Method development in chemical and biological selection platforms Part one: Reaction mining: A platform for the discovery of novel chemical reactivity Part two: Synthetic platforms for the characterization and targeting of viral RNA-capping enzymes

Szczepankiewicz, Daniel Timothy

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Description

Title

Method development in chemical and biological selection platforms Part one: Reaction mining: A platform for the discovery of novel chemical reactivity Part two: Synthetic platforms for the characterization and targeting of viral RNA-capping enzymes

Author(s)

Szczepankiewicz, Daniel Timothy

Issue Date

2024-03-27

Director of Research (if dissertation) or Advisor (if thesis)

• Mehta, Angad P
• Sarlah, David

Doctoral Committee Chair(s)

Mehta, Angad P

Committee Member(s)

• Hergenrother, Paul J
• Denmark, Scott E

Department of Study

Chemistry

Discipline

Chemistry

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

• Organic Chemistry
• Chemical Biology
• Medicinal Chemistry
• High Throughput Screening
• Nsp14
• Sars-cov-2
• Covid-19
• Monkeypox
• Mpox
• Bisubstrate Inhibitor

Language

eng

Abstract

PART ONE: REACTION MINING: A PLATFORM FOR THE DISCOVERY OF NOVEL CHEMICAL REACTIVITY High-Throughput Experimentation (HTE) is an enabling technology that allows chemists to carry out hundreds of reactions in the time in would take to set up one. However, the use of HTE in reaction discovery has reached a bottleneck in the acquisition and interpretation of experimental data. Herein, we describe the design and refinement of a computational method for the deconvolution of acquired UPLC/MS data, coupled with isotopic ratio labeling provides a system by which to identify potential reactions without human inspection of acquired data. The platform is used to probe the spaces of ruthenium, palladium, nickel, and copper-catalyzed coupling reactions, resulting in the discovery of several novel coupling reactions. PART TWO: SYNTHETIC PLATFORMS FOR THE CHARACTERIZATION AND TARGETING OF VIRAL GENOME-CAPPING ENZYMES Pathogenic RNA viruses pose great danger to human health, as evidenced by the SARS-CoV-2 pandemic. As such, highly conserved mechanisms of RNA viruses represent an attractive and modular therapeutic target. One such conserved yet underexplored mechanism concerns the process of viral RNA capping. Mature RNA caps are required for viral mRNA to be recognized by host cellular replication machinery, provide improved thermal stability, and allow capped viral RNA to circumvent the innate immune system response. In SARS-CoV-2, the N7-Methyltransferase (N7-MTase) mediating this first methylation in the sequence is the S-adenosyl methionine-dependent (SAM-dependent) enzyme known as nonstructural protein 14 (Nsp14). Structurally, these viral MTase enzymes are often highly conserved; the RNA binding site of the SARS-CoV-2 Nsp14 bears high (94.9%) sequence homology to the original SARS-CoV Nsp14, and similar inhibitor profiling has been demonstrated in-vitro between the MPox, SARS-CoV-2, and Zika capping enzymes, suggesting there is potential for broad-spectrum antiviral therapeutics if bioavailable inhibitors can be identified. However, efforts in this field are hampered by poor methyltransferase (MTase) isolation yields, issues with protein solubility, and notable discrepancies between MTase phenotype in in-vitro assays versus apparent behavior in-vivo. For these in-vivo trials, active viral replicons are required, typically mandating the use of BSL-3 facilities, thereby severely restricting the scope of research groups equipped to carry out these assays. In order to address these limitations, our group has developed a concise model system by which to study MTase activity in-vivo using the BSL-1 organism S. cerevisiae, and have since begun utilizing this system to evaluate small molecule inhibitors with the intent to identify candidates which are reliably active in-vivo for further study in full pathogenic assays. Herein, we detail the efforts towards adapting this model system into a high-throughput protocol, as well as the currently ongoing efforts towards inhibitor profiling.

Graduation Semester

2024-05

Type of Resource

Text

Handle URL

https://hdl.handle.net/2142/124490

Copyright and License Information

Copyright 2024 Daniel Szczepankiewicz

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