Atom-type-based AI topological descriptors: application in structure-boiling point correlations of oxo organic compounds

Structure-boiling point relationships are studied for a series of oxo organic compounds by means of multiple linear regression (MLR) analysis. Excellent MLR models based on the recently introduced Xu index and the atom-type-based AI indices are obtained for the two subsets containing respectively 77 ethers and 107 carbonyl compounds and a combined set of 184 oxo compounds. The best models are tested using the leave-one-out cross-validation and an external test set, respectively. The MLR model produces a correlation coefficient of r = 0.9977 and a standard error of s = 3.99 degrees C for the training set of 184 compounds, and r(cv) = 0.9974 and s(cv) = 4.16 degrees C for the cross-validation set, and r(pred) = 0.9949 and s(pred) = 4.38 degrees C for the prediction set of 21 compounds. For the two subsets containing respectively 77 ethers and 107 carbonyl compounds, the quality of the models is further improved. The standard errors are reduced to 3.30 and 3.02 degrees C, respectively. Furthermore, the results obtained from this study indicate that the boiling points of the studied oxo compound dominantly depend on molecular size and also depend on individual atom types, especially oxygen heteroatoms in molecules due to strong polar interactions between molecules. These excellent structure-boiling point models not only provide profound insights into the role of structural features in a molecule but also illustrate the usefulness of these indices in QSPR/QSAR modeling of complex compounds.     

New atom-type-based AI topological indices: Application to QSPR studies of aldehydes and ketones

Multiple linear regression (MLR) analysis based on a combined use of the modified Xu index and the atom-type based AI indices is performed to construct quantitative structure-property models on several data sets of organic compounds including aliphatic aldehydes and/or ketones. For each of the physical properties (the normal boiling points, molar refractions, gas heat capacities at 25 degrees C, water solubility at 25 degrees C, and n-octanol/water partition coefficient at 25 degrees C), high quality QSPR models are obtained, particularly the decrease in the standard error is within the range of 23.6-75.9% relative to the linear models with the modified Xu index alone. For individual subsets containing only aldehydes or ketones, in the majority of cases the quality of the model can be further improved. The significant improvement verifies the efficiency of the present approach and also indicates the usefulness of these indices for application to a wide range of physical properties. The results indicate that the physical properties studied are dominated by molecular size but atom types have smaller influences, especially the oxygen atom seems to be most important due to intermolecular polar interactions. The final models are validated to be statistically reliable using the leave-one-out cross-validation and/or an external test set.     

On the topological sub-structural molecular design (TOSS-MODE) in QSPR/QSAR and drug design research

A recently introduced graph-theoretical approach to the study of structure-property-activity relationships is presented. The theoretical approach and the computational strategy for the use of the TOSS-MODE approach are given with details. Several QSPR and QSAR applications are reviewed including the study of physical properties of organic compounds, diamagnetic susceptibilities, and biological properties. The applications of the TOSS-MODE approach to discrimination of active/inactive compounds, the virtual screening of compounds with a desired property from databases of chemical structures, identification of active/inactive fragments and its relationships with 2D/3D pharmacophores, and to the design of novel compounds with desired biological activities are also reviewed.     

QSAR/QSPR在POPs归趋与风险评价中的应用

持久性有机污染物(POPs)是目前备受国际社会关注的高危害性有机污染物,对它们的环境归趋分析和风险评价需要获得大量可靠的性质数据和毒性数据,而定量结构活性/性质相关(QSAR/QSPR)方法为快速有效地获得这些数据提供了可能性。QSAR/QSPR模型已在预测POPs的生物活性/性质,补充缺失的基础数据及探求POPs的环境过程机制和生态效应机理等方面得到了广泛应用,近年来也在新POPs物质的筛选、归趋模拟以及风险评价等方面有着更进一步的应用或潜在应用前景。本文介绍了QSAR/QSPR在POPs性质和生物活性预测中的基本应用及其在POPs归趋和风险评价中的扩展应用,并对QSAR/QSPR在POPs研究领域的应用前景进行了展望。     

On the Topological Sub-Structural Molecular Design (TOSS-MODE) in QSPR/QSAR and Drug Design Research

Abstract

A recently introduced graph-theoretical approach to the study of structure-property-activity relationships is presented. The theoretical approach and the computational strategy for the use of the TOSS-MODE approach are given with details. Several QSPR and QSAR applications are reviewed including the study of physical properties of organic compounds, diamagnetic susceptibilities, and biological properties. The applications of the TOSS-MODE approach to discrimination of active/inactive compounds, the virtual screening of compounds with a desired property from databases of chemical structures, identification of active/inactive fragments and its relationships with 2D/3D pharmacophores, and to the design of novel compounds with desired biological activities are also reviewed.     

一种新的分子拓扑指数及其在QSPR/QSAR研究中的应用

通过引入量子数、键参数,认为分子的性质与其中各原子的电负性、价电子数、成键电子数、价层主量子数及各化学键的键长有关,提出了一种新的分子拓扑指数mAY.采用该拓扑指数对饱和烷烃、烷基苯、烷氧氯硅烷、卤代苯、含氮杂环化合物、碱金属卤化物及卤化锡的性质/活性进行了相关关系的研究.结果表明,mAY与有机物和无机物的性质/活性间具有良好的相关性.     

A generalized graph-theoretical matrix of heterosystems and its application to the VMV procedure

The extensions of generalized (molecular) graph-theoretical matrix and vector-matrix-vector procedure are considered. The elements of the generalized matrix are redefined in order to describe molecules containing heteroatoms and multiple bonds. The adjacency, distance, detour and reciprocal distance matrices of heterosystems, and corresponding vectors are derived from newly defined generalized graph matrix. The topological indices, which are most widely used in predicting physicochemical and biological properties/activities of various compounds, can be calculated from the new generalized vector-matrix-vector invariant.     

Modification of the Wiener index 4

A novel topological index W(F) is defined by the matrices X, W, and L as W(F) = XWL. Where L is a column vector expressing the characteristic of vertices in the molecule; X is a row vector expressing the bonding characteristics between adjacent atoms; W is a reciprocal distance matrix. The topological index W(F), based on the distance-related matrix of a molecular graph, is used to code the structural environment of each atom type in a molecular graph. The good QSPR/QSAR models have been obtained for the properties such as standard formation enthalpy of inorganic compounds and methyl halides, retention indices of gas chromatography of multiple bond-containing hydrocarbons, aqueous solubility, and octanol/water partition of benzene halides. These models indicate that the idea of using multiple matrices to define the modified Wiener index is valid and successful.     

一个新的拓扑指数用于有机化合物的QSPR/QSAR研究

在分子图的邻接矩阵和距离矩阵的基础上提出了一个新的拓扑指数Xu,该拓扑指数易于计算,对C~2-C~1~6饱和烷烃有较高的结构区分能力,通过适当的处理可方便地推广到含多重键杂原子体系。该指数与饱和烷烃的正常沸点等理化性质,不饱和链烃类化合物的热容以及某些脂肪醇的毒性和疏水性参数均具有较好的性质相关性。绝大多数理化性质与Xu指数均能建立简单线性模型,且相关系数均大于0.99,表明该指数有望在QSPR/QSAR研究中作为一个新的参数而获得推广应用。     

A novel PI index and its applications to QSPR/QSAR studies

A novel topological index, PI (Padmakar-Ivan index), is derived in this paper. The index is very simple to calculate and has disseminating power similar to that of the Wiener (W) and the Szeged (Sz) indices. The comprehensive studies show that the proposed PI index correlates highly with W and Sz as well as with physicochemical properties and biological activities of a large number of diversified and complex compounds. The proposed PI index promises to be a useful parameter in the QSPR/QSAR studies. The stability of each model is demonstrated by applying cross-validation test. Furthermore, more favorable comparison with other representative indices such as the Randic index is also made in order to establish the predictive ability of the PI index. The results have shown that in several cases the PI index gave better results.     

Open computing grid for molecular science and engineering

Grid is an emerging infrastructure for distributed computing that provides secure and scalable mechanisms for discovering and accessing remote software and data resources. Applications built on this infrastructure have great potential for addressing and solving large scale chemical, pharmaceutical, and material science problems. The article describes the concept behind grid computing and will present the OpenMolGRID system that is an open computing grid for molecular science and engineering. This system provides grid enabled components, such as a data warehouse for chemical data, software for building QSPR/QSAR models, and molecular engineering tools for generating compounds with predefined chemical properties or biological activities. The article also provides an overview about the availability of chemical applications in the grid.