Identification and characterisation of somatic regulatory mutations in the breast cancer genome

Luminal breast cancer remains a major clinical challenge with over 2 million cases diagnosed annually. While prognosis is favourable in these patients, roughly 40% will relapse over the course of the next 20 years. Understanding the evolution of disseminated tumour cells at distal sites is critical to effectively treating these patients. While metastatic driver mutations, such as those in the Oestrogen Receptor (ESR1) gene, can be identified in many cases for a significant proportion of patients, clear drivers remain elusive. A limitation of previous genomics studies in metastatic breast cancer is their focus on the coding genome. Advances in our understanding have revealed the critical role of regulatory elements such as enhancers and promoters in transcriptional regulation. This effect is mediated through the functional and hierarchical organisation of chromatin within the nucleus, the key unit of chromatin organisation is the Topologically Associating Domains (TADs). TAD organisation is, in part, mediated by the CCCTC-Binding Factor (CTCF) protein which physically binds to DNA mediating the formation of loops and domains. Together promoters, enhancers, and CTCF-bound regions provide potential as sites for non-coding mutations to occur, drastically impacting gene regulation and tumour evolution. In this work we interrogate the contribution of regulatory element mutations in the evolution of metastatic breast cancer. This is done through two projects. First, a proof of principle study functionally characterising a clinically relevant CTCF binding site mutation. Second, through the design of an informed panel of regulatory regions utilised in a longitudinal targeted sequencing study in patient samples and a CRISPRi perturbation study in cell lines. Through these studies we provide evidence that the mutation of TAD boundary associated CTCF binding sites is unlikely to contribute to tumour evolution. We also fail to identify recurrence of non-coding drivers, though more patient specific mutations may contribute to metastatic evolution. Results obtained from the CRISPRi screen illustrate the functionality of the regulatory regions in the panel, identifying regulatory elements that confer fitness or vulnerabilities when specifically repressed. This study identifies that repression of several members of the NF-κB signalling pathway provides MCF7 cells with an advantage in adapting to oestrogen deprivation. This data underlines the importance of regulatory regions in the evolution of luminal breast cancers and indicates that non-genetic mechanisms may play a key role.Open Acces

Prediction of protein allosteric signalling pathways and functional residues through paths of optimised propensity

Allostery commonly refers to the mechanism that regulates protein activity through the binding of a molecule at a different, usually distal, site from the orthosteric site. The omnipresence of allosteric regulation in nature and its potential for drug design and screening render the study of allostery invaluable. Nevertheless, challenges remain as few computational methods are available to effectively predict allosteric sites, identify signalling pathways involved in allostery, or to aid with the design of suitable molecules targeting such sites. Recently, bond-to-bond propensity analysis has been shown successful at identifying allosteric sites for a large and diverse group of proteins from knowledge of the orthosteric sites and its ligands alone by using network analysis applied to energy-weighted atomistic protein graphs. To address the identification of signalling pathways, we propose here a method to compute and score paths of optimised propensity that link the orthosteric site with the identified allosteric sites, and identifies crucial residues that contribute to those paths. We showcase the approach with three well-studied allosteric proteins: h-Ras, caspase-1, and 3-phosphoinositide-dependent kinase-1 (PDK1). Key residues in both orthosteric and allosteric sites were identified and showed agreement with experimental results, and pivotal signalling residues along the pathway were also revealed, thus providing alternative targets for drug design. By using the computed path scores, we were also able to differentiate the activity of different allosteric modulators

Prediction of allosteric sites and signalling: insights from benchmarking datasets

Allostery is a pervasive mechanism that regulates protein activity through ligand binding at a site different from the orthosteric site. The universality of allosteric regulation complemented by the benefits of highly specific and potentially non-toxic allosteric drugs makes uncovering allosteric sites invaluable. However, there are few computational methods to effectively predict them. Bond-to-bond propensity analysis has successfully predicted allosteric sites in 19 of 20 cases using an energy-weighted atomistic graph. We here extended the analysis onto 432 structures of 146 proteins from two benchmarking datasets for allosteric proteins: ASBench and CASBench. We further introduced two statistical measures to account for the cumulative effect of high-propensity residues and the crucial residues in a given site. The allosteric site is recovered for 127 of 146 proteins (407 of 432 structures) knowing only the orthosteric sites or ligands. The quantitative analysis using a range of statistical measures enables better characterization of potential allosteric sites and mechanisms involved

Text Mining Improves Prediction of Protein Functional Sites

We present an approach that integrates protein structure analysis and text mining for protein functional site prediction, called LEAP-FS (Literature Enhanced Automated Prediction of Functional Sites). The structure analysis was carried out using Dynamics Perturbation Analysis (DPA), which predicts functional sites at control points where interactions greatly perturb protein vibrations. The text mining extracts mentions of residues in the literature, and predicts that residues mentioned are functionally important. We assessed the significance of each of these methods by analyzing their performance in finding known functional sites (specifically, small-molecule binding sites and catalytic sites) in about 100,000 publicly available protein structures. The DPA predictions recapitulated many of the functional site annotations and preferentially recovered binding sites annotated as biologically relevant vs. those annotated as potentially spurious. The text-based predictions were also substantially supported by the functional site annotations: compared to other residues, residues mentioned in text were roughly six times more likely to be found in a functional site. The overlap of predictions with annotations improved when the text-based and structure-based methods agreed. Our analysis also yielded new high-quality predictions of many functional site residues that were not catalogued in the curated data sources we inspected. We conclude that both DPA and text mining independently provide valuable high-throughput protein functional site predictions, and that integrating the two methods using LEAP-FS further improves the quality of these predictions

Targeting allosteric sites of Escherichia coli heat shock protein 70 for antibiotic development

Hsp70s are members of the heat shock proteins family with a molecular weight of 70-kDa and are the most abundant group in bacterial and eukaryotic systems, hence the most extensively studied ones. These proteins are molecular chaperones that play a significant role in protein homeostasis by facilitating appropriate folding of proteins, preventing proteins from aggregating and misfolding. They are also involved in translocation of proteins into subcellular compartments and protection of cells against stress. Stress caused by environmental or biological factors affects the functionality of the cell. In response to these stressful conditions, up-regulation of Hsp70s ensures that the cells are protected by balancing out unfolded proteins giving them ample time to repair denatured proteins. Hsp70s is connected to numerous illnesses such as autoimmune and neurodegenerative diseases, bacterial infection, cancer, malaria, and obesity. The multi-functional nature of Hsp70s predisposes them as promising therapeutic targets. Hsp70s play vital roles in various cell developments, and survival pathways, therefore targeting this protein will provide a new avenue towards the discovery of active therapeutic agents for the treatment of a wide range of diseases. Allosteric sites of these proteins in its multi-conformational states have not been explored for inhibitory properties hence the aim of this study. This study aims at identifying allosteric sites that inhibit the ATPase and substrate binding activities using computational approaches. Using E. coli as a model organism, molecular docking for high throughput virtual screening was carried out using 623 compounds from the South African Natural Compounds Database (SANCDB; https://sancdb.rubi.ru.ac.za/) against identified allosteric sites. Ligands with the highest binding affinity (good binders) interacting with critical allosteric residues that are druggable were identified. Molecular dynamics (MD) simulation was also performed on the identified hits to assess for protein-inhibitor complex stability. Finally, principal component analysis (PCA) was performed to understand the structural dynamics of the ligand-free and ligand-bound structures during MD simulation

Mitigation of off-target toxicity in CRISPR-Cas9 screens for essential non-coding elements.

Pooled CRISPR-Cas9 screens are a powerful method for functionally characterizing regulatory elements in the non-coding genome, but off-target effects in these experiments have not been systematically evaluated. Here, we investigate Cas9, dCas9, and CRISPRi/a off-target activity in screens for essential regulatory elements. The sgRNAs with the largest effects in genome-scale screens for essential CTCF loop anchors in K562 cells were not single guide RNAs (sgRNAs) that disrupted gene expression near the on-target CTCF anchor. Rather, these sgRNAs had high off-target activity that, while only weakly correlated with absolute off-target site number, could be predicted by the recently developed GuideScan specificity score. Screens conducted in parallel with CRISPRi/a, which do not induce double-stranded DNA breaks, revealed that a distinct set of off-targets also cause strong confounding fitness effects with these epigenome-editing tools. Promisingly, filtering of CRISPRi libraries using GuideScan specificity scores removed these confounded sgRNAs and enabled identification of essential regulatory elements

Mechanistic insights into allosteric regulation of the A2A adenosine G protein-coupled receptor by physiological cations.

Cations play key roles in regulating G-protein-coupled receptors (GPCRs), although their mechanisms are poorly understood. Here, 19F NMR is used to delineate the effects of cations on functional states of the adenosine A2A GPCR. While Na+ reinforces an inactive ensemble and a partial-agonist stabilized state, Ca2+ and Mg2+ shift the equilibrium toward active states. Positive allosteric effects of divalent cations are more pronounced with agonist and a G-protein-derived peptide. In cell membranes, divalent cations enhance both the affinity and fraction of the high affinity agonist-bound state. Molecular dynamics simulations suggest high concentrations of divalent cations bridge specific extracellular acidic residues, bringing TM5 and TM6 together at the extracellular surface and allosterically driving open the G-protein-binding cleft as shown by rigidity-transmission allostery theory. An understanding of cation allostery should enable the design of allosteric agents and enhance our understanding of GPCR regulation in the cellular milieu

Characterization of the Interaction between the Parkin Ubiquitin-like domain and Ataxin-3 Ubiquitin Interacting Domains

The ubiquitin signaling pathway (USP) consists of hundreds of enzymes which are tightly regulated for proper maintenance of intracellular protein level homeostasis. The main goals of this thesis were to characterize the interaction of two proteins involved in the USP, the E3 ubiquitin ligase called parkin, and the Deubiquitinating (DUB) enzyme, ataxin-3. The effect of disease-state substitutions in the parkin ubiquitin-like domain (UbLD) on the interaction with ataxin-3 was investigated through NMR 1H-15N HSQC titration experiments and affinity binding assays. The three UIM regions in ataxin-3bind the hydrophobic patch of parkin UbLD (KD = 680 μM) and are proposed to use a multivalent binding mechanism. The disease-state UbLD proteins (UbLDV15M, UbLDR33Q, UbLDK48A) retain their interaction with ataxin-3. Other DUB enzymes and E3 ligases have been reported to have regulatory interplay, which has triggered interest in studying protein pairings such as ataxin-3 and parkin

Minimal metabolic pathway structure is consistent with associated biomolecular interactions

Pathways are a universal paradigm for functionally describing cellular processes. Even though advances in high-throughput data generation have transformed biology, the core of our biological understanding, and hence data interpretation, is still predicated on human-defined pathways. Here, we introduce an unbiased, pathway structure for genome-scale metabolic networks defined based on principles of parsimony that do not mimic canonical human-defined textbook pathways. Instead, these minimal pathways better describe multiple independent pathway-associated biomolecular interaction datasets suggesting a functional organization for metabolism based on parsimonious use of cellular components. We use the inherent predictive capability of these pathways to experimentally discover novel transcriptional regulatory interactions in Escherichia coli metabolism for three transcription factors, effectively doubling the known regulatory roles for Nac and MntR. This study suggests an underlying and fundamental principle in the evolutionary selection of pathway structures; namely, that pathways may be minimal, independent, and segregated

Enzymatic Characterization Of The Ammonia Tunnel In Helicobacter Pylori Asp-Trnaasn/glu-Trnagln Amidotransferase

The Helicobacter pylori (H. pylori) Asp-tRNAAsn/Glu-tRNAGln amidotransferase (AdT) plays important roles in indirect aminoacylation and translational fidelity; however, its inter-domain communication and ammonia delivery mechanisms are not well understood. In the present study, we investigated the three activities of H. pylori AdT (glutaminase, kinase and transamidase) and used these reactions as probes to examine the inter-domain communication and ammonia delivery mechanisms between this enzyme\u27s two isolated active sites. We adapted and optimized an assay to kinetically characterize a series of mutations at conserved positions throughout the putative AdT ammonia tunnel. The kinase assay enabled us to identify mutations within AdT, specifically T149 and K89, for further enzymatic characterization and molecular dynamics (MD) simulations and correlation analyses to unveil a set of 59 residues that may form the interdomain communication pathway between AdT\u27s two active sites. The glutaminase and transamidase assays identified another residue, D185, in the GatA subunit. Kinetic and computational characterizations of D185 AdT mutants suggest that D185 serves as a general acid or base in ammonia delivery. These results are the first demonstration of acid/base chemistry within an ammonia tunnel. Finally, preliminary characterization of the predicted ammonia tunnel gate residues (K89 and E126 in the GatB subunit) suggest that proper positioning of the appropriate charge states in the tunnel are important for AdT catalysis. The results presented in this dissertation extend our understanding of AdT\u27s distinct ammonia transfer mechanism