Studies in Small Molecule Drug Discovery: Part I. Synthesis of Novel Nucleoside-Based Antivirals to Treat Hepatitis C; Part II. Validation and Implementation of a Machine Learning Algorithm to Create a Safer Kinase Inhibitor as a Potential First-in-Class Antiparkinsonian Agent Restricted; Files Only
Dentmon, Zackery W (Fall 2022)
Abstract
Xenobiotics have been used to alleviate human pathology for thousands of years, yet average life expectancy remained flat until the Enlightenment when it began to increase rapidly. Many factors contributed to this rise, but some of the most influential were revolutions in medical science and technology, particularly in the fields of vaccination and anti-infective drug discovery. The invention of new medicines, however, is no trivial task as most contemporary small molecule drugs spend nearly a decade or more in clinical development before a new safe and effective agent is approved. Clearly there is a need not only for new drugs, but also for a new way of discovering them.
Part I of this dissertation discusses a traditional approach to discover new nucleoside-based antivirals to treat hepatitis C virus (HCV). The first chapter provides some historical context for nucleosides in medicine and briefly previews the following two chapters. Chapter 2 details our work building and evaluating a small set of prodrugs of 4’-thionucleoside analogs for anti-HCV activity. Having determined them to be relatively ineffective, Chapter 3 then reports our investigation of a hypothesis to rationalize the poor activity we observed with our analogs from Chapter 2 compared to their parent congener. We used a computational model to suggest some novel modifications which could bias the conformational dynamics of the parent scaffold and support an observed correlation between conformation and potency. This effort produced analogs with even less antiviral efficacy against HCV and confirmed that conformational bias is only one potential consideration in antiviral drug design.
Part II of this dissertation showcases an alternative approach to drug discovery which makes use of artificial intelligence to redesign and improve upon extant drugs exemplified in the literature. Chapter 4 discusses the discovery of our machine learning algorithm and the foundational retrospective and prospective case studies across three diverse biological and chemical targets which validated the AI workflow. The final chapter then relays our efforts at utilizing this technology to redesign a class of antineoplastic kinase inhibitors to make them less cardiotoxic and therefore safer to use in a chronic, unmet medical need like neurodegeneration.
Table of Contents
Part I. Synthesis of Novel Nucleosides and their Monophosphate Prodrugs to Target the RNA-Dependent RNA Polymerase of the Hepatitis C Virus
Chapter 1. Nucleoside & Nucleotide Antivirals: A Preface..................... 1
1.1 INTRODUCTION...............................................................................................................................1
1.2 A FORAY INTO NUCLEOSIDE-BASED INHIBITORS OF HEPATITIS C ......................................3
1.2.1 Thionucleoside Prodrugs – A Preview of Chapter 2................................................................5
1.2.2 A Conformational Consideration – A Preview of Chapter 3....................................................6
1.3 REFERENCES AND NOTES............................................................................................................11
Chapter 2. Synthesis and Antiviral Evaluation of a Series of 4’-Thio Congeners of 2’-C-Methyl-Substituted Ribonucleoside Prodrugs .....14
2.1 INTRODUCTION.............................................................................................................................14
2.2 RESULTS AND DISCUSSION .........................................................................................................17
2.2.1 Synthesis of the 4′-Thionucleosides & Phosphoramidate Prodrugs .......................................17
2.2.2 Antiviral Evaluation of Monophosphate Prodrugs................................................................23
2.3 MATERIALS AND METHODS........................................................................................................26
2.3.1 Synthetic Chemistry.................................................................................................................26
2.3.2 Pharmacology...........................................................................................................................46
2.4 REFERENCES AND NOTES............................................................................................................60
Chapter 3. Synthesis and Antiviral Evaluation of 3’-C-Substituted Congeners of 2’-C-Methyluridine......................................................................65
3.1 INTRODUCTION.............................................................................................................................65
3.2 RESULTS AND DISCUSSION .........................................................................................................71
3.2.1 Synthesis of the Key 3’-Ketonucleoside Intermediate for Diversification...........................71
3.2.2 Synthesis and Antiviral Evaluation of the Nucleoside Monophosphate Prodrugs .............83
3.3 MATERIALS AND METHODS........................................................................................................90
3.3.1 Computational Methods ..........................................................................................................90
3.3.2 Synthetic Chemistry.................................................................................................................90
3.3.3 Pharmacology.........................................................................................................................118
3.4 REFERENCES AND NOTES..........................................................................................................127
Part II. Studies on the Machine Learning Algorithm-Enhanced Hit-to-Lead Optimization of Drug-Like Small Molecules
Chapter 4. The Discovery & Development of FRESH: An Algorithm for Small Molecule Hit-to-Lead Optimization ..........................................135
4.1 INTRODUCTION...........................................................................................................................135
4.1.1 The Design of the FRESH Algorithm .....................................................................................136
4.2 VALIDATION OF FRESH: RETROSPECTIVE CASE STUDIES..................................................139
4.2.1 Phosphotidylinositol 3-Kinase (PI3K) .........................................................................................140
4.2.2 Carbonic Anhydrase II (CA II) ....................................................................................................142
4.2.3. Histone Deacetylase (HDAC)................................................................................................145
4.3 IMPLEMENTATION OF FRESH: PROSPECTIVE CASE STUDIES............................................146
4.3.1 Predicting Potent, Novel Inhibitors of CA II.........................................................................147
4.3.2 Predicting Potent, Novel Inhibitors of PI3Kα.......................................................................149
4.4 REFERENCES AND NOTES..........................................................................................................156
Chapter 5. The Machine Learning Algorithm-Enabled Design and Synthesis of Novel Abelson Non-Receptor Tyrosine Kinase Inhibitors as Safer Therapeutics for Parkinson’s Disease..................160
5.1 INTRODUCTION...........................................................................................................................160
5.2 RESULTS AND DISCUSSION .......................................................................................................163
5.2.1 Core Scaffold and Single-NBN Compound Selection ...........................................................164
5.2.2 Parallel Linear Synthetic Strategy to Access and Evaluate the Single-NBN Compounds .....168
5.2.3 Dual-NBN Compound Selection and a Divergent Synthetic Strategy.................................170
5.2.4 Divergent Synthesis to Access the Dual-NBN Compounds .................................................173
5.2.5 In vitro Evaluation of the Dual-NBN Compounds ................................................................176
5.2.6 In vivo Pharmacokinetic Evaluation of 5.17a and 5.17b .....................................................181
5.3 MATERIALS AND METHODS......................................................................................................188
5.3.1 Synthetic Chemistry...............................................................................................................188
5.3.2 In vitro Pharmacology............................................................................................................214
5.3.3 In vivo Pharmacology .............................................................................................................222
5.4 REFERENCES AND NOTES..........................................................................................................232
Supplemental Appendix.....................................................................................238
SA.1 NMR Spectra of Compounds in Chapter 2 ............................................................................239
SA.1.1 Construction of the Thiosugar Core (2.S1 – 2.9)...............................................................239
SA.1.2 Thionucleosides and Monophosphate Prodrugs (2.11a-f; 2.13a-f) ...............................255
SA.2 NMR Spectra of Compounds in Chapter 3 (3.3 – 3.11) ......................................................289
SA.3 NMR Spectra of Compounds in Chapter 5............................................................................305
SA.3.1 Single-NBN Compounds (5.1 – 5.9c)..................................................................................305
SA.3.2 Dual-NBN Compounds (5.10 – 5.17c)...............................................................................342
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