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Deciphering Molecular Mechanisms of Adverse Reactions of Drugs

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Deciphering Molecular Mechanisms of Adverse Reactions of Drugs UNIVERSITY OF CALIFORNIA, SAN DIEGO Deciphering Molecular Mechanisms of Adverse Reactions of Drugs A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Bioinformatics and Systems Biology by Yu-Chen Chen Committee in charge: Professor Ruben Abagyan, Chair Professor Grace M. Kuo, Co-Chair Professor Nuno F. Bandeira Professor Sanjoy Dasgupta Professor Lucila Ohno-Machado 2014 Copyright Yu-Chen Chen, 2014 All rights reserved. Signature Page The Dissertation of Yu-Chen Chen is approved, and it is acceptable in quality and form for publication on microfilm and electronically: _____________________________________________________________________ _____________________________________________________________________ _____________________________________________________________________ _____________________________________________________________________ Co-Chair _____________________________________________________________________ Chair University of California, San Diego 2014 iii TABLE OF CONTENTS Table of Contents Signature Page ............................................................................................................... iii Table of Contents .......................................................................................................... iv List of Figures ................................................................................................................ ix List of Tables ................................................................................................................ xii Acknowledgements ...................................................................................................... xv Vita ............................................................................................................................ xviii Abstract of the Dissertation ........................................................................................ xxii Chapter 1 Docking to Multiple Pockets or Ligand Fields for Screening, Activity Prediction and Scaffold Hopping ................................................................................... 1 1.1 Introduction .................................................................................................. 2 1.2 Scaffold hopping benchmark preparation .................................................... 4 1.3 Protein Target Selection ............................................................................... 6 1.4 3D Atomic Property Field Models, docking and scoring ............................. 7 1.5 Internal Coordinates Mechanics Grid Docking ............................................ 8 1.6 Evaluating the Prediction Performance by Normalized Square Root ROC AUC .................................................................................................................. 10 1.7 Generation of high quality superimposed protein pockets ......................... 11 1.8 Analysis of the benchmark ......................................................................... 12 iv 1.9 Prediction of ligand binding geometry by APF self-docking ..................... 13 1.10 Comparison of molecular recognition between APF and molecular docking ............................................................................................................. 14 1.11 Conclusion ................................................................................................ 17 1.12 Acknowledgements .................................................................................. 17 Chapter 2 Compound activity prediction using models of binding pockets or ligand properties in 3D ............................................................................................................ 28 2.1 Introduction ................................................................................................ 29 2.2 The Pocketome encyclopedia ..................................................................... 31 2.3 Computational models of compound activity ............................................. 33 2.4 Compound sets for model benchmarking ................................................... 34 2.5 Pocket-based models .................................................................................. 38 2.6 Models based on 3D ligand property fields ................................................ 41 2.7 Advantages and limitations of the pocket-based and ligand-based approaches ........................................................................................................ 44 2.8 Hybrid models ............................................................................................ 45 2.9 Acknowledgements .................................................................................... 46 Chapter 3 Docking, screening and selectivity prediction for small molecule nuclear receptor modulators ...................................................................................................... 55 3.1 Introduction ................................................................................................ 55 v 3.2 Chemicals Targeting Nuclear Receptors .................................................... 58 3.2.1 Chemical Specificity: From Highly Specific to Highly Promiscuous ......................................................................................... 58 3.2.2 Agonists, Antagonists, SNuRMs ................................................. 60 3.2.3 Analysis of Cross-Reactivity ....................................................... 61 3.3 Nuclear Receptor Ligand Binding Domains .............................................. 63 3.3.1 Structural coverage ...................................................................... 63 3.3.2 Structural Basis of Agonism and Antagonism ............................ 64 3.4 Computational Prediction of Nuclear Receptor Modulators ...................... 66 3.4.1 Improving the Docking and Scoring Accuracy to Ligand Binding Domains ................................................................................................ 66 3.4.2 Docking to Pockets Obtained from Multiple Co-crystal Structures .............................................................................................................. 67 3.4.3 Docking and Screening Against a Single Crystal Structure ........ 71 3.4.4 Ligand-derived Atom Property Fields from Co-Crystal structures as Activity Predictors ........................................................................... 73 3.4.5 Prediction of Ligand Selectivity and Polypharmacology ............ 76 3.5 Acknowledgements .................................................................................... 79 Chapter 4 Millions of Preventable Deaths: Early Alerts about Serious Side Effects ... 88 4.1 Introduction ................................................................................................ 89 vi 4.2 Data processing .......................................................................................... 90 4.3 Estimating risk signal for adverse drug reactions ....................................... 91 4.4 Early, relevant, and stronger made signal for adverse drug reactions ........ 95 4.5 Widely used crazy pills for anti-malaria over 20 years could be stopped early .................................................................................................................. 98 4.6 A dark mythology in the estrogen-containing contraception ..................... 99 4.7 Balance between benefits and risks with statin use .................................. 101 4.8 Walking near dead with popular sleeping pills, zolpidem ....................... 103 4.9 Acknowledgements .................................................................................. 105 Chapter 5 Large-scale Drug Polypharmacological Target Profiling - Deciphering Drug Associated Adverse Reactions ................................................................................... 116 5.1 Introduction .............................................................................................. 117 5.2 Chemical models based on 2D fingerprint ............................................... 119 5.3 Atomic Property Field Models based on 3D crystallographic ligands ..... 120 5.4 APF score normalization for cross-model comparison ............................ 122 5.5 Optimized APF model with distance-dependent clusters and sub-cluster selection .......................................................................................................... 122 5.6 Drug polypharmacological target profiling .............................................. 124 5.7 Fibroblast growth factor receptor 2 as a potential therapeutic target of raloxifene for treating osteoporosis ................................................................ 126 vii 5.8 Raloxifene-induced ischemic stroke and blood clotting caused by anti- target activity from thrombin .......................................................................... 128 5.9 Conclusion ................................................................................................ 129 5.10 Acknowledgements ................................................................................ 130 References .................................................................................................................. 172 viii LIST OF FIGURES List of Figures Figure 1.1 The flowchart of APF cloud generation. .................................................... 22 Figure 1.2 The outline of the structural
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