Chapter title |
A Round Trip from Medicinal Chemistry to Predictive Toxicology.
|
---|---|
Chapter number | 19 |
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_19 |
Pubmed ID | |
Book ISBNs |
978-1-4939-3607-6, 978-1-4939-3609-0
|
Authors |
Giuseppe Felice Mangiatordi, Angelo Carotti, Ettore Novellino, Orazio Nicolotti |
Editors |
Emilio Benfenati |
Abstract |
Predictive toxicology is a new emerging multifaceted research field aimed at protecting human health and environment from risks posed by chemicals. Such issue is of extreme public relevance and requires a multidisciplinary approach where the experience in medicinal chemistry is of utmost importance. Herein, we will survey some basic recommendations to gather good data and then will review three recent case studies to show how strategies of ligand- and structure-based molecular design, widely applied in medicinal chemistry, can be adapted to meet the more restrictive scientific and regulatory goals of predictive toxicology. In particular, we will report: Docking-based classification models to predict the estrogenic potentials of chemicals. Predicting the bioconcentration factor using biokinetics descriptors. Modeling oral sub-chronic toxicity using a customized k-nearest neighbors (k-NN) approach. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 5 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Librarian | 1 | 20% |
Student > Ph. D. Student | 1 | 20% |
Professor > Associate Professor | 1 | 20% |
Researcher | 1 | 20% |
Unknown | 1 | 20% |
Readers by discipline | Count | As % |
---|---|---|
Pharmacology, Toxicology and Pharmaceutical Science | 1 | 20% |
Unknown | 4 | 80% |