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E-grāmata: Molecular Interaction Fields: Applications in Drug Discovery and ADME Prediction

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Peter Goodford begins by explaining the basic principles of his GRID software for determining energetically favorable binding sites on molecules of known structure, which has been incorporated into many other software packages designed to predict the absorption, distribution, metabolism, and excretion (ADME) of a drug. Then chemists and pharmacologists from industry and academia in Europe and the US discuss calculating and applying molecular interaction fields, pharmacodynamics, and pharmacokinetics. The accompanying disk contains some software packages discussed in the text. Annotation ©2006 Book News, Inc., Portland, OR (booknews.com)

This unique reference source, edited by the world's most respected expert on molecular interaction field software, covers all relevant principles of the GRID force field and its applications in medicinal chemistry. Entire chapters on 3D-QSAR, pharmacophore searches, docking studies, metabolism predictions and protein selectivity studies, among others, offer a concise overview of this emerging field. As an added bonus, this handbook includes a CD-ROM with the latest commercial versions of the GRID program and related software.

Recenzijas

"This book is very useful for computational pharmaceutical scientists, medicinal chemists, biochemists, and pharmacologists..." (American Journal of Therapeutics, July/August 2006) "...a worthy volume in this series of monographs. It will become a good addition to the libraries of computational/modeling chemists..." (Journal of Medicinal Chemistry, May 18, 2006)

A Personal Foreword.
Preface.
List of Contributors.
I Introduction.
1 The Basic Principles of GRID (Peter Goodford).
1.1 Introduction.
1.2 Philosophy and Objectives.
1.3 Priorities.
1.4 The GRID Method.
1.5 The GRID Force Field.
1.6 Nomenclature.
1.7 Calibrating the GRID Force Field.
1.8 The Output from GRID.
1.9 Conclusions.
2 Calculation and Application of Molecular Interaction Fields (Rebecca C. Wade).
2.1 Introduction.
2.2 Calculation of MIFs.
2.3 Selected Applications of MIFs.
2.4 Concluding Remarks and Outlook.
II Pharmacodynamics.
3 Protein Selectivity Studies Using GRID-MIFs (Thomas Fox).
3.1 Introduction.
3.2 GRID Calculations and Chemometric Analysis.
3.3 Applications.
3.4 Discussion and Conclusion.
4 FLAP: 4-Point Pharmacophore Fingerprints from GRID (Francesca Perruccio, Jonathan S. Mason, Simone Sciabola, and Massimo Baroni).
4.1 Introduction.
4.2 FLAP Theory.
4.3 Docking.
4.4 Structure Based Virtual Screening (SBVS).
4.5 Ligand Based Virtual Screening (LBVS).
4.6 Protein Similarity.
4.7 TOPP (Triplets of Pharmacophoric Points).
4.8 Conclusions.
5 The Complexity of Molecular Interaction: Molecular Shape Fingerprints by the PathFinder Approach (Iain McLay, Mike Hann, Emanuele Carosati, Gabriele Cruciani, and Massimo Baroni).
5.1 Introduction.
5.2 Background.
5.3 The PathFinder Approach.
5.4 Examples.
5.5 Conclusions.
6 Alignment-independent Descriptors from Molecular Interaction Fields (Manuel Pastor).
6.1 Introduction.
6.2 GRIND.
6.3 How to Interpret a GRIND-based 3D QSAR Model.
6.4 GRIND Limitations and Problems.
6.5 Recent and Future Developments.
6.6 Conclusions.
7 3D-QSAR Using the GRID/GOLPE Approach (Wolfgang Sippl).
7.1 Introduction.
7.2 3D-QSAR Using the GRID/GOLPE Approach.
7.3 GRID/GOLPE Application Examples.
7.4 Conclusion.
III Pharmacokinetics.
8 Use of MIF-based VolSurf Descriptors in Physicochemical and Pharmacokinetic Studies (Raimund Mannhold, Giuliano Berellini, Emanuele Carosati, and Paolo Benedetti).
8.1 ADME Properties and Their Prediction.
8.2 VolSurf Descriptors.
8.3 Application Examples.
8.4 Conclusion.
9 Molecular Interaction Fields in ADME and Safety (Giovanni Cianchetta, Yi Li, Robert Singleton, Meng Zhang, Marianne Wildgoose, David Rampe, Jiesheng Kang, and Roy J. Vaz).
9.1 Introduction.
9.2 GRID and MIFs.
9.3 Role of Pgp Efflux in the Absorption.
9.4 HERG Inhibition.
9.5 CYP 3A4 Inhibition.
9.6 Conclusions.
10 Progress in ADME Prediction Using GRID-Molecular Interaction Fields (Ismael Zamora, Marianne Ridderstr.m, Anna-Lena Ungell, Tommy Andersson, and Lovisa Afzelius).
10.1 Introduction: ADME Field in the Drug Discovery Process.
10.2 Absorption.
10.3 Distribution.
10.4 Metabolism.
10.5 Conclusions.
11 Rapid ADME Filters for Lead Discovery (Tudor I. Oprea, Paolo Benedetti, Giuliano Berellini, Marius Olah, Kim Fejgin, and Scott Boyer).
11.1 Introduction.
11.2 The Rule of Five (Ro5) as ADME Filter.
11.3 Molecular Interaction Fields (MIFs): VolSurf.
11.4 MIF-based ADME Models.
11.5 Clinical Pharmacokinetics (PK) and Toxicological (Tox) Datasets.
11.6 VolSurf in Clinical PK Data Modeling.
11.7 ChemGPS-VolSurf (GPSVS) in Clinical PK Property Modeling.
11.8 ADME Filters: GPSVS vs. Ro5.
11.9 PENGUINS: Ultrafast ADME Filter.
11.10 Integrated ADME and Binding Affinity Predictions.
11.11 Conclusions.
12 GRID-Derived Molecular Interaction Fields for Predicting the Site of Metabolism in Human Cytochromes (Gabriele Cruciani, Yasmin Aristei, Riccardo Vianello, and Massimo Baroni).
12.1 Introduction.
11.2 The Human Cytochromes P450.
12.3 CYPs Characterization using GRID Molecular Interaction Fields.
12.4 Description of the Method.
12.5 An Overview of the Most Significant Results.
12.6 Conclusions.
12.7 Software Package.
Index.
CD-ROM Information.


Gabriele Cruciani received his PhD in Organic Chemistry in 1987 and after several positions in Italy and abroad has been appointed full professor at Perugia University in 2002 where he is regularly teaching courses in computational chemistry and chemoinformactics. Professor Cruciani has published more than 120 papers and in 2001 has received the Hansch award from the Molecular Modeling Society. During a stay with Peter Goodford in Oxford he became intimately familiar with the GRID force field developed there and has been endowed by Prof. Goodford with the task of further developing this highly successful software tool. In addition to his research and teaching duties at Perugia, Professor Cruciani is the scientific director of the London-based scientific software company 'Molecular Discovery' that distributes and develops numerous chemoinformatics software tools for pharmaceutical research.
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