Chapter title |
QSAR Methods.
|
---|---|
Chapter number | 1 |
Book title |
In Silico Methods for Predicting Drug Toxicity
|
Published in |
Methods in molecular biology, January 2016
|
DOI | 10.1007/978-1-4939-3609-0_1 |
Pubmed ID | |
Book ISBNs |
978-1-4939-3607-6, 978-1-4939-3609-0
|
Authors |
Giuseppina Gini |
Editors |
Emilio Benfenati |
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. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 27 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 6 | 22% |
Student > Bachelor | 5 | 19% |
Student > Ph. D. Student | 4 | 15% |
Other | 1 | 4% |
Student > Doctoral Student | 1 | 4% |
Other | 3 | 11% |
Unknown | 7 | 26% |
Readers by discipline | Count | As % |
---|---|---|
Pharmacology, Toxicology and Pharmaceutical Science | 4 | 15% |
Chemistry | 3 | 11% |
Computer Science | 3 | 11% |
Biochemistry, Genetics and Molecular Biology | 3 | 11% |
Agricultural and Biological Sciences | 2 | 7% |
Other | 2 | 7% |
Unknown | 10 | 37% |