This paper gives an overview of the mathematical methods currently used in quantitative structure-activity/property relationship (QASR/QSPR) studies. Recently, the mathematical methods applied to the regression of QASR/QSPR models are developing very fast, and new methods, such as Gene Expression Programming (GEP), Project Pursuit Regression (PPR) and Local Lazy Regression (LLR) have appeared o...

In this paper, we report on the potential of a recently developed neural network for structures applied to the prediction of physical chemical properties of compounds. The proposed recursive neural network (RecNN) model is able to directly take as input a structured representation of the molecule and to model a direct and adaptive relationship between the molecular structure and target property...

Quantitative structure-property relationship (QSPR) models are developed to predict the logarithm of infinite dilution activity coefficient of hydrocarbons, oxygen containing organic compounds and halogenated hydrocarbons in water at 298.15 K. The description of the molecular structure in terms of quantum-connectivity descriptors allows to obtain more simple QSPR models because of the quantum-c...

Abstract Topological index is a numerical value associated with chemical constitution for correlation of structure various physical properties, reactivity or biological activity. In this work, some new indices based on neighborhood degree sum nodes are proposed. To make the computation novel convenient, an algorithm designed. Quantitative property relationship (QSPR) study good statistical meth...

The vapor pressures and the aqueous solubilities of 411 compounds with a large structural diversity were investigated using a quantitative structure-property relationship (QSPR) approach. A five-descriptor equation with the squared correlation coefficient (R2) of 0.949 for vapor pressure and a six-descriptor equation with R2 of 0.879 for aqueous solubility were obtained. All descriptors were de...

One of the most recent developments in field graph theory is analysis networks such as Butterfly networks, Benes Interconnection and David-derived using theoretic parameters. The topological indices (TIs) have been widely used invariants among various tools. Quantitative structure activity relationships (QSAR) quantitative property (QSPR) need use TIs. Different structure-based parameters, degr...

Quantitative structure-property relationships (QSPRs) for estimating the logarithm octanol/water partition coefficients, logK(ow), at 25 degrees C were developed based on fuzzy ARTMAP and back-propagation neural networks using a heterogeneous set of 442 organic compounds. The set of molecular descriptors were derived from molecular connectivity indices and quantum chemical descriptors calculate...

Quantitative structure-property relationship (QSPR) for estimating the adsorption of aliphatic alcohols onto activated carbon were developed using substructural molecular fragments (SMF) method. The adsorption capacity of activated carbon (gr/100grC) for 150 aliphatic alcohols onto activated carbon (AC) is studied under equilibrium conditions. Forward and backwards stepwise regression variable ...

Many organic chemicals are ionizable by nature. After use and release into the environment, various fate processes determine their concentrations, and hence exposure to aquatic organisms. In the absence of suitable data, such fate processes can be estimated using Quantitative Structure-Property Relationships (QSPRs). In this review we compiled available QSPRs from the open literature and assess...

Quantitative structure-property relationships (QSPRs) for estimating aqueous solubility of organic compounds at 25 degrees C were developed based on a fuzzy ARTMAP and a back-propagation neural networks using a heterogeneous set of 515 organic compounds. A set of molecular descriptors, developed from PM3 semiempirical MO-theory and topological descriptors (first-, second-, third-, and fourth-or...