QSAR modeling using a set of intermediate-duration oral NOELs Público

Abstract

Purpose

The purpose of the project is to investigate the utility of data collected at the National Institute of Health Science in Japan for quantitative structure-activity relationship (QSAR) modeling. The hypothesis being tested is that a linear relationship exists between a chemical compound's structural and physicochemical characteristics and its no observed effect level (NOEL).

Methods

The data that was used included a set of intermediate-duration oral NOELs that are publicly accessible on the website of the National Institute of Health Science in Japan ( http://www.nihs.go.jp/index-j.html ). The software, Leadscope Predictive Data Miner, was used to build an associative model and to analyze the correlation between observed NOELs and calculated NOELs.

Results

The results showed that Leadscope PDM selected 117 structural characteristics (e.g., sulfonate, 1-hydoroxynaphthalen, 3-hydroxy-1-benzensulfonate, etc.) and 7 physicochemical characteristics (e.g., hydrogen bond acceptors, polar surface area, ALogP, etc.) for 218 compounds that were entered into the software. An associative model with one latent descriptor, called a PLS factor, was then developed. The Leadscope PDM program provided visualization of the correlation between observed NOELs and calculated NOELs. The R² was 0.35, and cross-validated R² was 0.21.

Conclusions

Overall, this analysis provided little evidence for utility of the data. This was because the hypothesis could not be proven with the available data and model. This project did demonstrate a good example of QSAR modeling using NOELs and Leadscope software as evidenced by the results of this study. It is anticipated that this project will facilitate further QSAR studies in the near future utilizing the data already generated.

Table of Contents

1. Introduction 1
2. Methods 6
3. Results 12
4. Discussion 19
5. Conclusion 24
6. References 25
Appendices 28
I. General Information for the 218 Chemical Compounds 28
II. Experimental Data 39
III. Chemical Structures of the 218 Chemical Compounds 46

About this Master's Thesis

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School	Rollins School of Public Health
Department	Environmental Health
Degree	MPH
Submission	Master's Thesis
Language	English
Research Field	Health Sciences, Toxicology
Palavra-chave	Japan QSAR quantitative structure activity relationship Leadscope NOEL
Committee Chair / Thesis Advisor	Yang, Liu, Emory University
Committee Members	Tolbert, Paige, Emory University Demchuk, Eugene, CDC
Partnering Agencies	Non-US governmental agency (e.g., Minister of Health in Haiti) CDC

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