From Medicinal Chemistry to Food Science: A Transfer of In Silico Methods Applications


Pietro Cozzini (Editor)
Molecular Modelling Lab, Dept of Food Science, University of Parma, Parco Area delle Scienze, Parma, Italy

Series: Food Science and Technology
BISAC: TEC012000

The aim of this book is to illustrate the big opportunity to transfer computational techniques, well accepted and used in medicinal chemistry to food science; through this, we hope to discover new pollutants, possible dangerous food additives, contaminants from industries, xenoestrogens, etc. The paradigm is: if a molecule can interact with a receptor (i.e. a Nuclear Receptor), it can modify the signaling pathway and should be investigated to discover negative effects on food. The interaction can be predicted using in silico techniques well known by medicinal chemists to discover new lead compounds or to study the behavior of a protein ligand interaction.

The book starts with an introduction about the computational methods applied to food safety by authors coming from a big food company, who elucidate the importance of this approach for industries and food agencies. In Chapter Two, the authors give an overview of in vivo tests for food contaminant and toxin evaluation. In Chapter Three, in vitro and in silico models of digestion are compared. In Chapter Four, the authors, belonging both to an in silico lab and a wet lab use a case study of poliphenols to show how to merge in silico prediction and in vitro controls to gain time and money in estrogen receptors. Additionally, poliphenol binding studies use a molecule modeling approach. In Chapter Five, a non-typical docking approach is presented: a reverse docking approach.

Chapter Six and Seven introduce the problem of receptor flexibility and how to treat this important characteristic that must be considered in computational simulations. Chapter Eight is a review about QSAR methods well considered in this approach. Chapter Nine show a non-conventional informatics approach to ab initio in silico protein structure prediction. The last chapter is dedicated to the informatics requirements for in silico simulations to help researchers approaching this field.
(Imprint: Nova)

Table of Contents

Table of Contents


Chapter 1
Computational Methods Applied to Food Safety
(Elena Lo Piparo and Benoît Schilter, Nestlé Research Centre, Vers-Chez-Les-Blanc, Lausanne, Switzerland)

Chapter 2
In vivo Test for Food Contaminants and Toxins Evaluation
(N. Rizzi and S. Della Torre, University of Milan, Center of Excellence on Neurodegenerative Diseases and Department of Pharmacological and Biomolecular Sciences, Milan, Italy, and others)

Chapter 3
In-Vitro and In-Silico Models of Digestion: Limitations and Challenges
(Thomas Moxon, Clifford Latty, Ourania Gouseti, Serafim Bakalis, School of Chemical Engineering, The University of Birmingham, UK)

Chapter 4
Polyphenols: From Computer Simulations to Workbench Analysis
(Luca Dellafiora, Luca Calani, Daniele Del Rio, Pietro Cozzini, Department of Food Science, University of Parma, Parma, Italy, and others)

Chapter 5
Inverse Docking Approaches
(Scafuri Bernardina, Facchiano Angelo, Marabotti Anna, Dept. Chemistry and Biology, University of Salerno, Fisciano (SA), Italy, and others)

Chapter 6
Molecular Dynamics: An Emerging Tool For Exploring the Molecular Events in Food Research
(Tiziana Ginex, Constantí Seira, Carolina Estarellas, Axel Bidon-Chanal, F. Javier Luque, Molecular Modeling Laboratory, Department of Food Science, University of Parma, Parma, Italy, and others)

Chapter 7
Incorporating Protein Flexibility in Structure-Based Drug Design
(Francesca Spyrakis and Claudio N Cavasotto, Department of Life Sciences, University of Modena and Reggio Emilia, Modena, Italy, and others)

Chapter 8
How Qsar Changed the World of Drug Design, and Beyond …
(Hardik I. Parikh and Glen E. Kellogg, Department of Medicinal Chemistry, School of Pharmacy, Virginia Commonwealth University, Richmond, VA, USA, and others)

Chapter 9
Constraint-Based Computational Methods for Investigation of Protein Flexibility
(Alessandro Dal Palù, Agostino Dovier, Enrico Pontelli, Dept. of Mathematics and Computer Science, University of Parma, Parma, Italy, and others)

Chapter 10
A Quick Guide to Running Classical Molecular Dynamics on High Performance Computers
(Andrew Emerson, Cineca Supercomputing Centre, Casalecchio di Reno, Italy)


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