Chapter title |
VirtualToxLab: Exploring the Toxic Potential of Rejuvenating Substances Found in Traditional Medicines.
|
---|---|
Chapter number | 7 |
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_7 |
Pubmed ID | |
Book ISBNs |
978-1-4939-3607-6, 978-1-4939-3609-0
|
Authors |
Martin Smieško, Angelo Vedani |
Editors |
Emilio Benfenati |
Abstract |
Docking and quantifying the binding of small molecules to the 3D structure of a macromolecular bioregulator by computational techniques is a typical task in R&D aimed at the design and optimization of medically or otherwise active compounds. Much less known is the fact that these methods can be successfully applied for the purpose of toxicity prediction-for example, detecting a compound's potential binding to so-called "off-targets" already at the preclinical stage. In this chapter, we provide an overview of such a computational approach, discuss its strengths and weaknesses, and include a case study-focused on natural compounds present in traditional medicines. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 9 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 3 | 33% |
Other | 2 | 22% |
Lecturer > Senior Lecturer | 1 | 11% |
Student > Bachelor | 1 | 11% |
Student > Doctoral Student | 1 | 11% |
Other | 0 | 0% |
Unknown | 1 | 11% |
Readers by discipline | Count | As % |
---|---|---|
Pharmacology, Toxicology and Pharmaceutical Science | 3 | 33% |
Medicine and Dentistry | 2 | 22% |
Neuroscience | 1 | 11% |
Environmental Science | 1 | 11% |
Unknown | 2 | 22% |