Understanding Stability of Protein-Protein Complexes

For all living organisms, macromolecular interactions facilitate most of their natural functions. Alterations to macromolecular structures through mutations, can affect the stability of their interactions, which may lead to unfavourable phenotypes and disease. Presented here, are a number of computational methods aimed at uncovering the principles behind complex stability - as described by binding affinity and dissociation rate constants. Several factors are known to govern the stability of protein-protein interactions, however, no one factor dominates, and it is the synergistic effect of a number of contributions, which amount to the affinity, and stability of a complex. The characterization of complex stability can thus be presented as a two-fold problem; modelling the individual factors and modelling the synergistic effect of the combination of such individual factors. Using machine learning as a central framework, empirical functions are designed for estimating affinity, dissociation rates and the effects of mutations on these properties. The performance of all models is in turn benchmarked on experimental data available from the literature and carefully curated datasets. Firstly, a wild-type binding free energy prediction model is designed, composed of a diverse set of stability descriptors, which account for flexibility and conformational changes undergone by the complex in question. Similarly, models for estimating the effects of mutations on binding affinity are also designed and benchmarked in a community-wide blind trial. Emphasis here is on the detection of a small subset of mutations that are able to enhance the stability of two de novo protein drugs targeting the flu virus hemagglutinin. Probing further the determinants of stability, a set of descriptors that link hotspot residues with the off-rate of a complex are designed, and applied to models predicting changes in off-rate upon mutation. Finally, the relationship between the distribution of hotspots at protein interfaces, and the rate of dissociation of such interfaces, is investigated

A Role for Mindbomb 1 in Adenovirus Genome Delivery

The journey from plasma membrane to nuclear pore is a critical step in the lifecycle of DNA viruses, many of which must successfully deposit their genomes into the nucleus for replication. Viral capsids strategically navigate this vast distance (and all subsequent lifecycle steps) through the coordinated hijacking of a number of cellular proteins subsequently termed host factors. Given the virus’ dependence on these proteins, host factors therefore represent valuable targets for therapeutic interventions. Still, the identity and function of many of these factors remains unknown. In this body of work, I will detail our own journey from initial identification to comprehensive characterization of one such host factor, Mindbomb 1 (MIB1), in the context of adenovirus infection. Adenoviruses (AdVs) are widespread and highly contagious DNA viruses that can cause severe respiratory illness in children and immune-compromised individuals. An initial genome-wide loss-of-function screen to identify host factors for this virus revealed MIB1, an E3 ubiquitin ligase best known for its role in neurodevelopment, as critical for AdV infectivity. In a series of mechanistic studies centered on the earliest stage of infection, we observed that in the absence of MIB1, viral capsids successfully traffic to the proximity of the nucleus but ultimately fail to deliver their genomes within. AdV infection is dependent on MIB1’s primary action as an E3 ubiquitin ligase — to carry out ubiquitination, a posttranslational modification widely capitalized upon by viruses for rapid manipulation of the host environment via altered protein localization, activity or turnover. Our work suggests that in the immediate vicinity of the nucleus, MIB1 may be required for the proteasomal degradation of one or more negative regulators of AdV infection. To identify this relevant MIB1-ubiquitination target, we turned to complementary proteomic approaches to determine proteins proximal to MIB1 upon AdV infection and those differentially ubiquitinated in its presence or absence. Using these unbiased approaches, we corroborated previous reports of MIB1 as a core component of centriollar satellites, dynamic structures localized to the intervening distance between centrosome and nucleus. Furthermore, both proteomic approaches independently pointed to an understudied yet evolutionarily-conserved role for MIB1 in regulating RNP granules and cytoskeleton within the perinuclear environment. Understanding the full relevance of these MIB1-regulated pathways to AdV infection and identifying the specific ubiquitination target responsible will be natural extensions of this work to fully dissect the mechanism of MIB1-mediated viral genome delivery. Together, this work highlights yet another creative way in which viruses recruit host cell machinery to facilitate their replication with the potential to inform the design of new antiviral treatments and emerging adenoviral vector-based therapies

Decompositions of Free Energies in Molecular Simulation

This thesis describes advances in methods to measure free energy changes in simulations of molecular systems. In each case the free energy is decomposed into local environments which reveal insights about the complex systems being studied. Free energy is a fundamental quantity that can be used to predict whether changes in state are physically favourable. This can be used to predict the solubility of molecules and whether molecules are likely to bind to proteins. There are a handful of methods which measure free energy from molecular simulations. In chapter 3 we show results for an improved endpoint free energy method using inhomogeneous fluid solvation theory (IFST) which takes second order fluid-fluid entropy corrections into account. This is applied to a system of Lennard-Jones particles which show no measurable second order entropy contribution which fits with theoretical predictions. In chapter 4 an adaptation to the Zwanzig equation for path based exponential averaging methods is made. The equation is expanded to give contributions associated with every atom in the system. This method is called atomwise free energy perturbation and is applied to small molecules and ligand-protein binding. In chapter 5, IFST is applied to decompose hydration free energy at the surface of a protein into hydration sites. From these sites, information is inferred about the binding conformation of two proteins GABARAP and the GABA-A receptor. In chapter 6 statistics from hydration sites around hundreds of proteins are analysed. The distributions of free energy are shown and discussed for hydration sites in a range of local chemical environments. Also in chapter 6, the hydration sites decomposition method is augmented with local energy information associated with replacing a water molecule at a hydration site with a probe. The probe represents a ligand, and this is compared to the binding site prediction from the previous method. Further suggestions for improvements are made

Computational immunology : analyses of viral escape, epitope binding and T cell receptor recognition

It has been shown repeatedly that infectious diseases in humans have strong associations with the human leukocyte antigen system, but an understanding of the basis of these associations remains elusive. Adaptive immune responses involving CD4 and CD8 T lymphocytes are dependent on (1) the appropriate and effective processing of a peptide from a protein source, (2) the stable binding of the peptide to the HLA molecule and (3) the recognition of this complex by the T cell receptor. In this thesis, we present work helping to better define such host-virus dynamics, examining aspects relating to each of the described steps. We examined two large patient cohorts, the first infected with HIV-1 and the second with HCV. We identified viral escape mutations and thus potential immune epitopes. Also, we examined the possible effects of HLA genotypes on the development of drug resistance mutations (HIV-1) and the success of antiviral therapy (HCV). To better understand the stable binding of peptides to HLA molecules, we evaluated the performance of diverse HLA class I prediction methods on large datasets, showing that all leading methods are capable of good to excellent performance. Finally, we developed the first algorithms, based on the interactions found in actual experimental structures, which allow for the prediction of interactions between residues in the T cell receptor\u27s CDR loops and residues in the HLA-peptide antigen. The algorithms had good performance under cross-validation.Wiederholt wurden viele Zusammenhänge menschlicher Infektionskrankheiten mit dem Human-Leukozyten-Antigen-System aufgezeigt, doch ein vollständiges Verständnis dieser Zusammenhänge fehlt. Adaptive Immunantworten mit CD4- und CD8-T-Lymphozyten sind abhängig von (1) einer angemessenen und effektiven Bearbeitung eines Peptids, (2) der stabilen Bindung des Peptids an das HLA-Molekül und (3) der Erkennung dieses HLA-Peptid-Komplexes durch den T-Zell-Rezeptor. In dieser Dissertation präsentieren wir Arbeiten, die helfen, diese Wirt-Virus-Dynamik besser zu definieren, indem wir Aspekte jedes dieser beschriebenen Schritte untersuchen. In zwei großen Patientengruppen (die erste mit HIV-1 und die zweite mit HCV infiziert) identifizierten wir virale Escape-Mutationen und damit potentielle Immun-Epitope. Wir untersuchten die möglichen Auswirkungen des HLA-Genotypes auf die Entwicklung von Resistenz-Mutationen (HIV-1) und den Erfolg einer antiviralen Therapie (HCV). Um die stabile Bindung von Peptiden an HLA-Moleküle besser zu verstehen, untersuchten wir die Leistung verschiedener HLA-Klasse I-Prognoseverfahren und zeigten, dass alle führenden Methoden gute bis sehr gute Ergebnisse liefern können. Abschließend haben wir die ersten Algorithmen entwickelt, die die Interaktionen zwischen den Aminosäuren der CDR-Schleifen des T-Zell-Rezeptors und Aminosäuren des HLA-Peptid-Komplexes vorhersagen. Diese Algorithmen zeigten gute Leistung unter Cross-Validierung

The Host Immune Response to HTLV-1 Infection

Human T-lymphotropic virus Type 1 (HTLV-1) is a retrovirus that persists lifelong in the host. In ~4% of infected people, HTLV-1 causes a chronic disabling neuroinflammatory disease known as HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP). The pathogenesis of HAM/TSP is unknown and treatment remains ineffective. In this study we aimed to identify patterns in frequencies of peripheral leukocyte populations and blood gene expression profiles of HTLV-1 carriers that suggest new hypotheses as to the mechanisms of HTLV-1 persistence and HAM/TSP pathology. Flow cytometric immunophenotyping of peripheral blood leukocytes revealed abnormal activation and maturation profiles of effector T cells but not antigen-presenting cells. High frequencies of circulating granzyme and perforin-rich CD8+ T cells were associated with an increased probability of HAM/TSP. However, the cytolytic capacity of these T cells is not known as although they accumulated cytolytic proteins, granzyme mRNA levels were down-regulated in patients with HAM/TSP. Furthermore, presence of HAM/TSP was associated with an expansion of CD56-negative NK cells, which are thought to have decreased cytolytic functions. Blood gene expression profiles identified perturbations of the p53 signalling pathway as a hallmark of HTLV-1 infection. In contrast, a subset of interferon (IFN)-stimulated genes was over-expressed in patients with HAM/TSP but not in asymptomatic HTLV-1 carriers or patients with the clinically similar disease multiple sclerosis. The IFN-inducible signature was present in all circulating leukocytes and its intensity correlated with the clinical severity of HAM/TSP. Leukocytes from patients with HAM/TSP were primed to respond strongly to stimulation with exogenous IFN. However, while type I IFN suppressed expression of the HTLV-1 structural protein Gag it failed to suppress the highly immunogenic viral transcriptional transactivator Tax. Based on our findings we hypothesise that impaired NK cell and T cell-mediated immune responses result in high HTLV-1 proviral loads but that the over-expression of a subset of IFN-stimulated genes contributes to the development of HAM/TSP

Novel urinary and serological markers of prostate cancer using proteomics techniques: an important tool for early cancer diagnosis and treatment monitoring

In Africa, Prostate cancer (PCa) is the most frequently diagnosed solid organ tumour in males and use of prostate specific antigen (PSA) is presently fraught with diagnostic inaccuracies. Not least, in a multi-ethnic society like South Africa, proteome differences between African, Caucasian and Mixed-Ancestry PCa patients are largely unknown. Hence, discovery and validation of affordable, non-invasive and reliable diagnostic biomarkers of PCa would expand the frontiers of PCa management. We have employed two high-throughput proteomics technologies to identify novel urine- and blood-based biomarkers for early diagnosis and treatment monitoring of prostate cancer in a South African cohort as well as elucidate proteome differences in patients from our heterogeneous cohort. We compared the urinary proteomes of PCa, Benign Prostatic Hyperplasia (BPH), disease controls comprising patients with other uropathies (DC) and normal healthy controls (NC) both by pooling and individual discovery shotgun proteomic assessment on a nano-Liquid chromatography (nLC) coupled Hybrid Quadrupole-Orbitrap Mass Spectrometer platform. In-silico verification of identified biomarkers was performed using the Human Protein Atlas (HPA) as well as SRMAtlas; and verified potential biomarkers were experimentally prevalidated using a targeted parallel reaction monitoring (PRM) proteomics approach. Further, we employed the CT100+ antigen microarray platform to assess the differential humoral antibody response of PCa, DC and BPH patients in our cohort to a panel of 123 tumour-associated cancer antigens. Candidate antigen biomarkers were analyzed for ethnic group variation in our cohort and potential cancer diagnostic and immunotherapeutic inferences were drawn. Using these approaches, we identified 5595 and 9991 non-redundant peptides from the pooled and individual experiments respectively. While nine proteins demonstrated ethnic trend, 37 and 73 proteins were differentially expressed by pooled and individual analysis respectively. All 32 verified biomarkers were prevalidated with parallel reaction monitoring. Good PRM signals for 12 top ranking biomarker was observed, including PSA and prostatic acid phosphatase. We also identified 41 potential diagnostic and immunotherapeutic antigen biomarkers. Proteogenomic functional pathway analyses of differentially expressed antigens showed similar enrichments of biologic processes. We identified herein novel urinary and blood-based potential diagnostic biomarkers and immunotherapeutic targets of PCa in a South African PCa Cohort using multiple proteomics approaches

Literature-based discovery of known and potential new mechanisms for relating the status of cholesterol to the progression of breast cancer

Breast cancer has been studied for a long period of time and from a variety of perspectives in order to understand its pathogeny. The pathogeny of breast cancer can be classified into two groups: hereditary and spontaneous. Although cancer in general is considered a genetic disease, spontaneous factors are responsible for most of the pathogeny of breast cancer. In other words, breast cancer is more likely to be caused and deteriorated by the dysfunction of a physical molecule than be caused by germline mutation directly. Interestingly, cholesterol, as one of those molecules, has been discovered to correlate with breast cancer risk. However, the mechanisms of how cholesterol helps breast cancer progression are not thoroughly understood. As a result, this study aims to study known and discover potential new mechanisms regarding to the correlation of cholesterol and breast cancer progression using literature review and literature-based discovery. The known mechanisms are further classified into four groups: cholesterol membrane content, transport of cholesterol, cholesterol metabolites, and other. The potential mechanisms, which are intended to provide potential new treatments, have been identified and checked for feasibility by an expert

Natural Products and Derivatives in Human Disorders

With this Special Issue, we have aimed to collect, publish and disseminate some of the most significant and recent contributions using both natural compounds present in living organisms and some of their chemical derivatives aimed at reducing the risk of developing inflammatory and oxidative diseases such as cancer, metabolic syndrome and other human disorders related to the bone, vascular and ocular systems. The publication of articles on the anticancer and antioxidant activity of natural compounds and their derivatives is particularly encouraged.Natural products, many of them phytochemicals, are bioactive compounds. They have traditionally been used by different cultures for the prevention and treatment of various human diseases. Subsequently, their chemical derivatives are being used to enhance their bioactivities. antiproliferative, antitumour, growth stimulating, as well as cardio- and neuroprotective activities, with particular attention being paid to the study of their antitumour capacity, through potential modulation of cancer initiation and growth, cell differentiation, apoptosis and autophagy, angiogenesis and metastatic dissemination.Aucuba japonica; aucubin; cornea; dry eye; tear; chondrosarcoma cells; osteoarthritis; Ryupunghwan (natural product mixture); IL-1β; isomucronulatol 7-O-β-d-glucoside; ecliptasaponin A; cardiomyocytes (H9C2 cells); angiotensin II; hypertension; No-ap (natural product mixture); reactive oxygen species; roseoside; icariside E4; acetylcholinesterase; butyrylcholinesterase; triterpenoids; Teucrium mascatense; natural plant products; anticancer activity; breast and cervical cancer; apoptosis; caspases; aberrant crypt foci; colon cancer; mucin depleted foci; maslinic acid; dimethylhydrazine; saikosaponin d; neuropilin-1; HepG2; metabolomics; metabolite deregulation score; n/

Exploring genetic interactions with G-quadruplex structures

G-quadruplexes are non-canonical nucleic acid secondary structures of increasing biological and medicinal interest due to their proposed physiological functions in transcription, replication, translation and telomere biology. Aberrant G4 formation and stabilisation have been linked to genome instability, cancer and other diseases. However, the specific genes and pathways involved are largely unknown, and the work within this thesis aims to investigate this. Stabilisation of G4s by small molecules can perturb G4-mediated processes and initial studies suggest that this approach has chemotherapeutic potential. I therefore also aimed to identify cell genotypes sensitive to G4-ligand treatment that may offer further therapeutic opportunities. To address these aims, I present the first unbiased genome-wide genetic screen in cells where genes were silenced via short-hairpin RNAs (shRNAs) whilst being treated with either PDS or PhenDC3, two independent G4-stabilising small molecules. I explored gene deficiencies that enhance cell death (sensitisation) or provide a growth advantage (resistance) in the presence of these G4-ligands. Additionally, I present a validation screen, comprising hits uncovered via genome-wide screening, and also the use of this in another cell line of different origin. Sensitivities were enriched in DNA replication, cell cycle, DNA damage repair, splicing and ubiquitin-mediated proteolysis proteins and pathways. Ultimately, I uncovered four synthetic lethalities BRCA1, TOP1, DDX42, GAR1, independent of cell line and ligand. These were validated with three G4-stabilising ligands (PDS, PhenDC3 and CX-5461) using an independent siRNA approach. The latter siRNA methodology was used to screen 12 PDS derivatives with improved medicinal chemistry properties and ultimately identified SA-100-128, as a lead compound. The mechanism behind synthetic lethality with G4-stabilising ligands was explored further for DDX42, which I show has in vitro affinity for both RNA- and DNA-G4s and may represent a previously unknown G4-helicase. Also within this thesis, gene deficiencies that provided a growth advantage to PDS and/or PhenDC3 as uncovered by genome-wide and focused screening were explored. These showed enrichment in transcription, chromatin and lysosome-associated genes. The resistance phenotype of three gene deficiencies, TAF1, DDX39A and ZNF217 was further supported by additional siRNA experiments. Overall, I satisfied the primary aims and established many novel synthetic lethal and resistance interactions that may represent new therapeutic possibilities. Additionally, the results expand our knowledge of G4-biology by identifying genes, functions and subcellular locations previously not known to involve or regulate G4s.funded by CRU