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The Resource A Primer on QSAR/QSPR Modeling : Fundamental Concepts

A Primer on QSAR/QSPR Modeling : Fundamental Concepts

Label
A Primer on QSAR/QSPR Modeling : Fundamental Concepts
Title
A Primer on QSAR/QSPR Modeling
Title remainder
Fundamental Concepts
Creator
Contributor
Subject
Language
eng
Summary
This brief goes back to basics and describes the Quantitative structure-activity/property relationships (QSARs/QSPRs) that represent predictive models derived from the application of statistical tools correlating biological activity (including therapeutic and toxic) and properties of chemicals (drugs/toxicants/environmental pollutants) with descriptors representative of molecular structure and/or properties. It explains how the sub-discipline of Cheminformatics is used for many applications such as risk assessment, toxicity prediction, property prediction and regulatory decisions apart from drug discovery and lead optimization. The authors also present, in basic terms, how QSARs and related chemometric tools are extensively involved in medicinal chemistry, environmental chemistry and agricultural chemistry for ranking of potential compounds and prioritizing experiments. At present, there is no standard or introductory publication available that introduces this important topic to students of chemistry and pharmacy. With this in mind, the authors have carefully compiled this brief in order to provide a thorough and painless introduction to the fundamental concepts of QSAR/QSPR modelling. The brief is aimed at novice readers
Member of
Cataloging source
MiAaPQ
Literary form
non fiction
Nature of contents
dictionaries
Series statement
SpringerBriefs in Molecular Science
A Primer on QSAR/QSPR Modeling : Fundamental Concepts
Label
A Primer on QSAR/QSPR Modeling : Fundamental Concepts
Link
http://libproxy.rpi.edu/login?url=https://ebookcentral.proquest.com/lib/rpi/detail.action?docID=2095477
Publication
Copyright
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Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
  • Foreword -- Preface -- Contents -- 1 QSAR/QSPR Modeling: Introduction -- Abstract -- 1.1 Introduction -- 1.2 What Is QSAR/QSPR Modeling? -- 1.2.1 Definition and Formalism -- 1.2.2 Objectives of QSAR: Key Features -- 1.2.3 Background -- 1.2.4 Importances of QSAR -- 1.2.5 QSAR and Regulatory Perspectives -- 1.2.6 Applications of QSAR -- 1.3 What Are Descriptors? -- 1.3.1 Definition -- 1.3.2 Types of Descriptors -- 1.3.2.1 2D-Descriptors -- Topological -- Structural Parameters -- Physicochemical Parameters -- Indicator Variables -- Thermodynamic Descriptors -- 1.3.2.2 3D-Descriptors -- Electronic Parameters -- Spatial Parameters -- Molecular Shape Analysis (MSA) Descriptors -- Molecular Field Analysis (MFA) Parameters -- Receptor Surface Analysis (RSA) Parameters -- 1.3.3 Software Tools and Online Platforms -- 1.4 Conclusion -- References -- 2 Statistical Methods in QSAR/QSPR -- Abstract -- 2.1 Introduction -- 2.2 Chemometric Tools -- 2.2.1 Various Chemometric Tools Used in QSAR/QSPR -- 2.2.2 Pretreatment of the Data Table -- 2.2.3 Feature Selection -- 2.2.4 Multiple Linear Regression -- 2.2.5 Partial Least Squares (PLS) -- 2.2.6 Linear Discriminant Analysis -- 2.2.7 Cluster Analysis -- 2.3 Quality Metrics -- 2.3.1 Importance of Metrics for Determination of Quality of QSAR Models -- 2.3.2 Types of Validation -- 2.3.2.1 The OECD Principles -- 2.3.2.2 Internal Validation -- 2.3.2.3 External Validation -- Selection of Training and Test Sets -- Applicability Domain (AD) -- 2.3.3 Validation Metrics for Regression-Based QSAR Models -- 2.3.3.1 Metrics for Internal Validation -- 2.3.3.2 Metrics for External Validation -- 2.3.4 Validation Metrics Employed in Classification-Based QSAR -- 2.3.4.1 Parameters for Goodness-of-Fit and Quality Determination -- 2.3.4.2 Metrics for Model Performance Parameters
  • 2.3.5 Parameters for Receiver Operating Characteristics (ROC) Analysis -- 2.3.5.1 Metrics for Pharmacological Distribution Diagram (PDD) -- 2.4 Conclusion -- References -- 3 QSAR/QSPR Methods -- Abstract -- 3.1 Introduction -- 3.2 De Novo Models -- 3.2.1 Free--Wilson Model -- 3.2.2 Fujita--Ban Model -- 3.3 Property-Based QSAR -- 3.3.1 LFER Approach of Hansch -- 3.3.2 The Mixed Approach -- 3.4 Graph Theoretical Approach -- 3.4.1 Introduction to Graph Theory -- 3.4.2 Matrix and Chemical Graphs -- 3.4.3 Topological Descriptors -- 3.4.4 Applications -- 3.5 Three-Dimensional QSAR -- 3.5.1 In Silico Representation of Molecular Structure -- 3.5.2 Computational Chemistry for Property Simulation -- 3.5.2.1 Conformational Analysis -- 3.5.2.2 Energy Minimization -- 3.5.2.3 Molecular Mechanics -- 3.5.2.4 Molecular Dynamics -- 3.5.2.5 Quantum Mechanics -- The Basic Formalism -- The Born--Oppenheimer Approximation -- The Hartree--Fock Approximation -- Density Function Theory (DFT) -- Semi-empirical Analysis -- 3.5.3 Examples of 3D-QSAR -- 3.5.3.1 CoMFA -- Perception of CoMFA -- Formalism of CoMFA -- Factors Responsible for the Performance of CoMFA -- Display and Interpretation of Results -- Advantages and Drawbacks of CoMFA -- 3.5.3.2 CoMSIA -- Idea of CoMSIA -- Methodology of CoMSIA -- Advantages of CoMSIA -- 3.5.3.3 MSA -- Concept of the MSA -- Methodology of the MSA -- MSA Descriptors -- 3.5.3.4 RSA -- Concept of the RSA -- Methodology of the RSA -- RSA Descriptors -- Miscellaneous -- 3.6 Conclusion -- References -- 4 Newer Directions in QSAR/QSPR -- Abstract -- 4.1 Introduction -- 4.2 Newer Methods -- 4.2.1 HQSAR -- 4.2.1.1 Perception of HQSAR -- 4.2.1.2 Methodology -- 4.2.1.3 HQSAR Parameters -- 4.2.1.4 Application of HQSAR Models -- 4.2.1.5 Advantages of HQSAR -- 4.2.2 G-QSAR -- 4.2.2.1 Idea Behind Group-based QSAR (G-QSAR) -- 4.2.2.2 G-QSAR Methodology
  • 4.2.2.3 Advantage of G-QSAR -- 4.2.2.4 Application of G-QSAR Model -- 4.2.3 MIA-QSAR -- 4.2.3.1 Concept of MIA-QSAR -- 4.2.3.2 Methodology of MIA-QSAR -- 4.2.3.3 Advantages of MIA-QSAR -- 4.2.3.4 Drawbacks of MIA-QSAR -- 4.2.3.5 Application of MIA-QSAR -- 4.2.4 Binary QSAR -- 4.2.4.1 Concept of Binary QSAR -- 4.2.4.2 Methodology of Binary QSAR -- 4.2.4.3 Advantage of Binary QSAR -- 4.2.4.4 Drawbacks of Binary QSAR -- 4.2.5 Miscellaneous Methods -- 4.3 Future Scope -- 4.3.1 What to Expect in the Coming Days -- 4.3.2 Newer Application Areas of QSAR/QSPR -- 4.3.2.1 QSAR of Nanoparticles -- 4.3.2.2 QSAR of Mixture Toxicity -- 4.3.2.3 QSAR of Peptides -- 4.3.2.4 QSAR of Cosmetics -- 4.3.2.5 QSAR of Ionic Liquids -- 4.3.2.6 Material Informatics -- 4.3.2.7 Interspecies Toxicity Modeling -- 4.3.2.8 QSAR of Phytochemicals -- 4.4 Conclusion -- References
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{'f': 'http://opac.lib.rpi.edu/record=b4383180'}
Extent
1 online resource (129 pages)
Form of item
online
Isbn
9783319172811
Media category
computer
Media MARC source
rdamedia
Media type code
c
Sound
unknown sound
Specific material designation
remote

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