ADVANCING QUANTITATIVE STRUCTURE ACTIVITY RELATIONSHIP STRATEGIES IN LIGAND-BASED COMPUTER-AIDED DRUG DESIGN By Mariusz Butkiewicz Dissertation Submitted to the Faculty of the Graduate School of Vanderbilt University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY In Chemistry August, 2014 Nashville, Tennessee Approved: Jens Meiler, Ph.D. Brian O. Bachmann, Ph.D. David W. Wright, Ph.D. Clare M. McCabe, Ph.D. Copyright © 2014 by Mariusz Butkiewicz All Rights Reserved ii DEDICATION To my parents, my sister, and Nicole. iii ACKNOWLEDGEMENTS Over the past years, I have received support and encouragement from a great number of individuals to whom I am very grateful. I would like to express my deepest and sincere gratitude to my advisor, Dr. Jens Meiler. Coming to Nashville and joining the Meiler laboratory to start my graduate studies has been a tremendous opportunity and extraordinary experience in my life. Jens was an excellent mentor and supported me on each step in my graduate career. His guidance taught me how to approach scientific problems, how to ask-the right scientific questions, and how to write and present scientific work. Jens found the right balance between encouraging my own scientific explorations and providing invaluable guidance and help. I would like to thank Dr. Meiler for making the past several years such a pleasant academic experience. The members of my dissertation committee, Dr. David Wright, Dr. Brian Bachmann, and Dr. Clare McCabe, were a great source of support and guidance for my graduate work. Their insightful comments and constructive criticism gave appreciated impulses to my research. Many friends and colleagues in the Meiler lab provided great help and support during the past years. Particularly, I would like to thank Will Lowe, Jeff Mendenhall, Nils Woetzel, Ralf Mueller, and Kristian Kaufmann for great discussions, ideas, and inspiration. I would like to express my deepest gratitude to my family, my parents, and my sister, Sylvia. Their constant love and support made this incredible experience possible, despite the large geographical distance. Finally, I want to thank my better half, Nicole Restrepo. Her unconditional love and support provided balance in my life and made this dissertation possible. She made sure that I took care of myself during my years in graduate school. iv TABLE OF CONTENTS Page DEDICATION ............................................................................................................................................. iii ACKNOWLEDGEMENTS ......................................................................................................................... iv TABLE OF CONTENTS .............................................................................................................................. v LIST OF TABLES ..................................................................................................................................... viii LIST OF FIGURES ................................................................................................................................... viii LIST OF ABBREVIATIONS ....................................................................................................................... x SUMMARY ................................................................................................................................................ xii Chapter 1. INTRODUCTION ................................................................................................................................ 1 Distinct CADD strategies cope with availability of protein structure information ................................... 1 Quantitative Structure Activity Relationships correlate chemical structure to biological activity ........... 3 Molecular descriptors encode chemical structure in QSAR modeling ..................................................... 3 Machine learning approaches model QSARs between chemical structure and biological activity .......... 4 Improvements to prediction accuracy of QSAR models ........................................................................... 5 High-throughput screening sets knowledge base for virtual screening in drug discovery ........................ 6 Curating and identifying publicly and commercially available biological assay data sets ....................... 6 Virtual high-throughput screening expands chemical search space in comparison to traditional HTS .... 7 Allosteric potentiators of mGlu5 provide a novel approach for treatment of schizophrenia ..................... 7 Novel inhibitors for Plasmodium falciparum have potential to diminish Malaria drug resistance ........... 8 Predicting molecular properties through Quantitative Structure Property Relationships ......................... 9 Concepts of CADD are implemented in Bio Chemistry Library ............................................................ 10 v 2. LIGAND-BASED VIRTUAL HIGH-THROUGHPUT SCREENING BENCHMARK AND METHOD DEVELOPMENT ..................................................................................................................... 11 Introduction ............................................................................................................................................. 11 Results and Discussion............................................................................................................................ 15 Experimental ........................................................................................................................................... 22 Conclusions ............................................................................................................................................. 34 3. IDENTIFICATION OF PATHWAY SPECIFIC INHIBITORS FOR β-HEMATIN CRYSTALLIZATION IN PLASMODIUM FALCIPARUM INVOLVED IN MALARIA ...................... 36 Introduction ............................................................................................................................................. 36 Results ..................................................................................................................................................... 38 Methods ................................................................................................................................................... 44 Discussion ............................................................................................................................................... 47 4. NOVEL ALLOSTERIC MODULATORS FOR MGLU5 RELATED TO CPPHA BINDING ......... 50 Introduction ............................................................................................................................................. 50 Results ..................................................................................................................................................... 54 Methods ................................................................................................................................................... 61 Discussion ............................................................................................................................................... 65 Conclusions ............................................................................................................................................. 67 5. SMALL MOLECULE PROPERTY PREDICTIONS ........................................................................ 69 Comparative Analysis of Machine Learning Techniques for the Prediction of LogP ............................ 69 Quantitative Structure Property Modeling for the Prediction of DMPK Parameters Intrinsic Clearance and Plasma Protein Binding .................................................................................................................... 80 6. DISCUSSION ..................................................................................................................................... 90 vi Conclusions and future directions ........................................................................................................... 90 Methods development and benchmarking of Quantitative Structure Activity Relationships ................. 90 Discovery of pathway specific antimalarial hit compounds to diminish P. falciparum ......................... 92 Selective allosteric modulators for distinct mGlu5 site related to CPPHA binding................................. 93 Molecular property predictions ............................................................................................................... 94 Future perspectives of LB-CADD .......................................................................................................... 94 APPENDIX ............................................................................................................................................... 100 General Comments ................................................................................................................................ 100 Supporting information for Chapter 2 ................................................................................................... 100 Supporting information for Chapter 3 ................................................................................................... 113 Supporting information for Chapter 4 ................................................................................................... 115 Supporting