Molecular interaction fields : applications in drug discovery and ADME prediction
著者
書誌事項
Molecular interaction fields : applications in drug discovery and ADME prediction
（Methods and principles in medicinal chemistry / edited by R. Mannhold ... [et al.], v. 27）
Wiley-VCH, c2006
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注記
Includes bibliographies and index
内容説明・目次
内容説明
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.
目次
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.
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