ABSTRACT VAN DEN DRIESSCHE, GEORGE A. Cheminformatics
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ABSTRACT VAN DEN DRIESSCHE, GEORGE A. Cheminformatics Approaches to Model HLA-Mediated Adverse Drug Reactions, Challenging Protein-Ligand Complexes, and Large Series of Chemical Dyes. (Under the Direction of Dr. Denis Fourches). Cheminformatics applies a combination of mathematics, informatics, machine learning, and other computational technologies to solving chemical problems. Ultimately, the goal of cheminformatics is to provide insight and guidance for experimental design that improves the desired properties of a molecule (such as drug binding potency) and eliminates undesired properties (such as toxicity). However, the development of accurate and reliable cheminformatic models is extremely difficult when there is limited experimental data for model development, as is the case with predicting adverse drug reactions (ADR). An ADR occurs anytime a patient, who is administered a drug, suffers a severe and harmful reaction to that drug; these events occur through a variety of pathways and are usually not observed until wide-spread population use. One type of ADR, known as idiosyncratic ADRs, occurs through immune-cell activation by binding with the human leukocyte antigen (HLA) protein. Though the occurrence of HLA-mediated ADRs are well documented, the specific drug binding relationship with HLA is not well understood and, to date, there is only one example of a fully solved HLA-drug binding mode: HLA-B*57:01 with the small molecule drug abacavir. Herein, using three X-ray crystal structures of HLA-B*57:01 in complex with abacavir and three unique co-binding peptides, we have analyzed, for the first time, the exact molecular interactions formed by the drug with HLA variant and co-binding peptide. Our goal is to develop a virtual screening platform based on molecular docking. We began by testing molecular docking’s capabilities for modeling complex tripartite HLA-drug-peptide systems by exploring native versus predicted interactions between HLA- B*57:01, abacavir, and co-binding peptide. Using the Schrödinger Suite’s Glide docking software, we docked abacavir with three X-ray crystal structures and co-binding peptides (PDB: 3VRI, 3VRJ, 3UPR); these docking results revealed that the co-binding peptide provides ~2 kcal/mol of stabilization for bound abacavir. Using these new insights, we began developing a three-tiered peptide dependent virtual screening protocol for predicting a drug’s likelihood of binding to the HLA-B*57:01 variant (carried by 7% of Caucasians and 3% of African-Americans). This screening protocol was used to screen the whole DrugBank database, which at the time of this study contained over 7,000 withdrawn, approved, illicit, and experimental drugs. Virtual screening of DrugBank resulted in the identification of 22 potential HLA-B*57:01 binders that were predicted as active for all three peptides. Recently, Metushi et al. had attempted to screen the ZINC database of drug-like molecules and predicted seven compounds as HLA-B*57:01 liable, but were experimentally determined to be non-binders except for acyclovir. Therefore, we applied our model to these same seven compounds and explored the time-dependent relationship of abacavir and acyclovir with peptide P3 (PDB: 3UPR) using molecular dynamic simulations. Next, a panoramic virtual screening platform was developed for HLA, pan-HLA. Six evolutionary diverse HLA variants were selected through a phylogeny analysis of Protein Databank deposited HLA crystal structures. Drugbank was then docked against five pan-HLA variants and 72 drugs were predicted active. Another unique opportunity for cheminformatics is the characterization, exploration and analysis of large libraries of molecules. We have assisted in the development of the hair dye substance database (HDSD). As the HDSD contains over 300 synthetic organic dyes, we clustered this library to discriminate precursors from temporary and permanent hair dyes. Indeed, hierarchical clustering identified C.I. Basic Orange 1 and 2 as dyes with high chemical similarity to precursors. These dyes were then used to perform a 2D-similarity search of the NC State Wilson College of Textiles Max Waver Dye Library (MWDL). The MWDL was donated to NC State by Eastman Chemical and contains over 98,000 organic-dyes. Ultimately, four MWDL dyes were identified as promising hair dye candidates. © Copyright 2019 by George A. Van Den Driessche All Rights Reserved Cheminformatics Approaches to Model HLA-Mediated Adverse Drug Reactions, Challenging Protein-Ligand Complexes, and Large Series of Chemical Dyes by George A. Van Den Driessche A dissertation submitted to the Graduate Faculty of North Carolina State University in partial fulfillment of the requirements for the degree of Doctor of Philosophy Chemistry Raleigh, North Carolina 2019 APPROVED BY: _______________________________ _______________________________ Denis Fourches Gavin Williams Chair of Advisory Committee _______________________________ _______________________________ Joshua Pierce David Shultz DEDICATION This dissertation is dedicated to my loving wife, Michelle. Without you, this document would not exist. Thank you! ii BIOGRAPHY Earning a bachelor’s degree from Aquinas College in Grand Rapids, Michigan, I conducted a senior research project with Assistant Professor of Chemistry Jonathan Fritz. Beginning my master’s degree in chemistry at Illinois State, I transitioned from experimental chemistry into the field of theoretical chemistry by joining Professor Jean Standard’s lab. This shift was fueled by an interest to utilize computational tools to understand molecular mechanisms and then apply these insights to experimental design. I saw the field of theoretical chemistry as a limitless resource to help guide scientists in designing their research projects and, simultaneously, helping them to more efficiently utilize time and resources. As a member of the Standard Lab at Illinois State University, I employed quantum mechanics to model donor- acceptor complexes and studied their role in the removal of sulfur from coal flue gas. This work earned the MidWestern Association of Graduate Schools (MAGS)/ProQuest Outstanding Thesis Award in Mathematical, Physical Sciences, and Engineering. After completing my master’s degree, I moved to Raleigh, North Carolina, to pursue a Ph.D. in chemistry at NCSU under Dr. Denis Fourches. During the past 4 years I have gained cheminformatics experience as part of the Fourches Lab conducting virtual screening, molecular docking, and molecular dynamics, and scientific writing. In addition to my research efforts, I served the chemistry department in science communication and outreach acting as Chemistry Graduate Student Association social media chair and as a science writer. Upon completion of my Ph.D. I will be pursuing a career in industry. iii ACKNOWLEDGMENTS I would like to thank Dr. Denis Fourches for all the guidance he has given me these past 4 years. I would also like to thank Dr. Gavin Williams, Dr. Joshua Pierce, Dr. David Shultz, and Dr. Fred Wright for being on my committee. The past 4 years here at North Carolina State University have been a wonderful growth and learning experience for me and I am grateful for all the professors, students, and friends which I have had the privilege to cross paths with. I would also like to thank the North Carolina State Chemistry Department for funding my educational and research experience. Finally, I would like to thank all my family and friends for their continued support over the years. To my mom Julie Van Den Driessche, my dad Hank Van Den Driessche, my Grandpa and Grandma Van Den Driessche, and my parents-in-law, Brent and Denise Benmark – thank you all. iv TABLE OF CONTENTS LIST OF TABLES ......................................................................................................................... ix LIST OF FIGURES .........................................................................................................................x CHAPTER 1: Introduction ..............................................................................................................1 REFERENCES ................................................................................................................................3 SECTION I: Cheminformatics Approaches to Modeling HLA-Mediated Adverse Drug Reactions ..........................................................................................................................................5 CHAPTER 2: Adverse Drug Reactions Triggered by the Common HLA-B*57:01 Variant: A Molecular Docking Study ................................................................................................................5 Chapter 2 Summary ...................................................................................................................6 2.1. Introduction .........................................................................................................................7 2.2. Materials and Methods ......................................................................................................11 2.2.1. Dataset ......................................................................................................................... 11 2.2.2. Molecular Docking ..................................................................................................... 13 2.3. Results and discussion ......................................................................................................16 2.3.1. Alignment of 3VRI, 3VRJ, and 3UPR