The Using of the Index of Ideality of Correlation (IIC) to Improve Predictive Potential of Models of Water Solubility for Pesticides

Overview

Journal Environ Sci Pollut Res Int

Publisher Springer

Specialties Environmental Health
Toxicology

Date 2020 Feb 6

PMID 32020455

Citations 3

Authors

Alla P Toropova

Andrey A Toropov

Edoardo Carnesecchi

Emilio Benfenati

Jean Lou Dorne

Affiliations

Soon will be listed here.

Abstract

Models for water solubility of pesticides suggested in this manuscript are important data from point of view of ecologic engineering. The Index of Ideality of Correlation (IIC) of groups of quantitative structure-property relationships (QSPRs) for water solubility of pesticides related to the calibration sets was used to identify good in silico models. This comparison confirmed the high IIC set provides better statistical quality of the model for the validation set. Though there are large databases on solubility, the reliable prediction of the endpoint for new substances which are potential pesticides is an important ecologic task. Unfortunately, predictive models for various endpoints suffer overtraining, and the IIC serves to avoid or at least reduce this. Thus, the approach suggested has both theoretical and economic effects for ecology.

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