Genetic algorithm and partial least square (GA-PLS), the kernel PLS (KPLS) and Levenberg-Marquardt artificial neural network (L-M ANN) techniques were used to investigate the correlationbetween retention time (RT) and descriptors for 15 nanoparticle compounds which obtained by thecomprehensive two dimensional gas chromatography system (GC x GC). Application of thedodecanethiol monolayer-protect...

predictive quantitative structure–activity relationship was performed on the novel 4-oxo-1,4-dihydroquinoline and 4-oxo-4h-pyrido[1,2-a]pyrimidine derivatives to explore relationship between the structure of synthesized compounds and their anti-hiv-1 activities. in this way, the suitable set of the molecular descriptors was calculated and the important descriptors using the variable selections ...

Topological indices are the numerical value associated with chemical constitution purporting for correlation of chemical structure with various physical properties, chemical reactivity or biological activity. Graph theory is a delightful playground for the exploration of proof techniques in Discrete Mathematics and its results have applications in many areas of sciences. One of the useful indic...

During the search for new structural descriptors we have defined the information-theory operators U(M), V(M), X(M), and Y(M), that are computed from atomic invariants and measure the information content of the elements of molecular matrices. Structural descriptors computed with these four information-theory operators are used to develop structure-property models for the boiling temperature, mol...

in this work some quantitative structure activity relationship models were developed for prediction of three bioenvironmental parameters of 28 volatile organic compounds, which are used in assessing the behavior of pollutants in soil. these parameters are; half-life, non dimensional effective degradation rate constant and effective péclet number in two type of soil. the most effective descripto...

The support vector machine (SVM), as a novel type of learning machine, for the first time, was used to develop a Quantitative Structure-Property Relationship (QSPR) model of the heat capacity of a diverse set of 182 compounds based on the molecular descriptors calculated from the structure alone. Multiple linear regression (MLR) and radial basis function networks (RBFNNs) were also utilized to ...

Quantitative structure-property relationship (QSPR) studies based on artificial neural network (ANN) and wavelet neural network (WNN) techniques were carried out for the prediction of solvent polarity. Experimental S' values for 69 solvents were assembled. This set included saturated and unsaturated hydrocarbons, solvents containing halogen, cyano, nitro, amide, sulfide, mercapto, sulfone, phos...

Relationships between the molecular structure and the critical micelle concentration (cmc) of anionic surfactants were investigated using a quantitative structure-property relationship approach. Measured cmc values for 119 anionic structures, representing sodium alkyl sulfates and sodium sulfonates with a wide variety of hydrophobic and hydrophilic structures, were considered. The best multiple...

A coumarin-based prodrug system plays a significant role in preparing esterase-sensitive prodrugs of amines and peptides. The electronic structures of 27 coumarin-based prodrugs developed in our lab were calculated at a B3LYP/6-31+G (d,p) level with a Gaussian 03 program. The calculated structural parameters were taken as theoretical descriptors to establish five novel QSPR models. The SMLR lin...