Chemoinformatics approaches to virtual screening
| Other Authors: | |
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| Format: | Book |
| Language: | English |
| Published: |
Cambridge,
Royal Society of Chemistry,
2008.
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| Subjects: | |
| Online Access: | http://dx.doi.org/10.1039/9781847558879 |
Table of Contents:
- Preface
- 1 - Fragment Descriptors in SAR/QSAR/QSPR studies, molecular similarity analysis and in virtual screening
- Introduction
- Historical survey
- Main characteristics of Fragment Descriptors
- Types of Fragments
- Simple Fixed Types
- WLN and SMILES Fragments
- Atom-Centered Fragments
- Bond-Centered Fragments
- Maximum Common Substructures
- Atom Pairs and Topological Multiplets
- Substituents and Molecular Frameworks
- Basic Subgraphs
- Mined Subgraphs
- Random Subgraphs
- Library Subgraphs
- Fragments describing supramolecular systems and chemical reactions
- Storage of fragments' information
- Fragment's Connectivity
- Generic Graphs
- Labeling Atoms
- Application in Virtual Screening and In Silico Design
- Filtering
- Similarity Search
- SAR Classification (Probabilistic) Models
- QSAR/QSPR Regression Models
- In Silico Design
- Limitations of Fragment Descriptors
- Conclusion
- 2 - Topological Pharmacophores
- Introduction
- 3D pharmacophore models and descriptors
- Topological pharmacophores
- Topological pharmacophores from 2D-aligments
- Topological pharmacophores from 2D pharmacophore fingerprints
- Topological index-based 'pharmacophores'?
- Topological pharmacophores from 2D-aligments
- Topological pharmacophores from pharmacophore fingerprints
- Topological pharmacophore pair fingerprints
- Topological pharmacophore triplets
- Similarity searching with pharmacophore fingerprints - Technical Issues
- Similarity searching with pharmacophore fingerprints - Some Examples
- Machine-learning of Topological Pharmacophores from Fingerprints
- Topological index-based 'pharmacophores'?
- Conclusions
- 3 - Pharmacophore-based Virtual Screening in Drug Discovery
- Introduction
- Virtual Screening Methods
- Chemical Feature-based Pharmacophores
- The Term "3D Pharmacophore"
- Feature Definitions and Pharmacophore Representation
- Hydrogen bonding interactions
- Lipophilic areas
- Aromatic interactions
- Charge-transfer interactions
- Customization and definition of new features
- Current super-positioning techniques for aligning 3D pharmacophores and molecules
- Generation and Use of Pharmacophore Models
- Ligand-based Pharmacophore Modeling
- Structure-based Pharmacophore Modeling
- Inclusion of Shape Information
- Qualitative vs. Quantitative Pharmacophore Models
- Validation of Models for Virtual Screening
- Application of Pharmacophore Models in Virtual Screening
- Pharmacophore Models as Part of a Multi-Step Screening Approach
- Antitarget and ADME(T) Screening Using Pharmacophores
- Pharmacophore Models for Activity Profiling and Parallel Virtual Screening
- Pharmacophore Method Extensions and Comparisons to Other Virtual Screening Methods
- Topological Fingerprints
- Shape-based Virtual Screening
- Docking Methods
- Pharmacophore Constraints Used in Docking
- Further Reading
- Summary and Conclusion
- 4 - Molecular Similarity Analysis in Virtual Screening
- Ligand-Based Virtual Screening
- Foundations of Molecular Similarity Analysis
- Molecular Similarity and Chemical Spaces
- Similarity Measures
- Activity Landscapes
- Analyzing the Nature of Structure-Activity Relationships
- Relationships between different SARs
- SARs and target-ligand interactions
- Qualitative SAR characterization
- Quantitative SAR characterization
- Implications for molecular similarity analysis and virtual screening
- Strengths and Limitations of Similarity Methods
- Conclusion and Future Perspectives
- 5 - Molecular Field Topology Analysis in drug design and virtual screening
- Introduction: local molecular parameters in QSAR, drug design and virtual screening
- Supergraph-based QSAR models
- Rationale and history
- Molecular Field Topology Analysis (MFTA)
- General principles
- Local molecular descriptors: facets of ligand-biotarget interaction
- Construction of molecular supergraph
- Formation of descriptor matrix
- Statistical analysis
- Applicability control
- From MFTA model to drug design and virtual screening
- MFTA models in biotarget and drug action analysis
- MFTA models in virtual screening
- MFTA-based virtual screening of compound databases
- MFTA-based virtual screening of generated structure libraries
- Conclusion
- 6 - Probabilistic approaches in activity prediction
- Introduction
- Biological Activity
- Dose-Effect Relationships
- Experimental Data
- Probabilistic Ligand-Based Virtual Screening Methods
- Preparation of Training Sets
- Creation of Evaluation Sets
- Mathematical Approaches
- Evaluation of Prediction Accuracy
- Single-Targeted vs. Multi-Targeted Virtual Screening
- PASS Approach
- Biological Activities Predicted by PASS
- Chemical Structure Description in PASS
- SAR Base
- Algorithm of Activity Spectrum Estimation
- Interpretation of Prediction Results
- Selection of the Most Prospective Compounds
- Conclusions
- 7 - Fragment-based de novo design of druglike molecules
- Introduction
- From Molecules to Fragments
- From Fragments to Molecules
- Scoring the Design
- Conclusions and Outlook
- 8 - Early ADME/T predictions: a toy or a tool?
- Introduction
- Which properties are important for early drug discovery?
- Physico-chemical profiling
- Lipophilicity
- Solubility
- Data availability and accuracy
- Models
- Why models don't work: the challenge of the Applicability Domain
- AD based on similarity in the descriptor space
- AD based on similarity in the property-based space
- How reliable are predictions of physico-chemical properties?
- Available Data for ADME/T biological properties
- Absorption
- Data
- Models
- Distribution
- Data
- Models
- The usefulness of ADME/T models is limited by available data
- Conclusions
- 9 - Compound Library Design - Principles and Applications
- Introduction to Compound Library Design
- Methods for Compound Library Design
- Design for Specific Biological Activities
- Similarity Guided Design of Targeted Libraries
- Diversity Based Design of General Screening Libraries
- Pharmacophore Guided Design of Focused Compound Libraries
- QSAR Based Targeted Library Design
- Protein Structure Based Methods for Compound Library Design
- Design for Developability or Drug-likeness
- Rule & Alert Based Approaches
- QSAR Based ADMET Models
- Undesirable Functionality Filters
- Design for Multiple Objectives and Targets Simultaneously
- Concluding Remarks
- 10 - Integrated Chemo- and Bioinformatics Approaches to Virtual Screening
- Introduction
- Availability of large compound collections for virtual screening
- NIH Molecular Libraries Roadmap Initiative and the PubChem database
- Other chemical databases in public domain
- Structure based virtual screening
- Major methodologies
- Challenges and limitations of current approaches
- The implementation of cheminformatics concepts in structure based virtual screening
- Predictive QSAR models as virtual screening tools
- Critical Importance of model validation
- Applicability domains and QSAR model acceptability criteria
- Predictive QSAR modeling workflow
- Examples of application
- Structure based chemical descriptors of protein ligand interface: the EnTESS method
- Derivation of the EnTESS descriptors
- Validation of the EnTESS descriptors for binding affinity prediction
- Structure based cheminformatics approach to virtual screening: the CoLiBRI method
- The representation of three-dimensional active sites in multidimensional chemistry space
- The mapping between chemistry spaces of active sites and ligands
- Summary and Conclusions.