QSAR Study and VolSurf Characterization of Human Intestinal Absorption of Druge

The prediction of human intestinal absorption is a major goal in the design,optimization,and selection of candidates for the develoment of oral drugs.In this study,a computerized method(VolSurf with GRID) was used as a novel tool for predicting human intestinal absorption of test compound,and for determining the critical molecular properties needed for human intestinal absorption.The tested molecules consisted of 20 diverse drug-like compounds.Partial least squares(PLS) discriminant analysis was used to correlate the experimental data with the theoretical molecular properties of human intestinal absorption.A good correlation(r^2=0.95,q^2=0.86) between the molecular modeling results and the experimental data demonstrated that human intestinal absorption could be predicted from the three-dimensional(3D) molecular structure of a compound .Favorable structureal properties identified for the potent intestinal absorption of drugs included strong imbalance between the center of mass of a molecule and the barycentre of its hydrophilic and hydrophobic regions and a definitive hydrophobic region as well as less hydrogen bonding donors and acceptors in the molecule.     

药物水溶解度的QSAR研究和VolSurf参数

药物的水溶解度与其吸收密切相关。本文利用一种新的计算方法,VolSurf,预测药物的水溶解度并测定有利于药物水溶解度的主要分子特征。被测化合物包括26个结构不同的药物,通过偏最小二乘分析法,对药物水溶解度实验值与分子特征进行相关,得到较好的模型(r2=0.90,q2=0.77)。将化合物分为训练集和预测集进行相关分析,结果表明以18个化合物所建立的训练集模型对其余8个化合物有较好的预测能力,预测的标准偏差(SDEP)为0.59。参数分析表明分子与水相互作用的3个局部能量最小值越小,且它们之间的距离越大,对其水溶解度越有利;亲水性占主导因素的分子有高的水溶解度;分子的疏水性越强,在水中的溶解性越弱;大分子的溶解度较小分子溶解度低。     

Experimental design based 3-D QSAR analysis of steroid-protein interactions: Application to human CBG complexes

Summary An experimental design based 3-D QSAR analysis using a combination of principal component and PLS analysis is presented and applied to human corticosteroid-binding globulin complexes. The predictive capability of the created model is good. The technique can also be used as guidance when selecting new compounds to be investigated.     

Modelling of the Biological Activity for a Set of Ceramic Fibre Materials: A QSAR Study

Abstract

The objective was to develop quantitative structure-activity relationships (QSARs) for a set of nine ceramic raw materials. The samples were characterized by a chemical analysis (both X-ray fluorescence and neutron activation analysis) and the morphology was determined by electron microscopy in combination with automated image analysis. Further, the fibre samples were subjected to two biological activity assays, measuring cytotoxicity and hydroxyl radical production. To investigate the produced data structures, principal component analysis (PCA) and partial least squares (PLS) were applied together with rigorous validation techniques. Significant QSARs were found for both biological activity assays. The morphology of the fibres plays an important role for the cytotoxicity and their trace element background is related to the hydroxyl radical production.     

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     

Integration of genetic virtual screening patterns and latent multivariate modeling techniques for QSAR optimization based on combinations and/or interactions between peptides and proteins

Both the concept and the model of snug quantitative structure-activity relationship (QSAR) were pro-posed and developed for molecular design through constructing QSAR based on some known mode of receptor/ligand interactions. Many disadvantages of traditional models can be avoided by using the proposed method because the traditional models only determined upon molecular structural features in sample sets themselves. A genetic virtual screening of peptide/protein combinations (GVSPPC) is proposed for the first time by utilizing this idea to examine peptide/protein affinity activities. A genetic algorithm (GA) was developed for screening combinative targets with an interaction mode for virtual receptors. GVSPPC succeeds in disposing difficulties in rational QSAR,in order to search for the ligand/receptor interactions on conditions of unknown structures. Some bioactive oligo-/poly-peptide systems covering 58 angiotensin converting enzyme (ACE) inhibitors and 18 double site mutation residues in camel antibody protein cAb-Lys3 were investigated by GVSPPC with satisfactory results (R 2 cu>0.91,Q 2 cv > 0.86,ERMS=0.19-0.95),respectively,which demonstrates that GVSPPC is more inter-pretable in the ligand-receptor interaction than the traditional QSAR method.     

Statistically rigorous analysis of imaging SIMS data in the presence of detector saturation

We present a new strategy for analyzing imaging time‐of‐flight SIMS data sets affected by detector saturation. Rather than attempt to correct the measured data to remove saturation, we incorporate the detector behavior into the statistical basis of the analysis. This is performed within the framework of maximum a posteriori reconstruction. The proposed approach has several advantages over previous techniques. No approximations are involved other than the assumed model of the detector. The method performs well even when applied to highly saturated and/or single‐scan data sets. It is statistically rigorous, correctly treating the underlying statistical distribution of the data. It is also compatible with Bayesian methods for incorporating prior knowledge about sample properties. An efficient iterative scheme for solving the proposed equations is presented for the case of the bilinear model commonly used in analyses of SIMS data. The correctness of the approach and its efficacy are demonstrated on synthetic data sets. The method is found to perform better than a widely‐used data‐correction method used in combination with alternating‐least‐squares Multivariate Curve Resolution analysis. Copyright © 2015 John Wiley & Sons, Ltd.     

Performance of multicomponent self-organizing regression (MCSOR) in QSAR,QSPR, and multivariate calibration: comparison with partial least-squares (PLS) and validation with large external data sets

A novel method for underdetermined regression problems, multicomponent self-organizing regression (MCSOR), has been recently introduced. Here, its performance is compared with partial least-squares (PLS), which is perhaps the most widely adopted multivariate method in chemometrics. A potpourri of models is presented, and MCSOR appears to provide highly predictive models that are comparable with or better than the corresponding PLS models in large internal (leave-one-out, LOO) and pseudo-external (leave-many-out, LMO) validation tests. The “blind” external predictive ability of MCSOR and PLS is demonstrated employing large melting point, factor Xa, log?P and log?S data sets. In a nutshell, MCSOR is fast, conceptually simple (employing multiple linear regression, MLR, as a statistical tool), and applicable to all kinds of multivariate problems with single Y-variable.     

Combretastatins类微管蛋白抑制剂的定量构效关系与结合模式

以Combretastatins的B环改造化合物为研究对象, 采用遗传函数分析方法进行了二维定量构效关系研究. 研究结果表明, Apol, PMI-mag, Dipole-mag, Hbond donor和RadOfGyration等描述符对该系列抑制剂活性的贡献最大. 采用比较分子场分析方法(CoMFA)和比较分子相似因子分析方法(CoMSIA)进行了三维定量构效关系研究, 建立的CoMFA和CoMSIA模型的交叉验证相关系数q2分别为0.630和0.634, 具有较强的预测能力. 利用CoMFA和CoMSIA模型的三维等势图解析了Combretastatins类化合物的构效关系, 阐明了B环上各取代基对抑制微管蛋白聚合活性的影响, 同时应用分子对接方法分析并验证了定量构效关系模型.     

On QSAR Study of Stereoselectivity for Wittig Reaction

1INTRODUCTION Witting reaction is an important and well-known organic reaction.In this reaction system,phospho-nium ylides react with aldehydes or ketones to gene-rate olefins and phosphonium oxides.Obviously,the position of double bond in olefins is exactly the po-sition of carbonyl group in the reactants,so there are no other position isomers in products.Due to this advantage,Witting reaction has been widely used in organic synthesis[1].Witting reaction could introduce double bond to c…     

QSAR study and VolSurf characterization of anti-HIV quinolone library

Antiviral quinolones are promising compounds in the search for new therapeutically effective agents for the treatment of AIDS. To rationalize the SAR for this new interesting class of anti-HIV derivatives, we performed a 3D-QSAR study on a library of 101 6-fluoro and 6-desfluoroquinolones, taken either from the literature or synthesized by us. The chemometric procedure involved a fully semiempirical minimization of the molecular structures by the AMSOL program, which takes into account the solvatation effect, and their 3D characterization by the VolSurf/GRID program. The QSAR analysis, based on PCA and PLS methods, shows the key structural features responsible for the antiviral activity.     

3D‐QSAR studies and molecular design on a novel series of pyrimidine benzimidazoles as Lck inhibitors

The development of selective lymphocyte‐specific kinase (Lck) inhibitors has attracted much attention for the research of the treatment of T‐cell mediated autoimmune and inflammatory diseases. In the present work, three‐dimensional quantitative structure–activity relationship (3D‐QSAR) analyses are performed on a novel series of 4‐amino‐6‐benzimidazole‐pyrimidines acting as Lck inhibitors. The established 3D‐QSAR models show significant statistical quality and satisfactory predictive ability, with high q² and R² values: the comparative molecular field analysis (CoMFA) model (q² = 0.802, R² = 0.991), and the comparative molecular similarity indexes analysis (CoMSIA) model (q² = 0.731, R² = 0.982). The systemic external validation indicates that both CoMFA and CoMSIA models are quite robust and possess high predictive abilities with values of 0.881 and 0.877, values of 0.897 and 0.847, values of 0.897 and 0.850, and values of 0.897 and 0.854, respectively. Several key structural features accounting for the inhibitory activities of these compounds are discussed. Based on established models and design considerations, six new compounds with significantly improved activities are theoretically designed, which still await experimental confirmation and evaluation. These theoretical results may provide a useful reference for understanding the action mechanism and designing novel potential Lck inhibitors. © 2014 Wiley Periodicals, Inc.