Doucet / Panaye Three Dimensional QSAR

Applications in Pharmacology and Toxicology
1. Auflage 2010
ISBN: 978-1-4200-9116-8
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 575 Seiten

Reihe: QSAR in Environmental and Health Sciences

As a result of new statistical and mathematical approaches, improved visualization tools, and recognition by international regulatory groups, quantitative structure-activity relationships (QSARs) now play important roles in pharmacology for the design of new drugs as well as in toxicology and ecotoxicology for hazard identification and risk assessment. Providing up-to-date coverage of the field, Three Dimensional QSAR: Applications in Pharmacology and Toxicology presents the most recent QSAR methods and illustrates their scope, advantages, and limitations.
Part I
The first part of the book addresses CoMFA and related methods, such as CoMSIA, FLUFF, SOMFA. It also describes shape-, surface-, and volume-based approaches, including MSA, excluded volume, LIV, HASL, receptor surface model, COMPASS, and CoMSA.
Part II
Focusing on methods that use 3D information, the second part covers autocorrelation methods, such as GRIND; similarity-based methods, including similarity matrices and quantum similarity indices; and quantitative spectroscopic data–activity relationships. Some applications in data mining are also explored.
Part III
The third part deals with post-3D models. The authors discuss the adaptation of the receptor and simultaneous presence of several conformers or solvation mechanisms.
Part IV
The final part presents receptor-related approaches as well as docking and free energy calculations, which are treated at various levels. This part concerns the extensive sampling of phase space and approximate methods, such as linear interaction energy, Poisson–Boltzmann, and generalized Born models. A case study covering several parallel approaches is also developed.

An appendix offers the basic principles of modeling and statistical tools routinely required in QSAR methodologies, including optimization methods, molecular mechanics and dynamics, multivariate analysis, nonlinear models, and evolutionary techniques. It provides newcomers with the concepts necessary to fully grasp the essentials of these methods and gives a basic grounding in their correct use.

Illustrated with numerous examples and a color insert, this book supplies a clear overview of the strengths and weaknesses of 3D-QSAR approaches. It explains how these modern techniques can link the biological activity of chemicals to their structure, encompassing both their 2D structural formulae and 3D geometry.

Zielgruppe

Pharmaceutical and agrochemical researchers; researchers and graduate students in chemoinformatics, pharmacology, toxicology, and chemistry.

Autoren/Hrsg.

Doucet, Jean Pierre

Panaye, Annick

Fachgebiete

• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Biomedizin, Medizinische Forschung, Klinische Studien
• Naturwissenschaften Biowissenschaften Toxikologie

Inhaltsverzeichnis

ACTUAL 3D MODELS
Comparative Molecular Field Analysis
CoMFA: Basic Steps and Caveats
Improvements of CoMFA
Refining Alignment
Parallel Developments Meet CoMFA
Competitive Binding
Concluding Remarks
CoMFA-Type Grid Methods: CoMSIA, SOMFA, FLUFF, and SAMFA
Comparative Molecular Similarity Analysis
Self-Organizing Molecular Field Analysis
FLUFF-BALL
Simple Atom Mapping Following Alignment
Shape-, Surface-, and Volume-Based QSAR Models
Molecular Shape Analysis
Further Developments
Volume-Based Models
Hypothetical Active Site Lattice
Receptor Surface Model
COMPASS Approach
Comparative Molecular Surface Analysis
QSAR Models from Pharmacophore-Oriented Approaches
AROUND THE 3D APPROACHES
Autocorrelation and Derived Methods
Autocorrelation- and Cross-Correlation-Based Methods
SESP and DiP Models
GRID Independent Descriptor Approach
Mapping Property Distribution
Similarity-Based 3D-QSAR Models
Similarity Matrices
Seal-Based Similarity Matrices
Molecular Quantum Similarity Measures
Fragment Quantum Self-Similarity Measures
Other Similarity-Based Methods: CoMASA, k-NN, or CPANNs
Spectroscopic QSARs: Quantitative Spectroscopic Data Activity Relationships
IR Eigenvalues
Using NMR Shifts
Electronic Eigenvalues
2.5D Descriptors and Related Approaches
Usual Structural Descriptors
From Topological to Topographical Indices
3D Fragments
Encoding Quantum-Chemical 3D Information
Encoding from Atom Positions
Encoding Interaction Energy
Matrix Treatments
2D vs. 3D Models
QSARs in Data Mining
CoMFA, CoMSIA in Database Screening
Autocorrelation Descriptors in Data Mining
Virtual Screening with COMBINE
Other Approaches
BEYOND 3D
4D-QSARs
4D-QSAR: Occupancy Analysis
Universal 4D Fingerprints
Extension of CoMSA to 4D-QSAR Schemes
4D-QSAR from a Simplex Representation
Dynamic 3D-QSAR: COREPA
Induced-Fit in 5D- and 6D-QSAR Models
Receptor Adaptation: The "Induced-Fit"
Quasar Approach (Quasi Atomistic Receptor Model)
Raptor Approach
The VirtualToxLab: Quasar and Raptor Studies of Endocrine Disruptors
RECEPTOR-RELATED MODELS
Docking and Interaction Energy Calculation
Docking and Internal Scoring Functions
Some Docking Programs
Nonspecific Scoring Functions
Docking: A Preprocessing Step for CoMFA-Type QSAR Models
Interaction Energy Calculation and Receptor-Dependent Models
Free Energy Calculation: Extensive Sampling and Simplified Models
Extensive Sampling
Approximation and Linear Interaction Energy Model
Continuum-Solvent Models: Poisson–Boltzmann and Generalized Born Surface Area Methods
A Case Study: 2-Amino-6-Arylsulfonylbenzonitrile Analogues, Inhibitors of HIV-1RT
Concluding Remarks
Appendix A: The Tool Kit
Appendix B: The Steroid Benchmark
References
Index

Über Autor(innen)

Jean Pierre Doucet and Annick Panaye are both professors at Université Denis-Diderot, Paris, France. They have chaired several conferences and published numerous papers.