Computational approaches to targeting structured genomic regions of viral genomes, the case of metal-containing drugs

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Melidis, Lazaros (2022). Computational approaches to targeting structured genomic regions of viral genomes, the case of metal-containing drugs. University of Birmingham. Ph.D. 7174-7184. doi: 10.1039/d1sc00933h.

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Abstract

Infectious agents and especially viruses have had a tremendous impact on all stages of the
evolution of the living matter. Being only composed of a few biomolecules they are often seen as a relic of processes from the early emergence of life on earth, but also they have contributed throughout evolution in all kingdoms of life. Throughout human history, infectious diseases have played significant role in the route of history, both regarding total death toll as well as policy changes. However, the highly dynamic nature of viral evolution in combination with overlapping mechanisms between the virus and the host poses a significant challenge for antiviral drug design based on traditional methods. This thesis examines the structural and dynamical properties of nucleic acid sequences from viruses as potentially broad-spectrum and robust antiviral target. The introductory chapter briefly introduces nucleic acid structures and previous work from the Hannon group on nucleic acid targeting and reviews viral processes throughout the different classifications. It also introduces theoretical and computational methods that could shine light on the generally elusive dynamical landscape of nucleic acid structures. After methodology is described in chapter a 2, fundamental theoretical understanding of dynamic molecular processes is discussed in chapter 3. Here, structure and dynamics of coordination compounds are discussed, in an effort to examine those away from crystal structure limitations. Employing Density Functional Theory (DFT), different spin states of complex molecules are discussed with the potential implications to metastable states within a chemical species. In chapter 4, work from the earlier chapters is applied in the understanding of structure and dynamics of HIV-1’s TAR RNA, the most well-characterised RNA structure in literature. Having validated the Molecular Dynamics approach against known properties of TAR RNA, comparing metastable states identified through a Markov state model of the system with published NMR data, its potential interactions with supramolecular cylinders are examined resulting in a proposed dominant binding mode in agreement with previous experimental results. Chapter 5 introduces a pipeline for in silico optimisation of molecules targeting RNA given only the sequence of a novel virus (in this case SARS-CoV2). From sequence, secondary and tertiary structure are proposed and using molecular dynamics the conformational landscape of some of its metastable states can be sampled, exposing potentially key regions that could be targeted and change the RNA’s behaviour and thus potentially disturbing the viral replication cycle. The predictions of the pipeline have been experimentally verified in collaboration with the Grzechnik group and in cellulo effects are also being observed and reported. In Chapter 6, DNA structures are investigated this time, specifically G quadruplexes (G4s). After a very brief exploration of the interaction of previously characterized mono-nuclear complexes with human G4s (MYC and H-Telo) at the MD level of theory, the chapter focuses on the newly identified (2018) unique structure of HIV-1 LTR G4. This G4 structure features a stem on top of a guanine quartet potentially creating a high affinity target aiming to change the dynamics of the structure. The previously established methodology in mapping molecular interactions between ligands and nucleic acids is also applied here and a global minimum can be suggested although further simulations and coordination with experiments is needed for conclusive mapping of the interaction. Chapters 4 and 5 have been published and are presented here verbatim, as well as parts of Chapter 3 whereas Chapter 6 has not been published.

Type of Work:

Thesis (Doctorates > Ph.D.)

Award Type:

Doctorates > Ph.D.

Supervisor(s):