Related Experiment Video
Updated: Mar 19, 2026

In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox
Published on: August 28, 2019
QSAR Methods
1DEIB, Politecnico di Milano, Milano, Italy. gini@elet.polimi.it.
Abstract:
In this chapter, we introduce the basis of computational chemistry and discuss how computational methods have been extended to some biological properties and toxicology, in particular. Since about 20 years, chemical experimentation is more and more replaced by modeling and virtual experimentation, using a large core of mathematics, chemistry, physics, and algorithms. Then we see how animal experiments, aimed at providing a standardized result about a biological property, can be mimicked by new in silico methods. Our emphasis here is on toxicology and on predicting properties through chemical structures. Two main streams of such models are available: models that consider the whole molecular structure to predict a value, namely QSAR (Quantitative Structure Activity Relationships), and models that find relevant substructures to predict a class, namely SAR. The term in silico discovery is applied to chemical design, to computational toxicology, and to drug discovery. We discuss how the experimental practice in biological science is moving more and more toward modeling and simulation. Such virtual experiments confirm hypotheses, provide data for regulation, and help in designing new chemicals.
More Related Videos
Related Concept Videos
Structure-Activity Relationships and Drug Design
SAR studies the intricate relationship between a drug's chemical structure and biological activity. It focuses on understanding how modifications to a drug's structure can influence...
2D NMR: Heteronuclear Single-Quantum Correlation Spectroscopy (HSQC)
Quantitative Aspects of Drug-Receptor Interaction
Qualitative Analysis
There are two main approaches to qualitative analysis:...
Response Surface Methodology
The process of RSM involves several key steps:
Mechanistic Models: Compartment Models in Individual and Population Analysis

