Drug Metabolism Prediction, Volume 63. Methods and Principles in Medicinal Chemistry

  • ID: 2865996
  • Book
  • 536 Pages
  • John Wiley and Sons Ltd
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The first professional reference on this highly relevant topic, for drug developers, pharmacologists and toxicologists.

The authors provide more than a systematic overview of computational tools and knowledge bases for drug metabolism research and their underlying principles. They aim to convey their expert knowledge distilled from many years of experience in the field. In addition to the fundamentals, computational approaches and their applications, this volume provides expert accounts of the latest experimental methods for investigating drug metabolism in four dedicated chapters. The authors discuss the most important caveats and common errors to consider when working with experimental data.

Collating the knowledge gained over the past decade, this practice–oriented guide presents methods not only used in drug development, but also in the development and toxicological assessment of cosmetics, functional foods, agrochemicals, and additives for consumer goods, making it an invaluable reference in a variety of disciplines.

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PART I: INTRODUCTION

Metabolism in Drug Development

PART II: SOFTWARE, WEB SERVERS AND DATA RESOURCES TO STUDY METABOLISM

Software for Metabolism Prediction

Online Databases and Web Servers for Drug Metabolism Research

PART III: COMPUTATIONAL APPROACHES TO STUDY CYTOCHROME P450 ENZYMES

Structure and Dynamics of Human Drug–Metabolizing Cytochrome P450 Enzymes

Cytochrome P450 Substrate Recognition and Binding

QM/MM Studies of Structure and Reactivity of Cytochrome P450 Enzymes: Methodology and Selected Applications

Computational Free Energy Methods for Ascertaining Ligand Interaction with Metabolizing Enzymes

Experimental Approaches to Analysis of Reactions of Cytochrome P450 Enzymes

PART IV: COMPUTATIONAL APPROACHES TO STUDY SITES AND PRODUCTS OF METABOLISM

Molecular Interaction Fields for Predicting the Sites and Products of Metabolism

Structure–Based Methods for Predicting the Sites and Products of Metabolism

Reactivity–Based Approaches and Machine Learning Methods for Predicting the Sites of Cytochrome P450–Mediated Metabolism

Knowledge–Based Approaches for Predicting the Sites and Products of Metabolism

PART V: COMPUTATIONAL APPROACHES TO STUDY ENZYME INHIBITION AND INDUCTION

Quantitative Structure–Activity Relationship (QSAR) Methods for the Prediction of Substrates, Inhibitors and Inducers of Metabolic Enzymes

Pharmacophore–Based Methods for Predicting the Inhibition and Induction of Metabolic Enzymes

Prediction of Phosphoglycoprotein (P–gp)–Mediated Disposition in Early Drug Discovery

Predicting Toxic Effects of Metabolites

PART VI: EXPERIMENTAL APPROACHES TO STUDY METABOLISM

In vitro Models for Metabolism: Applicability for Research on Food Bioactives

In vitro Approaches to Study Drug–Drug Interactions

Metabolite Detection and Profiling

Index
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Dr. Johannes Kirchmair is currently a lead researcher at the Institute of Pharmaceutical Sciences at ETH Zurich, Switzerland. He received his PhD in medicinal chemistry from the University of Innsbruck, Austria, and subsequently worked as an application scientist for Inte:Ligand in Vienna, Austria, before returning to his Alma Mater as an Assistant Professor. In 2009 he joined BASF SE Ludwigshafen, Germany, where he was responsible for the computational optimization of fungicide leads. From 2010 to 2013 he worked as a senior research associate at the Unilever Centre for Molecular Sciences Informatics, University of Cambridge (UK), where he developed computational methods for drug metabolism prediction. His main research interests include molecular informatics, bioinformatics, medicinal chemistry, and drug design.
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