Saudi Cultural Missions Theses & Dissertations
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Item Restricted Developing Novel Antiviral Agents: Targeting the N-Terminal Domain of SARS-CoV-2 Nucleocapsid Protein with Small Molecule Inhibitors(Virginia Commonwealth University, 2024-05-13) Alkhairi, Mona A.; Safo, Martin K.The COVID-19 pandemic, caused by SARS-CoV-2, persists globally with over 7 million deaths and 774 million infections. Urgent research is needed to understand virus behavior, especially considering the limited availability of approved medications. Despite vaccination efforts, the virus continues to pose a significant threat, highlighting the need for innovative approaches to combat it. The SARS-CoV-2 nucleocapsid protein (NP) emerges as a crucial target due to its role in viral replication and pathogenesis. The SARS-CoV-2 NP, essential for various stages of the viral life cycle, including genomic replication, virion assembly, and evasion of host immune defenses, comprises three critical domains: the N-terminal domain (NTD), C-terminal domain (CTD), and the central linker region (LKR). Notably, the NTD is characterized by a conserved electropositive pocket, which is crucial for viral RNA binding during packaging stages. This highlights the multifunctionality of the nucleocapsid protein and its potential as a therapeutic target due to its essential roles and conserved features across diverse pathogenic coronavirus species. Our collaborators previously initiated an intriguing drug repurposing screen, identifying certain β-lactam antibiotics as potential SARS-CoV-2 NP-NTD protein inhibitors in vitro. The current study employed ensemble of computational methodologies, biophysical, biochemical and X-ray crystallographic studies to discover novel chemotype hits against NP-NTD. Utilizing a combination of traditional molecular docking tools such as AutoDock Vina, alongside AI-enhanced techniques including Gnina and DiffDock for enhanced performance, eleven structurally diverse hit compounds predicted to target the SARS-CoV-2 NP-NTD were identified from the virtual screening (VS) studies. The hits include MY1, MY2, MY3, MY4, NP6, NP7, NP1, NP2, NP3, NP4 and NP5, which demonstrated favorable binding orientations and affinity scores. Additionally, one supplementary compound provided by Dr. Cen’s laboratory (denoted as CE) was assessed in parallel. These hits were further evaluated for their in vitro activity using various biophysical and biochemical techniques including differential scanning fluorimetry (DSF), microscale thermophoresis (MST), fluorescence polarization (FP), and electrophoretic mobility shift assay (EMSA). DSF revealed native NTD had a baseline thermal melting temperature (Tm) of 43.82°C. The compounds NP3, NP6 and NP7 notably increased the Tm by 2.55°C, 2.47°C and 2.93°C respectively, indicating strong thermal stabilization over the native protein. In contrast, NP4 and NP5 only achieved marginal Tm increases. MST studies showed NP1, NP3, and NP7 exhibited the strongest affinity with low micromolar dissociation constants (KD) of 0.32 μM, 0.57 μM, and 0.87 μM, respectively, significantly outperforming the control compounds PJ34 and Suramin, with dissociation constants of 8.35 μM and 5.24 μM, respectively. Although NP2, NP6, and CE showed relatively weaker affinity, these compounds still demonstrated better binding affinities with dissociation constants of 4.1 μM, 2.50 μM, and 1.81 μM, respectively than the control compounds PJ34 and Suramin. These results substantiate the potential of these scaffolds as modulators of NTD activity. In FP competition assays, NP1 and NP3 exhibited the lowest half-maximal inhibitory concentrations (IC50) of 5.18 μM and 5.66 μM, respectively, indicating the highest potency at disrupting the NTD-ssRNA complex among the compounds, outperforming the positive controls PJ34 and Suramin, with IC50 of 21.72 μM and 17.03 μM, respectively. The compounds NP6, NP7, CE, and NP2 also showed significant IC50 values that ranged from 7.00 μM to 10.13 μM. EMSA studies confirmed the NTD-ssRNA complex disruptive abilities of the compounds, with NP1 and NP3 as the most potent with IC50 of 2.70 μM and 3.31 μM, respectively. These values compare to IC50 of 8.64 μM and 3.61 μM of the positive controls PJ34 and Suramin, respectively. NP7, CE, NP6, and NP2 also showed IC50 ranging from 4.31 μM to 7.61 μM. The use of full-length nucleocapsid protein also showed that NP1 and NP3 disrupted the NP-ssRNA binding with IC50 of 1.67 μM and 1.95 μM, which was better than Suramin with IC50 of 3.24 μM. These consistent results from both FP and EMSA highlight the superior effectiveness of NP1 and NP3 in disrupting nucleocapsid protein-ssRNA binding, showcasing their potential as particularly powerful antiviral agents. Extensive crystallization trials were conducted to elucidate the atomic structures of SARS-CoV-2 NP-NTD in complex with selected hit compounds, assessing over 8000 unique crystallization conditions. Ultimately, only a PJ34-bound structure could be determined, albeit with weak ligand density, likely due to tight crystal packing impeding binding site access. The crystal structure was determined to 2.2 Å by molecular replacement using the published apo NP-NTD (PDB 7CDZ) coordinates as a search model, and refined to R-factors of 0.193 (Rwork) and 0.234 (Rfree). The refined NP-NTD structure showed conserved intermolecular interactions with PJ34 at the RNA binding pocket as observed in the previously reported HCoV-OC43 NP-NTD-PJ34 complex (PDB 4KXJ). This multi-faceted drug discovery endeavor, combining computational screening and in vitro assays resulted in successful identification of novel compounds inhibiting the SARS-CoV-2 nucleocapsid N-terminal domain. Biophysical and biochemical studies established compounds NP1 and NP3 as superior hits with low micromolar binding affinities, as well as low micromolar potency superior to standard inhibitors at disrupting both isolated N-NTD-RNA and full-length nucleocapsid-RNA complex formation. Though crystallographic efforts encountered challenges, important validation was achieved through a resolved crystal structure of PJ34 in complex with NP-NTD. Future effort will be to obtain co-crystals of NP-NTD with our compounds to allow for targeted structure modification to improve on the potency of the compounds.6 0Item Restricted Developing Antiviral Drugs for COVID-19 and Hepatitis C: Targeting Key Viral Proteases(Virginia Commonwealth University, 2024-05-14) AlAwadh, Mohammed; Safo, Martin K.Viruses are submicroscopic infectious agents causing immense global disease burdens. Propagation of viral particles relies on proteolytic cleavage of polyprotein precursors by host or virally-encoded proteases to liberate functional components necessary for replication and infection cycles. These processing events present vulnerable intervention points for antiviral targeting. This thesis focused on two indispensable viral proteases - the SARS-CoV-2 main protease and the NS3 protease domain from hepatitis C virus. The first project centered on the discovery of small molecule inhibitors against the SARS-CoV-2 main protease (Mpro). As a cysteine protease, Mpro plays an indispensable role in processing the virally-encoded replicase polyproteins through specific cleavages to liberate functional non-structural proteins that regulate virion maturation and assembly pathways. Owing to such critical involvement, Mpro offered an attractive target for coronavirus pathogenesis intervention. Its near-identical architecture with the SARS-CoV strain enabled rapid knowledge transfer for drug design using prior scaffolds. Therefore, an ensemble small molecule discovery platform consolidating computational screening, synthetic chemistry, enzymology and biophysical characterization was constructed to systematically retrieve inhibitors against this important drug target. Three virtual screening protocols using complementary in silico techniques – ligand-based 3D pharmacophore searches, protein structure-centric molecular docking, and artificial intelligence models employed deep neural networks. This triaged computational workflow efficiently narrowed a search space of millions to selectively cherry pick prospective hit candidates. In parallel, quantitative structure-activity examinations of a small, focused library of 168 synthetically derived α-ketoamide compounds revealed a reactive Michael acceptor warhead amenable for covalently targeting the key catalytic cysteine residue. Downstream characterization in a tiered cascade of biochemical and biophysical techniques validated the tandem computational-experimental screening approach. Fluorescence resonance energy transfer (FRET) enzyme assays confirmed dose-dependent SARS CoV-2 Mpro inhibition for 10 ligands – 7 from virtual screening pipelines and 3 α-ketoamide derivatives – with low micromolar half maximal inhibitory concentrations between 1.7-55 μM. Direct binding quantification via label-free biophysical methods like microscale thermophoresis and isothermal titration calorimetry supplemented functional data. The tightest-binder, compound MA4, achieved a binding affinity of around 5 μM. Attempts to co-crystallize Mpro with ligands for atomic perspectives encountered technical limitations likely owing to poor aqueous solubility, nevertheless yielding 1.8 Å resolution apo-enzyme insight into plasticity elements lining the substrate binding cleft. Microsecond timescale explicit-solvent molecular dynamics simulations tracked long-term dynamic stabilities of inhibitor-bound complexes, corroborated through rigorously computed binding free energy predictions. Lastly, objective hit enrichment and success rate metrics evaluated relative virtual screening performances, demonstrating superior early retrieval rates for the deep learning technique that leveraged biochemical data patterns. The second collaborative project expanded targeting scope beyond conventionally exploited catalytic sites to explore an allosteric regulatory protein-protein interface on the hepatitis C NS3 protease domain. NS3 requires binding of a co-factor NS4A peptide to achieve sufficient catalytic activity essential for mediating downstream viral polyprotein processing events linked to replication competency. NS4A triggers key structural rearrangements in otherwise natively disordered NS3 that enable organization of the catalytic triad into a configuration competent for catalyzing substrates. This activation paradigm presented possibilities for blocking the interaction site with engineered variants retaining affinity but subtly distorting functional geometries through strategic mutations. Results validated this, revealing a designed nanomolar-binding NS4A variant with a single cyclohexylglycine substitution that associated with NS3 but eliminated enzyme activity. Microscale thermophoresis quantifications revealed PEP15 associated with the NS3 protease domain target with remarkably high, low nanomolar binding affinity exhibiting a dissociation constant (KD) of 22.23 ± 0.297 nM. This was approximately two orders of magnitude stronger binding compared to the native NS4A cofactor peptide, which achieved a KD of 2.595 ± 0.0015 μM in the same assay configuration. The exceptionally improved affinity despite a single residue substitution substantiates the significant energetics contributions of the engineered glycine mutation and validates the allosteric targeting rationale underlying the inhibitor design. Differential scanning fluorimetry indicated unexpected reductions in thermal stability relative to native complex or isolated protein controls. Metadynamics simulations provided insights into the unexpected biophysical findings by modeling dynamics and stability of the PEP15-NS3 complex. The trajectories revealed favorable occupying of the deep hydrophobic environment lining the NS3 allosteric pocket by the engineered glycine substitution. Notably, the modelling also captured shifting of the key SER139 hydroxyl moiety away from the organized catalytic triad geometric center. Displacement of this nucleophilic residue plausibly misaligns other proximal components due to intricate hydrogen bonding networks. Structural rearrangement of active site elements likely contributes to the abolished enzymatic activity despite high affinity binding of the strategic PEP15 peptide.33 0Item Restricted Using Artificial Intelligence to Improve the Diagnosis and Treatment of Cancer(The University of Melbourne, 2024-02-01) Aljarf, Raghad; Ascher, DavidCancer is a complex and heterogeneous disease driven by the accumulation of mutations at the genetic and epigenetic levels—making it particularly challenging to study and treat. Despite Whole-genome sequencing approaches identifying thousands of variations in cancer cells and their perturbations, fundamental gaps persist in understanding cancer causes and pathogenesis. Towards this, my PhD focused on developing computational approaches by leveraging genomic and experimental data to provide fundamental insights into cancer biology, improve patient diagnosis, and guide therapeutic development. The increased mutational burden in most cancers can make it challenging to identify mutations essential for tumorigenesis (drivers) and those that are just background accumulation (passenger), impacting the success of targeted treatments. To overcome this, I focused on using insights about the mutations at the protein sequence and 3D structure level to understand the genotype-phenotype relationship to tumorigenesis.I have looked at proteins that participate in two DNA repair processes: primarily non homologous end joining (NHEJ) along with eukaryotic homologous recombination (HR), where missense mutations have been linked to many diverse cancers. The molecular consequences of these mutations on protein dynamics, stability, and binding affinities to other interacting partners were evaluated using in silico biophysical tools. This highlighted that cancer-causing mutations were associated with structure destabilization and altered protein conformation and network topology, thus impacting cell signalling and function. Interestingly, my work on NHEJ DNA repair machinery highlighted diverse driving forces for carcinogenesis among core components like Ku70/80 and DNA-PKcs. Cancer-causing mutations in anchor proteins (Ku70/80) impacted crucial protein-protein interactions, while those in catalytic components (DNA-PKcs) were likely to occur in regions undergoing purifying selection. This insight led to a consensus predictor for identifying driving mutations in NHEJ. While when assessing the functional consequences of BRCA1 and BRCA2 genes of HR DNA repair at the protein sequence level, this methodology underlined that cancer-causing mutations typically clustered in well-established structural domains. Using this insight, I developed a more accurate predictor for classifying pathogenic mutations in HR repair compared to existing approaches.This broad heterogeneity of cancers complicates potential treatment opportunities. I, therefore, next explored the properties of compounds potentially active against one or various types of cancer, including screens against 74 distinct cancer cell lines originating from 9 tumour types. Overall, the identified active molecules were shown to be enriched in benzene rings, aligning with Lipinski's rule of five, although this might reflect screening library biases. These insights enabled the development of a predictive platform for anticancer activity, thereby optimizing screening libraries with potentially active anticancer molecules.Similarly, I used compounds' structural and molecular properties to accurately predict those compounds with increased teratogenicity early in the drug development process and prioritize drug combinations to augment combinatorial screening libraries, potentially alleviating acquired drug resistance. The outcomes of this doctoral work highlight the potential benefits of using computational approaches in unravelling the underlying mechanisms of carcinogenesis and guiding drug discovery for designing more effective therapies. Ultimately, the predictions generated by these tools would improve our understanding of the genotype-phenotype association, enabling promising patient diagnosis and treatment.25 0Item Restricted Natural product inhibitors of Acetyl-CoA Carboxylase – A drug target in Type 2 Diabetes Mellitus(Saudi Digital Library, 2023-09-28) Alshamrani, Mohammed; Munday, MichaelType-2 diabetes mellitus (T2DM) is approaching epidemic proportions and threatens to become a global health issue, representing 9.9% of mortality worldwide. Raised plasma fatty acids are associated with obesity and are a cause of insulin resistance in T2DM. Consequently, there is a growing need to search for new, more efficient therapeutic approaches that not only decrease blood glucose, but also reduce the insulin resistance of diabetic patients. Acetyl-CoA carboxylase (ACC) is a crucial enzyme of fatty acid metabolism in mammals and consists of two isoforms. It catalyses the formation of malonyl-CoA, the precursor of fatty acid synthesis (ACC1) and inhibitor of fatty acid oxidation (ACC2). Recent studies in mice deficient in one of two main ACC isoforms (ACC2) demonstrated increased fatty acid oxidation with markedly improved insulin sensitivity. Therefore, ACC inhibitors represent a viable approach for the treatment of T2DM. Natural products have been recognised as a rich source of compounds with structural diversity for therapeutical potential. The aim of this study was to screen Middle Eastern plant extracts and identify their bioactive compounds responsible for ACC1/ACC2-inhibitory effects. Medicinal plants are well recognised as a source of therapeutic agents used by traditional healers and indigenous people in the treatment of various diseases based on ethnobotanical evidence. Eight Middle Eastern plants were selected for their published use to treat diabetes including Teucrium polium L., Crataegus azarolus L, Opuntia ficus-indica, Rosa damascena Mill, Achillea arabica kotschy, Pistacia falcata Becc. Ex Martell, Acacia ehrenbergiana Hayne, and Acacia asak (forss K). The plant extracts were prepared using sequential solvent extraction, and then assayed for inhibitory activity against purified ACC1 and ACC2 in vitro. The chloroform extract of A. Arabica and the methanolic extracts of R. Damascena, C. Azarolus and A. Asak showed the most promising ACC inhibition, so were subjected to chemical characterisation using LC-ESI-MS/MS. Flavonoids, acylated spermidines, and benzoic acid derivatives were tentatively identified in the methanolic extract of Rosa damascena, while the chloroform extract of Achillea arabica contained sesquiterpene lactones and methylated flavones. Crataegus azarolus predominantly contained procyanidins and sugars, while Acacia asak was rich in methylated flavonoids, dihydroflavonols, and hydroxybenzoic acid derivatives. Bioguided fractionation was performed on the selected active extracts employing partition chromatography, solid phase extraction (SPE) and thin layer chromatography. LC-ESI-MS/MS and NMR analysis of the sub-fractions shown to inhibit ACC1 led to the identification of tri-p-coumaroyl spermidine, astragalin, afzelin and tiliroside from Rosa damascena; hyperoside, procyanidin B2, catechin and epicatechin from Crataegus azarolus; taxifolin, isorhamnetin, aromadendrin and rhamnocitrin from Acacia asak and chrysosplenol D from Achillea arabica. This study supports the anti-diabetic potential of isolates or fractions from the selected Middle Eastern plants as evidenced by their ability to inhibit ACC, a key anti-diabetic drug target. The investigation of the compounds identified as potential lead compounds for the discovery of anti-T2DM drugs would a desirable consequence of the current study.45 0