Comparative QSTR Study Using Semi-Empirical and First Principle Methods Based Descriptors for Acute Toxicity of Diverse Organic Compounds to the Fathead Minnow

Erol Eroglu,Cihat Ozaydın,Hasan Turkmen,Oral Oltulu,Selami Palaz

doi:10.3390/ijms8121265

Abstract

Several quantum-mechanics-based descriptors were derived for a diverse set of 48 organic compounds using AM1, PM3, HF/6-31+G, and DFT-B3LYP/6-31+G (d) level of the theory. LC50 values of acute toxicity of the compounds were correlated to the fathead minnow and predicted using calculated descriptors by employing Comprehensive Descriptors for Structural and Statistical Analysis (CODESSA) program. The heuristic method, implemented in the CODESSA program for selecting the ‘best’ regression model, was applied to a pre-selection of the most-representative descriptors by sequentially eliminating descriptors that did not satisfy a certain level of statistical criterion. First model, statistically, the most significant one has been drawn up with the help of DFT calculations in which the squared correlation coefficient R2 is 0.85, and the squared cross-validation correlation coefficient is 0.79. Second model, which has been drawn up with the help of HF calculations, has its statistical quality very close to the DFT-based one and in this model value of R2 is 0.84 and that of is 0.78. Third and fourth models have been drawn up with the help of AM1 and PM3 calculations, respectively. The values of R2 and in the third case are correspondingly 0.79 and 0.66, whereas in the fourth case they are 0.78 and 0.65 respectively. Results of this study clearly demonstrate that for the calculations of descriptors in modeling of acute toxicity of organic compounds to the fathead minnow, first principal methods are much more useful than semi-empirical methods.

Highlights

Many of QSAR studies are based on the assumption that molecules from the same chemical domain will behave in a similar manner, so that QSAR models drawn up with the analogical molecules are hypothesized to exhibit better performance than that derived from miscellaneous data set
Forty-eight compounds have been taken in this study, and their toxicity (LogLC50) and calculated logarithm of 1-octanol/water partition coefficient (LogP) values to fathead minnow have been taken from the literature [12] and are given in DFT-B3LYP) and semi-empirical (AM1 and PM3) methods calculations are shown in Table 2 to 5
Results presented in this study demonstrates that quantum mechanically calculated thermo chemical descriptors in combination with LogP are capable of modeling the acute toxicity of a quite diverse set of 48 compounds to the fathead minnow

Summary

Introduction

Many of QSAR studies are based on the assumption that molecules from the same chemical domain will behave in a similar manner, so that QSAR models drawn up with the analogical molecules are hypothesized to exhibit better performance than that derived from miscellaneous data set. The traditional approach to QSARs for acute toxicity of organic compounds to the fathead minnow is the modeling of the activity of homologous or congeneric series of chemicals such as nitroaromatics [1], alkylamines [2], halogenated hydrocarbons and phenols [3], and chlorobenzenes and chloroalinines [4]. It is worthy mention here that there has been a successful effort to draw up a global QSTR model by using a single descriptor, namely, logarithm of 1octanol/water partition coefficient LogP This model is applicable to quite miscellaneous data set, but still counts quite a big number of molecules as outliers [12]. Developing a better QSTR for the modeling of acute toxicity of diverse chemicals is a subject of interest due to its demand by the organizations such as OECD (Organization for Economic Co-operation and Development) or EC (European Communities) to use the QSTR model for regulatory purpose

Objectives

Methods

Results

Discussion

Conclusion