Computational Approaches to Nuclear Receptors: Volume 30

Computational Approaches to Nuclear Receptors: Volume 30 book cover

Computational Approaches to Nuclear Receptors: Volume 30

Author(s): Pietro Cozzini

  • Publisher: Royal Society of Chemistry
  • Publication Date: 2 Nov. 2012
  • Edition: Illustrated
  • Language: English
  • Print length: 176 pages
  • ISBN-10: 1849733643
  • ISBN-13: 9781849733649

Book Description

The aim of this book is to provide a state of the art review on investigations into Nuclear Receptors

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From the Back Cover

Nuclear Receptors (NRs) are ligand-induced activated transcription factors that are involved in numerous biological processes. Since the 90’s when the first structures were determined by means of X-ray diffraction, the number has increased considerably. Moreover several “omics” projects have opened up great opportunities for the discovery of new targets, the characterization of abnormal protein patterns, the selection of “tailored” drugs and the evaluation of drug efficacy even with a lack of structural data. Furthermore, structure-based drug design, computational methods for in silico screening and nanobiotechnology-based tools are simplifying this time-consuming and expensive research of identifying lead compounds and, possibly new drugs. Biological interactions such as those that occur between a protein and ligand are concerted events where flexible molecules interact. Understanding the flexibility of large molecules or biological complexes is of primary importance to help define the right model to approximate the reality for drug discovery, virtual screening and food safety analysis. NRs are known as flexible targets, with many structural similarities, in particular for their Ligand Binding Domain. To understand the behaviour of NRs, it is mandatory to approach the subject from a different perspective. The aim of this book is to provide a state-of- the-art review on investigations into Nuclear Receptors. The contents provide an introduction to their structure and function, a critical overview of experimental structural data as a base for modeling, development of theoretical approaches to modeling and computational studies to predict interactions with small ligands, in vitro and in vivo experiments to validate computational simulations, experimental applications, and as targets for endocrine disruptor screening.

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