An Introduction to Chemoinformatics

by Leach, Andrew R.; Gillet, Valerie J.

• ISBN13: 9781402013478
• ISBN10: 1402013477
• Format: Hardcover
• Copyright: 2003-07-01
• Publisher: Kluwer Academic Pub

Summary

Chemoinformatics draws upon techniques from many disciplines including computer science, mathematics, computational chemistry and data visualisation to tackle these problems. This, the first text written specifically for this field, aims to provide an introduction to the major techniques of chemoinformatics. The first part of the book deals with the representation of 2D and 3D molecular structures, the calculation of molecular descriptors and the construction of mathematical models. The second part describes other important topics including molecular similarity and diversity, the analysis of large data sets, virtual screening, and library design. Simple illustrative examples are used throughout to illustrate key concepts, supplemented with case studies from the literature. The book is aimed at graduate students, final-year undergraduates, and professional scientists. No prior knowledge is assumed other than a familiarity with chemistry and some basic mathematical concepts.

Table of Contents

PREFACE	xi
ACKNOWLEDGEMENTS	xv
CHAPTER 1. REPRESENTATION AND MANIPULATION OF 2D MOLECULAR STRUCTURES	1	(26)
1. Introduction	1	(1)
2. Computer Representations of Chemical Structures	1	(7)
2.1 Graph Theoretic Representations of Chemical Structures	2	(2)
2.2 Connection Tables and Linear Notations	4	(2)
2.3 Canonical Representations of Molecular Structures	6	(2)
3. Structure Searching	8	(1)
4. Substructure Searching	9	(10)
4.1 Screening Methods	11	(2)
4.2 Algorithms for Subgraph Isomorphism	13	(4)
4.3 Practical Aspects of Structure Searching	17	(2)
5. Reaction Databases	19	(2)
6. The Representation of Patents and Patent Databases	21	(3)
7. Relational Database Systems	24	(2)
8. Summary	26	(1)
CHAPTER 2. REPRESENTATION AND MANIPULATION OF 3D MOLECULAR STRUCTURES	27	(26)
1. Introduction	27	(1)
2. Experimental 3D databases	28	(3)
3. 3D Pharmacophores	31	(2)
4. Implementation of 3D database Searching	33	(1)
5. Theoretical 3D Databases	34	(6)
5.1 Structure-Generation Programs	34	(1)
5.2 Conformational Search and Analysis	35	(1)
5.3 Systematic Conformational Search	35	(3)
5.4 Random Conformational Search	38	(1)
5.5 Other Approaches to Conformational Search	39	(1)
5.6 The Generation of Distance Keys for Flexible Molecules	39	(1)
6. Methods to Derive 3D Pharmacophores	40	(11)
6.1 Pharmacophore Mapping using Constrained Systematic Search	41	(2)
6.2 Pharmacophore Mapping using Clique Detection	43	(2)
6.3 The Maximum Likelihood Method for Pharmacophore Mapping	45	(2)
6.4 Pharmacophore Mapping using a Genetic Algorithm	47	(2)
6.5 Practical Aspects of Pharmacophore Mapping	49	(2)
7. Applications of 3D Pharmacophore Mapping and 3D Database Searching	51	(1)
8. Summary	52	(1)
CHAPTER 3. MOLECULAR DESCRIPTORS	53	(18)
1. Introduction	53	(1)
2. Descriptors Calculated from the 2D Structure	54	(11)
2.1 Simple Counts	54	(1)
2.2 Physicochemical Properties	54	(3)
2.3 Molar Refractivity	57	(1)
2.4 Topological Indices	57	(2)
2.5 Kappa Shape Indices	59	(3)
2.6 Electrotopological State Indices	62	(1)
2.7 2D Fingerprints	63	(1)
2.8 Atom-Pairs and Topological Torsions	63	(1)
2.9 BCUT Descriptors	64	(1)
3. Descriptors Based on 3D Representations	65	(3)
3.1 3D Fragment Screens	65	(1)
3.2 Pharmacophore Keys	66	(1)
3.3 Other 3D Descriptors	67	(1)
4. Data Verification and Manipulation	68	(7)
4.1 Data Spread and Distribution	68	(1)
4.2 Scaling	69	(1)
4.3 Correlations	69	(2)
4.4 Reducing the Dimensionality of a Data Set: Principal Components Analysis	71	(4)
5. Summary	75
CHAPTER 4. COMPUTATIONAL MODELS	71	(32)
1. Introduction	77	(1)
2. Historical Overview	77	(2)
3. Deriving a QSAR Equation: Simple and Multiple Linear Regression	79	(6)
3.1 The Squared Correlation Coefficient, R2	81	(1)
3.2 Cross-Validation	82	(1)
3.3 Other Measures of a Regression Equation	83	(2)
4. Designing a QSAR "Experiment"	85	(6)
4.1 Selecting the Descriptors to Include	86	(1)
4.2 Experimental Design	86	(2)
4.3 Indicator Variables	88	(1)
4.4 Free-Wilson Analysis	89	(1)
4.5 Non-Linear Terms in QSAR Equations	89	(1)
4.6 Interpretation and Application of a QSAR Equation	90	(1)
5. Principal Components Regression	91	(1)
6. Partial Least Squares	92	(5)
7. Molecular Field Analysis and Partial Least Squares	97	(4)
8. Summary	101	(2)
CHAPTER 5. SIMILARITY METHODS	103	(20)
1. Introduction	103	(2)
2. Similarity Based on 2D Fingerprints	105	(1)
3. Similarity Coefficients	106	(4)
3.1 Properties of Similarity and Distance Coefficients	108	(2)
4. Other 2D Descriptor Methods	110	(2)
4.1 Maximum Common Subgraph Similarity	110	(1)
4.2 Reduced Graph Similarity	111	(1)
5. 3D Similarity	112	(10)
5.1 Alignment-Independent Methods	113	(2)
5.2 Alignment Methods	115	(1)
5.3 Field-Based Alignment Methods	115	(3)
5.4 Gnomonic Projection Methods	118	(1)
5.5 Finding the Optimal Alignment	119	(1)
5.6 Comparison and Evaluation of Similarity Methods	119	(3)
6. Summary	122	(1)
CHAPTER 6. SELECTING DIVERSE SETS OF COMPOUNDS	123	(24)
1. Introduction	123	(1)
2. Cluster Analysis	124	(9)
2.1 Hierarchical Clustering	126	(2)
2.2 Selecting the Appropriate Number of Clusters	128	(2)
2.3 Non-Hierarchical Clustering	130	(1)
2.4 Efficiency and Effectiveness of Clustering Methods	131	(2)
3. Dissimilarity-Based selection methods	133	(4)
3.1 Efficiency and Effectiveness of DBC S Methods	135	(2)
4. Cell-Based Methods	137	(5)
4.1 Partitioning Using Pharmacophore Keys	141	(1)
5. Optimisation Methods	142	(2)
6. Comparison and Evaluation of Selection Methods	144	(1)
7. Summary	145	(2)
CHAPTER 7. ANALYSIS OF HIGH-THROUGHPUT SCREENING DATA	147	(18)
1. Introduction	147	(3)
2. Data Visualisation	150	(3)
2.1 Non-Linear Mapping	151	(2)
3. Data Mining Methods	153	(10)
3.1 Substructural Analysis	154	(1)
3.2 Discriminant Analysis	155	(2)
3.3 Neural Networks	157	(3)
3.4 Decision Trees	160	(3)
4. Summary	163	(2)
CHAPTER 8. VIRTUAL SCREENING	165	(24)
1. Introduction	165	(2)
2. "Drug-Likeness" and Compound Filters	167	(3)
3. Structure-Based Virtual Screening	170	(11)
3.1 Protein-Ligand Docking	171	(3)
3.2 Scoring Functions for Protein-Ligand Docking	174	(5)
3.3 Practical Aspects of Structure-Based Virtual Screening	179	(2)
4. The Prediction of ADMET Properties	181	(7)
4.1 Hydrogen Bonding Descriptors	182	(1)
4.2 Polar Surface Area	183	(2)
4.3 Descriptors Based on 3D Fields	185	(1)
4.4 Toxicity Prediction	186	(2)
5. Summary	188	(1)
CHAPTER 9. COMBINATORIAL CHEMISTRY AND LIBRARY DESIGN	189	(20)
1. Introduction	189	(2)
2. Diverse and Focussed Libraries	191	(2)
3. Library Enumeration	193	(2)
4. Combinatorial Library Design Strategies	195	(2)
4.1 Monomer-Based Selection	195	(1)
4.2 Product-Based Selection	196	(1)
5. Approaches to Product-Based Library Design	197	(3)
6. Multiobjective Library Design	200	(3)
6.1 Multiobjective Library Design using a MOLA	201	(2)
7. Practical Examples of Library Design	203	(4)
7.1 Structure-Based Library Design	203	(1)
7.2 Library Design in Lead Optimisation	204	(3)
8. Summary	207	(2)
APPENDIX 1. MATRICES, EIGENVECTORS AND EIGENVALUES.	209	(4)
APPENDIX 2. CONFORMATION, ENERGY CALCULATIONS AND ENERGY SURFACES.	213	(6)
FURTHER READING	219	(6)
REFERENCES	225	(26)
INDEX	251