Using variable and fixed topological indices for the prediction of reaction rate constants of volatile unsaturated hydrocarbons with OH radicals.

Matevz Pompe,Marjan Veber,Alexandru T Balaban,Milan Randić

doi:10.3390/91201160

Abstract

Volatile organic compounds (VOCs) play an important role in different photochemical processes in the troposphere. In order to predict their impact on ozone formation processes a detailed knowledge about their abundance in the atmosphere as well as their reaction rate constants is required. The QSPR models were developed for the prediction of reaction rate constants of volatile unsaturated hydrocarbons. The chemical structure was encoded by constitutional and topological indices. Multiple linear regression models using CODESSA software was developed with the RMS(CV) error of 0.119 log units. The chemical structure was encoded by six topological indices. Additionally, a regression model using a variable connectivity index was developed. It provided worse cross-validation results with an RMS(CV) error of 0.16 log units, but enabled a structural interpretation of the obtained model. We differentiated between three classes of carbon atoms: sp2-hybridized, non-allylic sp3-hybridized and allylic sp3-hybridized. The structural interpretation of the developed model shows that most probably the most important mechanisms are the addition to multiple bonds and the hydrogen atom abstraction at allylic sites.

Highlights

The reactions of volatile organic compounds (VOCs) of biogenic and anthropogenic origin play an important role in different atmospheric photochemical processes
The quantitative structure property relationship (QSPR) models were developed for the prediction of reaction rate constants of volatile unsaturated hydrocarbons
The multiple linear regression (MLR) models with up to 10 parameters were selected based on the best cross-validation capabilities obtained by leave-one-out cross-validation procedure

Summary

Introduction

The reactions of volatile organic compounds (VOCs) of biogenic and anthropogenic origin play an important role in different atmospheric photochemical processes. Several quantitative structure property relationship (QSPR) prediction models were developed to predict reaction rate constants for the reaction of OH radicals with different organic species. These methods offered models with, at least, moderate prediction capabilities Their use was mostly restricted because of a limited knowledge about the reaction pathways, limited databases with experimental molecular properties, or due to the extensive computations necessary for ab initio molecular orbital calculations. All these drawbacks are bypassed in QSPR models using molecular structural descriptors

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