In silico medicinal chemistry : computational methods to support drug design /
Covering computational tools in drug design using techniques from chemoinformatics, molecular modelling and computational chemistry, this book explores these methodologies and applications of in silico medicinal chemistry. The first part of the book covers molecular representation methods in computi...
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| Format: | eBook |
| Language: | English |
| Language Notes: | English. |
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[Cambridge] :
Royal Society of Chemistry,
[2015]
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| Series: | RSC theoretical and computational chemistry series ;
8. |
| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
Table of Contents:
- Cover; In Silico Medicinal Chemistry Computational Methods to Support Drug Design; Preface; Contents; Part 1 Introduction; Chapter 1
- Introduction; 1.1 Overview; Part 2 Molecular Representations; Chapter 2
- Chemistry and Graph Theory; 2.1 Overview; 2.2 Graph Theory and Chemistry; 2.3 Graph Theory in Chemistry; 2.4 Mathematical Chemistry and Chemical Graph Theory; 2.5 Summary; References; Chapter 3
- Structure Representation; 3.1 Overview; 3.2 The Need for Machine-Readable Structure Representations; 3.3 Adjacency Matrix; 3.4 Connection Table; 3.5 Line Notations.
- 3.5.1 WLN: Wiswesser Line Notation3.5.2 SMILES: Simplified Molecular-Input Line-Entry Specification; 3.5.3 InChI: IUPAC International Chemical Identifier; 3.6 Summary; References; Chapter 4
- Molecular Similarity; 4.1 Overview; 4.2 Molecular Similarity; 4.3 Similar Property Principle; 4.4 Molecular Descriptors; 4.5 Calculation of Molecular Similarity; 4.5.1 Similarity Coefficients; 4.6 Molecular Diversity; 4.7 Summary; References; Part 3 Molecular Descriptors; Chapter 5
- Molecular Property Descriptors; 5.1 Overview; 5.2 Molecular Weight (MW or MWt).
- 5.3 Octanol/Water Partition Coefficient (ClogP)5.4 Topological Polar Surface Area (TPSA); 5.5 Hydrogen Bond Acceptors and Donors (HBA and HBD); 5.6 Lipinski's Rule-of-Five; 5.7 Summary; References; Chapter 6
- Topological Descriptors; 6.1 Overview; 6.2 Topological Indices; 6.2.1 Wiener Index; 6.2.2 Randić Index; 6.2.3 Petitjean Index; 6.2.4 Zagreb Indices; 6.3 Molecular Fingerprints; 6.3.1 Structure-Key Fingerprints; 6.3.2 Hash-Key Fingerprints; 6.3.2.1 Fingal Fingerprints; 6.3.2.2 Morgan Fingerprints; 6.3.3 Ligand-Based Topological Pharmacophores; 6.3.3.1 CATS Vectors.
- 6.3.3.2 Hopfen Fingerprints6.4 Summary; References; Chapter 7
- Topographical Descriptors; 7.1 Overview; 7.2 Topographic Descriptors; 7.3 Pharmacophores; 7.4 ROCS: Rapid Overlay of Chemical Structures; 7.5 USR: Ultrafast Shape Recognition; 7.6 XED: Cresset Group; 7.7 Conformer Generation and the Conformer Problem; 7.8 Summary; References; Part 4 Statistical Learning; Chapter 8
- Statistical Learning; 8.1 Overview; 8.2 Statistical Learning; 8.3 Unsupervised Learning; 8.3.1 Overview; 8.3.2 Cluster Analysis; 8.3.3 k-Means Clustering; 8.3.4 Stirling Numbers of the Second Kind.
- 8.3.5 Self-Organising Maps8.3.6 Principal Component Analysis; 8.4 Supervised Learning; 8.4.1 Naïve Bayesian Classification; 8.4.2 Support Vector Machine; 8.4.3 Partial Least Squares; 8.5 Best Modelling Practice; 8.6 Summary; References; Part 5 Modelling Methodologies; Chapter 9
- Similarity Searching; 9.1 Overview; 9.2 Similar Property Principle; 9.3 Molecular Similarity and Virtual Screening; 9.4 Data Fusion; 9.5 Enrichment; 9.5.1 Lift Plots; 9.5.2 Confusion Matrix; 9.5.3 Receiver Operating Characteristic Curves; 9.5.4 Enrichment Factors; 9.6 Summary; References.
- Chapter 10
- Bioisosteres and Scaffolds.