N原子上的净电荷(e(N),总的偶极矩(μt)和第四个碳上的净电荷(e(C4))有很好的相关性,回归方程为:E0′=-7.820 5 0.884 9(Ip-3.739(e(N)-0.093 56μt 0.925 1(e(C4)),(R=0.979,SD为0.023 6).依据回归方程合理地预测了其余9个苯胺衍生物的离子化电势和式电位,探讨了取代基性质和取代位置对离子化电势和式电位的影响.     

Synthesis and QSAR studies on 1-[(5-substituted-1,3,4-thiadiazol-2-yl)methyl]-1H-1,2,4-triazole as antifungal agents

A series of 1-[(1,3,4-thiadiazol-2-yl)methyl]-1H-1,2,4-triazole derivatives were prepared and evaluated for their antifungal activities. The chemical structures of these compounds were determined by means of elemental analyses, ¹H NMR, and X-ray crystallography. Quantitative structure–activity relationship (QSAR) studies were performed on these compounds using physicochemical parameters as independent parameters and antifungal activity as a dependent parameter, where antifungal activity correlated best (r > 0.9) with hydrophobic parameters (π) and indicator (H). Moreover, the results are interpreted on the basis of a multiple regression model. The model has been internally and externally validated. Furthermore, the domain of applicability which indicates the area of reliable predictions is defined.     

A QSAR study and molecular design of benzothiazole derivatives as potent anticancer agents

A quantitative structure-activity relationship (QSAR) of a series of benzothiazole derivatives showing a potent and selective cytotoxicity against a tumorigenic cell line has been studied by using the density functional theory (DFT), molecular mechanics (MM ) and statistical methods, and the QSAR equation was established via a correlation analysis and a stepwise regression analysis. A new scheme determining outliers by "leave-one-out" (LOO) cross-validation coefficient (q2n-i) was suggested and successfully used. In the established optimal equation (excluding two outliers), the steric parameter (MRR) and the net charge (QFR) of the first atom of the substituent (R), as well as the square of hydrophobic parameter (lgP)2 of the whole molecule, are the main independent factors contributing to the anticancer activities of the compounds. The fitting correlation coefficient (R2) and the cross-validation coefficient (q2) values are 0.883 and 0.797, respectively. It indicates that this model has a significantly statistical quality and an excellent prediction ability. Based on the QSAR studies, 4 new compounds with high predicted anticancer activities have been theoretically designed and they are expected to be confirmed experimentally.     

QSAR studies of some side chain modified 7-chloro-4-aminoquinolines as antimalarial agents

The quantitative structure–activity relationship (QSAR) analyses were carried out for a series of new side chain modified 4-amino-7-chloroquinolines to find out the structural requirements of their antimalarial activities against both chloroquine sensitive (HB3) and resistant (Dd2) Plasmodium falciparum strain. The statistically significant best 2D QSAR models for Dd2, having correlation coefficient (r²) = 0.9188 and cross validated squared correlation coefficient (q²) = 0.8349 with external predictive ability (pred_r²) = 0.7258 and for HB3, having r² = 0.9024, q² = 0.8089 and pred_r² = 0.7463 were developed by multiple linear regression coupled with genetic algorithm (GA–MLR) and stepwise (SW–MLR) forward algorithm, respectively. The results of the present study may be useful on the designing of more potent analogues as antimalarial agents.     

QSAR Studies on the Calanolide Analogues as Anti-HIV-1 Agents

The Quantitative Structure-Activity Relationship (QSAR) of a series of novel calanolide analogues,which exhibit inhibitory activities of HIV-1,has been studied with a combined method of ab initio (HF),molecular mechanics (MM+) and statistics. The established QSAR model (Eq. 1) shows a reasonable regressive performance (R2 = 0.885). Both the surface area of the substituted group attached on C10,SR3,and the distance between atoms O13 and X14 (O,N,S),L,of the calanolide analogues play important roles in determining the inhibitory activity of HIV-1.     

AM1 and DFT study of polarizability of nitrogen-containing octatetraene with donor substituents: Comparative investigation

We report density functional theory (DFT) studies of the dipole polarizabilities of nitrogen-containing octatetraene with a number of Π-electron donor substituent at the end parts. All geometries were optimized at the B3LYP/6-311++G(d,p) level of theory and polarizabilities were done at the same level of theory. The results indicate that for the NO₂–(CHCH)₄–Y systems we find group polarizabilities in the order: N(Me)₂ > NBr₂ > OCH₃ > Br > NH₂ > OH > CH₃ > NF₂ > H～F.Semi empirical AM1 and QSAR-quality empirical calculations show poor quantitative agreement with the DFT results, but give excellent statistical correlation coefficients with the DFT values. This implies that the results of such cheaper calculations can suitably scaled for predictive purpose.     

DAPY类化合物抑制野生型HIV-1活性的QSAR研究

应用分子力学、半经验量子化学RM1方法优化了32个抗野生型HIV-1病毒毒株的二芳基嘧啶类(DAPYs)化合物分子结构,从分子构象模型中提取了多种参数并结合疏水性参数与指示性参数建立QSAR多元线性回归方程.回归方程显示:分子体积V的增大会降低其抑制活性,而左苯环与嘧啶环间二面角θ增大可以提高抑制活性.同时指示性参数I表明左苯环CN基团加入可以明显增加抑制活性,嘧啶环上R1位置苯基与硝基的加入可以极大降低抑制活性.     

QSAR analysis of 1,3-diaryl-2-propen-1-ones and their indole analogs for designing potent antibacterial agents

A series of 1,3-diaryl-2-propen-1-ones and their indole analogs were synthesized and evaluated for antibacterial activity. Structures of newly synthesized compounds were confirmed by physicochemical, spectral and elemental analysis. All the compounds were screened for their antibacterial activities against four different bacterial strains. The QSAR studies were performed using Vlife MDS 3.5 software. QSAR equation revealed that selected electronic, steric and lipophilic parameters have good correlation with antibacterial activity. Best equations were selected on basis of the correlation coefficient (r ²) and the predictable ability of the equations. The present findings suggest that the 1,3-diaryl-2-propen-1-ones framework is an attractive template for structure optimization to achieve higher potency, lower toxicity, and a wider spectrum of antibacterial activity.