Chemoinformatics approaches to virtual screening / / edited by Alexandre Varnek, Alex Tropsha

• Record Nr.: UNINA9911006771603321
• Pubbl/distr/stampa: Cambridge, : RSC Pub., 2008
• ISBN: 1-61583-352-8; 1-84755-887-9
• Edizione: [1st ed.]
• Descrizione fisica: 1 online resource (xvi, 338 pages) : illustrations (some color)
• Altri autori (Persone): VarnekAlexandre; TropshaAlex
• Disciplina: 542.8
• Soggetti: Cheminformatics; Chemistry - Data processing
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: 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.
• Sommario/riassunto: Focuses on chemoinformatics approaches applicable to virtual screening of very large available collections of chemical compounds to identify novel biologically active molecules.