von Hippel Lindau binding protein 1-mediated degradation of integrase affects HIV-1 gene expression at a postintegration step

HIV-1 integrase, the viral enzyme responsible for provirus integration into the host genome, can be actively degraded by the ubiquitin-proteasome pathway. Here, we identify von Hippel-Lindau binding protein 1(VBP1), a subunit of the prefoldin chaperone, as an integrase cellular binding protein that bridges interaction between integrase and the cullin2 (Cul2)-based von Hippel-Lindau (VHL) ubiquitin ligase. We demonstrate that VBP1 and Cul2/VHL are required for proper HIV-1 expression at a step between integrase-dependent proviral integration into the host genome and transcription of viral genes. Using both an siRNA approach and Cul2/VHL mutant cells, we show that VBP1 and the Cul2/VHL ligase cooperate in the efficient polyubiquitylation of integrase and its subsequent proteasome-mediated degradation. Results presented here support a role for integrase degradation by the prefoldin-VHL-proteasome pathway in the integration-transcription transition of the viral replication cycle.

Insight into determinants of substrate binding and transport in a multidrug efflux protein

Multidrug resistance arising from the activity of integral membrane transporter proteins presents a global public health threat. In bacteria such as Escherichia coli, transporter proteins belonging to the major facilitator superfamily make a considerable contribution to multidrug resistance by catalysing efflux of myriad structurally and chemically different antimicrobial compounds. Despite their clinical relevance, questions pertaining to mechanistic details of how these promiscuous proteins function remain outstanding, and the role(s) played by individual amino acid residues in recognition, binding and subsequent transport of different antimicrobial substrates by multidrug efflux members of the major facilitator superfamily requires illumination. Using in silico homology modelling, molecular docking and mutagenesis studies in combination with substrate binding and transport assays, we identified several amino acid residues that play important roles in antimicrobial substrate recognition, binding and transport by Escherichia coli MdtM, a representative multidrug efflux protein of the major facilitator superfamily. Furthermore, our studies suggested that 'aromatic clamps' formed by tyrosine and phenylalanine residues located within the substrate binding pocket of MdtM may be important for antimicrobial substrate recognition and transport by the protein. Such 'clamps' may be a structurally and functionally important feature of all major facilitator multidrug efflux proteins.

Serum Fatty Acid Binding Protein 4 (FABP4) Predicts Pre-eclampsia in Women with Type 1 Diabetes

Objective: To examine the association between fatty acid binding protein 4 (FABP4) and pre-eclampsia risk in women with type 1 diabetes.
Reesearch Design and Methods: Serum FABP4 was measured in 710 women from the Diabetes and Pre-eclampsia Intervention Trial (DAPIT) in early pregnancy and in the second trimester (median 14 and 26 weeks gestation, respectively).
Results: FABP4 was significantly elevated in early pregnancy (geometric mean 15.8 ng/mL [interquartile range 11.6–21.4] vs. 12.7 ng/mL [interquartile range 9.6–17]; P < 0.001) and the second trimester (18.8 ng/mL [interquartile range 13.6–25.8] vs. 14.6 ng/mL [interquartile range 10.8–19.7]; P < 0.001) in women in whom pre-eclampsia later developed. Elevated second-trimester FABP4 level was independently associated with pre-eclampsia (odds ratio 2.87 [95% CI 1.24, 6.68], P = 0.03). The addition of FABP4 to established risk factors significantly improved net reclassification improvement at both time points and integrated discrimination improvement in the second trimester.
Conclusions: Increased second-trimester FABP4 independently predicted pre-eclampsia and significantly improved reclassification and discrimination. FABP4 shows potential as a novel biomarker for pre-eclampsia prediction in women with type 1 diabetes.

Insulin-Like Growth Factor-I (IGF-1), IGF-Binding Protein-3 (IGFBP-3) and mammographic features

Introduction. The IGF system has recently been shown to play an important role in the regulation of breast tumor cell proliferation. However, also breast density is currently considered as the strongest breast cancer risk factor. It is not yet clear whether these factors are interrelated and if and how they are influenced by menopausal status. The purpose of this study was to examine the possible effects of IGF-1 and IGFBP-3 and IGF-1/IGFBP-3 molar ratio on mammographic density stratified by menopausal status. Patients and methods. A group of 341 Italian women were interviewed to collect the following data: family history of breast cancer, reproductive and menstrual factors, breast biopsies, previous administration of hormonal contraceptive therapy, hormone replacement therapy (HRT) in menopause and lifestyle information. A blood sample was drawn for determination of IGF-1, IGFBP-3 levels. IGF-1/ IGFBP-3 molar ratio was then calculated. On the basis of recent mammograms the women were divided into two groups: dense breast (DB) and non-dense breast (NDB). Student’s t-test was employed to assess the association between breast density and plasma level of IGF-1, IGFBP-3 and molar ratio. To assess if this relationship was similar in subgroups of pre- and postmenopausal women, the study population was stratified by menopausal status and Student’s t-test was performed. Finally, multivariate analysis was employed to evaluate if there were confounding factors that might influence the relationship between growth factors and breast density. Results. The analysis of the relationship between mammographic density and plasma level of IGF-1, IGFBP-3 and IGF-1/ IGFBP-3 molar ratio showed that IGF-1 levels and molar ratio varied in the two groups resulting in higher mean values in the DB group (IGF-1: 109.6 versus 96.6 ng/ml; p= 0.001 and molar ratio 29.4 versus 25.5 ng/ml; p= 0.001) whereas IGFBP-3 showed similar values in both groups (DB and NDB). Analysis of plasma level of IGF-1, IGFBP-3 and IGF-1/IGFBP-3 molar ratio compared to breast density after stratification of the study population by menopausal status (premenopausal and postmenopausal) showed that there was no association between the plasma of growth factors and breast density, neither in premenopausal nor in postmenopausal patients. Multivariate analysis showed that only nulliparity, premenopausal status and body mass index (BMI) are determinants of breast density. Conclusions. Our study provides a strong evidence of a crude association between breast density and plasma levels of IGF-1 and molar ratio. On the basis of our results, it is reasonable to assume that the role of IGF-1 and molar ratio in the pathogenesis of breast cancer might be mediated through mammographic density. IGF-1 and molar ratio might thus increase the risk of cancer by increasing mammographic density.

An investigation of the molecular pharmacology of G protein-coupled receptor 35

G protein-coupled receptors (GPCRs) are seven-pass integral membrane proteins that act as transducers of extracellular signals across the lipid bilayer. Their location and involvement in basic and pathological physiological processes has secured their role as key targets for pharmaceutical intervention. GPCRs are targeted by many of the best-selling drugs on the market and there are a substantial number of GPCRs that are yet to be characterised; these could offer interest for therapeutic targeting. GPR35 is one such receptor that, as a result of gene knockout and genome wide association studies, has attracted interest through its association with cardiovascular and gastrointestinal disease. Elucidation of the basic physiological function of GPR35 has, however, been difficult due a paucity of potent and selective ligands in addition to a lack of consensus on the endogenous ligand. Herein, a focussed drug discovery effort was carried out to identify agonists of GPR35. Various in vitro cellular assays were employed in conjunction with N- or C-terminally manipulated forms of the receptor to investigate GPR35’s signalling profile and to provide an assay format suitable for the characterisation of newly identified ligands. Although GPR35 associates with both Gαi/o and Gα13 families of small heterotrimeric G proteins, the G protein-independent β-arrestin-2 recruitment format was found to be the most suited to drug screening efforts. Small molecule compound screening, carried out in conjunction with the Medical Research Council Technology, identified compound 1 as the most potent ligand of human GPR35 reported at that time. However, the lower efficacy and potency of compound 1 at the rodent species orthologues of GPR35 prevented its use in in vivo studies. A subsequent effort, carried out with Novartis, focused on mast cell stabilisers as putative agonists of GPR35, revealed lodoxamide and bufrolin as highly potent agonists that activated human and rat GPR35 with equal potency. This finding offered–for the first time–the opportunity to employ the same GPR35 ligand between species at a similar concentration, an important factor to consider when translating rodent in vivo functional studies to those in man. Additionally, using molecular modelling and site directed mutagenesis studies, these newly identified compounds were used to aid characterisation of the ligand binding pockets of human and rat GPR35 to reveal the molecular basis of species selectivity at this receptor. In summary, this research effort presents GPR35 tool compounds that can now be used to dissect the basic biology of GPR35 and investigate its contribution to disease.

Complementation of the embryo-lethal T-DNA insertion mutant of AUXIN-BINDING-PROTEIN 1 (ABP1) with abp1 point mutated versions reveals crosstalk of ABP1 and phytochromes

The function of the extracytoplasmic AUXIN-BINDING-PROTEIN1 (ABP1) is largely enigmatic. We complemented a homozygous T-DNA insertion null mutant of ABP1 in Arabidopsis thaliana Wassilewskia with three mutated and one wild-type (wt) ABP1 cDNA, all tagged C-terminally with a strepII-FLAG tag upstream the KDEL signal. Based on in silico modelling, the abp1 mutants were predicted to have altered geometries of the auxin binding pocket and calculated auxin binding energies lower than the wt. Phenotypes linked to auxin transport were compromised in these three complemented abp1 mutants. Red light effects, such as elongation of hypocotyls in constant red (R) and far-red (FR) light, in white light supplemented by FR light simulating shade, and inhibition of gravitropism by R or FR, were all compromised in the complemented lines. Using auxin-or light-induced expression of marker genes, we showed that auxininduced expression was delayed already after 10 min, and light-induced expression within 60 min, even though TIR1/AFB or phyB are thought to act as receptors relevant for gene expression regulation. The expression of marker genes in seedlings responding to both auxin and shade showed that for both stimuli regulation of marker gene expression was altered after 10-20 min in the wild type and phyB mutant. The rapidity of expression responses provides a framework for the mechanics of functional interaction of ABP1 and phyB to trigger interwoven signalling pathways.

Applications of functional nucleic acids in imaging, sensing and drug delivery and investigations of DNAzyme-metal interactions

Functional nucleic acids (FNA), including nucleic acids catalysts (ribozymes and DNAzymes) and ligands (aptamers), have been discovered in nature or isolated in a laboratory through a process called in vitro selection. They are nucleic acids with functions similar to protein enzymes or antibodies. They have been developed into sensors with high sensitivity and selectivity; it is realized by converting the reaction catalyzed by a DNAzyme/ribozyme or the binding event of an aptamer to a fluorescent, colorimetric or electrochemical signal. While a number of studies have been reported for in vitro sensing using DNAzymes or aptamers, there are few reports on in vivo sensing or imaging. MRI is a non-invasive imaging technique; smart MRI contrast agents were synthesized for molecular imaging purposes. However, their rational design remains a challenge due to the difficulty to predict molecular interactions. Chapter 2 focuses on rational design of smart T1-weighted MRI contrast agents with high specificity based on DNAzymes and aptamers. It was realized by changing the molecular weight of the gadolinium conjugated DNA strand with the analytes, which lead to analyte-specific water proton relaxation responses and contrast changes on an MRI image. The designs are general; the high selectivity of FNA was retained. Most FNA-based fluorescent sensors require covalent labeling of fluorophore/quencher to FNAs, which incurrs extra expenses and could interfere the function of FNAs. Chapter 3 describes a new sensor design avoiding the covalent labeling of fluorophore and quencher. The fluorescence of malachite green (MG) was regulated by the presence of adenosine. Conjugate of aptamers of MG and adenosine and a bridge strand were annealed in a solution containing MG. The MG aptamer did not bind MG because of its hybridization to the bridge strand, resulting in low fluorescence signal of MG. The hybridization was weakened in the presence of adenosine, leading to the binding of MG to its aptamer and a fluorescence increase. The sensor has comparable detection limit (20 micromolar) and specificity to its labeled derivatives. Enzymatic activity of most DNAzymes requires metal cations. The research on the metal-DNAzyme interaction is of interest and challenge to scientists because of the lack of structural information. Chapters 4 presents the research on the characterization of the interaction between a Cu2+-dependent DNAzyme and Cu2+. Electron paramagnetic resonance (EPR) and UV-Vis spectroscopy were used to probe the binding of Cu2+ to the DNAzyme; circular dichroism was used to probe the conformational change of the DNAzyme induced by Cu2+. It was proposed that the conformational change by the Cu2+ binding is important for the activity of the DNAzyme. Chapter 5 reports the dependence of the activity of 8-17 DNAzyme on the presence of both Pb2+ and other metal cations including Zn2+, Cd2+ and Mg2+. It was discovered that presence of those metal cations can be cooperative or inhibitive to 8-17 activity. It is hypothesized that the 8-17 DNAzyme had multiple binding sites for metal cations based on the results. Cisplatin is effective killing tumor cells, but with significant side effects, which can be minimized by its targeted delivery. Chapter 6 focuses on the effort to functionalize liposomes encapsulating cisplatin by an aptamer that selectively bind nucleolin, an overexpressed protein by breast cancer cells. The study proved the selective cytotoxicity to breast cancer cells of the aptamer-functionalized liposome.

Preparation and In Vitro Release of Drug-Loaded Microparticles for Oral Delivery Using Wholegrain Sorghum Kafirin Protein

Kafirin microparticles have been proposed as an oral nutraceutical and drug delivery system. This study investigates microparticles formed with kafirin extracted from white and raw versus cooked red sorghum grains as an oral delivery system. Targeted delivery to the colon would be beneficial for medication such as prednisolone, which is used in the management of inflammatory bowel disease. Therefore, prednisolone was loaded into microparticles of kafirin from the different sources using phase separation. Differences were observed in the protein content, in vitro protein digestibility, and protein electrophoretic profile of the various sources of sorghum grains, kafirin extracts, and kafirin microparticles. For all of the formulations, the majority of the loaded prednisolone was not released in in vitro conditions simulating the upper gastrointestinal tract, indicating that most of the encapsulated drug could reach the target area of the lower gastrointestinal tract. This suggests that these kafirin microparticles may have potential as a colon-targeted nutraceutical and drug delivery system.

Improving drug discovery using hybrid softcomputing methods

Virtual screening (VS) methods can considerably aid clinical research, predicting how ligands interact with drug targets. Most VS methods suppose a unique binding site for the target, but it has been demonstrated that diverse ligands interact with unrelated parts of the target and many VS methods do not take into account this relevant fact. This problem is circumvented by a novel VS methodology named BINDSURF that scans the whole protein surface in order to find new hotspots, where ligands might potentially interact with, and which is implemented in last generation massively parallel GPU hardware, allowing fast processing of large ligand databases. BINDSURF can thus be used in drug discovery, drug design, drug repurposing and therefore helps considerably in clinical research. However, the accuracy of most VS methods and concretely BINDSURF is constrained by limitations in the scoring function that describes biomolecular interactions, and even nowadays these uncertainties are not completely understood. In order to improve accuracy of the scoring functions used in BINDSURF we propose a hybrid novel approach where neural networks (NNET) and support vector machines (SVM) methods are trained with databases of known active (drugs) and inactive compounds, being this information exploited afterwards to improve BINDSURF VS predictions.

Improving drug discovery using a neural networks based parallel scoring function

Virtual Screening (VS) methods can considerably aid clinical research, predicting how ligands interact with drug targets. Most VS methods suppose a unique binding site for the target, but it has been demonstrated that diverse ligands interact with unrelated parts of the target and many VS methods do not take into account this relevant fact. This problem is circumvented by a novel VS methodology named BINDSURF that scans the whole protein surface to find new hotspots, where ligands might potentially interact with, and which is implemented in massively parallel Graphics Processing Units, allowing fast processing of large ligand databases. BINDSURF can thus be used in drug discovery, drug design, drug repurposing and therefore helps considerably in clinical research. However, the accuracy of most VS methods is constrained by limitations in the scoring function that describes biomolecular interactions, and even nowadays these uncertainties are not completely understood. In order to solve this problem, we propose a novel approach where neural networks are trained with databases of known active (drugs) and inactive compounds, and later used to improve VS predictions.

PROTEIN-TRIGGERED SUSTAINED DRUG RELEASE CONTROLLED BY APTAMERS BOUND TO OLIGOMER-CROSSLINKED ALGINATE

Sustained drug release systems provide many advantages over traditional delivery methods such as extending the time in which the drug is found to be within an effective concentration within the therapeutic window, which decreases the frequency of administration of the drug, and increases patient compliance. Research using polyacrylamide crosslinked by oligomers containing an aptamer sequence, has demonstrated a pulsatile release over 50 minutes triggered by a 2 mM target adenosine concentration. This thesis aims to build off this concept by designing a system that delivers in a sustained manner when triggered by micromolar target concentrations reflective of disease in vivo, using macromolecular targets. For example, the disease wet age related macular degeneration (wet AMD) is associated with increased concentrations of the protein vascular endothelial growth factor (VEGF-A) – a macromolecule. Patients with wet AMD would benefit from the implantation of devices or microspheres that release drugs in a sustained manner in response to local VEGF concentrations. In this thesis, we hypothesize that the protein lysozyme, used to demonstrate proof-of-concept, could trigger the increased release of drugs from oligomer-crosslinked alginate. The objectives are to (i) demonstrate sustained release from alginate, (ii) design oligomer crosslinked alginate that degrades in response to lysozyme, and then (iii) use these systems to control the release of FITC-dextran with and without lysozyme. A series of control experiments and analyses were used to optimize the crosslinking of alginate by annealed oligomers. The cumulative release of FITC-dextran (MW 20,000) from oligomer crosslinked alginate increased by 3.4 μg when lysozyme (3 μM) was introduced at 48 hours, as opposed to controls which released only 0.2 μg. FITC-loaded alginate microspheres coated by oligomer-crosslinked alginate released 15% more FITC-dextran over 120 hours when placed into 3 μM of lysozyme than without lysozyme. Controls of alginate crosslinked with PEG or control oligomers (without a lysozyme aptamer sequence) had no changes in release with lysozyme. The incorporation of a lysozyme aptamer onto oligomers used to crosslink alginate disks or alginate coatings on microspheres resulted in different diffusion and release of FITC-dextran into PBS with or without lysozyme. This approach could be adapted for the delivery of drugs to diseases with specific protein profiles such as wet AMD.

Inhibition of nonsense-mediated mRNA decay by the cytoplasmic poly(A)-binding protein

The expression of a gene from transcription of the DNA into pre-messenger RNA (pre-mRNA) over translation of messenger RNA (mRNA) into protein is constantly monitored for errors. This quality control is necessary to guarantee successful gene expression. One quality control mechanism important to this thesis is called nonsense-mediated mRNA decay (NMD). NMD is a cellular process that eliminates mRNA transcripts harboring premature translation termination codons (PTCs). Furthermore, NMD is known to regulate certain transcripts with long 3′ UTRs. However, some mRNA transcripts are known to evade NMD. The mechanism of NMD activation has been subjected to many studies whereas NMD evasion or suppression still remains rather elusive. It has previously been shown that the cytoplasmic poly(A)-binding protein (PABPC1) is able to suppress NMD of certain transcripts. In this study I show that PABPC1 is able to suppress NMD of a long 3′ UTR-carrying reporter when tethered immediately downstream of the termination codon. I further am able to show the importance of the interaction between PABPC1 and eIF4G for NMD suppression, whereas the interaction between PABPC1 and eRF3a seems dispensable. These results indicate an involvement of efficient translation termination and potentially ribosome recycling in NMD suppression. I am able to show that if PABPC1 is too far removed from the terminating ribosome NMD is activated. After showing the importance of PABPC1 recruitment directly downstream of a terminating ribosome in NMD suppression, I am further able to demonstrate several different methods by which PABPC1 can be recruited. Fold-back of the poly(A)-tail mediated by two interacting proteins on opposite ends of a 3′ UTR manages to bring PABPC1 bound to the poly(A)-tail into close proximity of the terminating ribosome and therefore suppress NMD. Furthermore, small PAM2 peptides that are known to interact with the MLLE domain of PABPC1 are able to strongly suppress NMD initiated by either a long 3′ UTR or an EJC. I am also able to show the NMD antagonizing power of recruited PABPC1 for the known endogenous NMD target β-globin PTC39, which is responsible for the disease β-thalassemia. This shows the potential medical implications and application of suppressing NMD by recruiting PABPC1 into close proximity of a terminating ribosome.

Machine learning tools for protein annotation: the cases of transmembrane β-barrel and myristoylated proteins

Biology is now a “Big Data Science” thanks to technological advancements allowing the characterization of the whole macromolecular content of a cell or a collection of cells. This opens interesting perspectives, but only a small portion of this data may be experimentally characterized. From this derives the demand of accurate and efficient computational tools for automatic annotation of biological molecules. This is even more true when dealing with membrane proteins, on which my research project is focused leading to the development of two machine learning-based methods: BetAware-Deep and SVMyr. BetAware-Deep is a tool for the detection and topology prediction of transmembrane beta-barrel proteins found in Gram-negative bacteria. These proteins are involved in many biological processes and primary candidates as drug targets. BetAware-Deep exploits the combination of a deep learning framework (bidirectional long short-term memory) and a probabilistic graphical model (grammatical-restrained hidden conditional random field). Moreover, it introduced a modified formulation of the hydrophobic moment, designed to include the evolutionary information. BetAware-Deep outperformed all the available methods in topology prediction and reported high scores in the detection task. Glycine myristoylation in Eukaryotes is the binding of a myristic acid on an N-terminal glycine. SVMyr is a fast method based on support vector machines designed to predict this modification in dataset of proteomic scale. It uses as input octapeptides and exploits computational scores derived from experimental examples and mean physicochemical features. SVMyr outperformed all the available methods for co-translational myristoylation prediction. In addition, it allows (as a unique feature) the prediction of post-translational myristoylation. Both the tools here described are designed having in mind best practices for the development of machine learning-based tools outlined by the bioinformatics community. Moreover, they are made available via user-friendly web servers. All this make them valuable tools for filling the gap between sequential and annotated data.

A multidisciplinary approach to the study of protein dynamics and signal transmission

Allostery is a phenomenon of fundamental importance in biology, allowing regulation of function and dynamic adaptability of enzymes and proteins. Despite the allosteric effect was first observed more than a century ago allostery remains a biophysical enigma, defined as the “second secret of life”. The challenge is mainly associated to the rather complex nature of the allosteric mechanisms, which manifests itself as the alteration of the biological function of a protein/enzyme (e.g. ligand/substrate binding at the active site) by binding of “other object” (“allos stereos” in Greek) at a site distant (> 1 nanometer) from the active site, namely the effector site. Thus, at the heart of allostery there is signal propagation from the effector to the active site through a dense protein matrix, with a fundamental challenge being represented by the elucidation of the physico-chemical interactions between amino acid residues allowing communicatio n between the two binding sites, i.e. the “allosteric pathways”. Here, we propose a multidisciplinary approach based on a combination of computational chemistry, involving molecular dynamics simulations of protein motions, (bio)physical analysis of allosteric systems, including multiple sequence alignments of known allosteric systems, and mathematical tools based on graph theory and machine learning that can greatly help understanding the complexity of dynamical interactions involved in the different allosteric systems. The project aims at developing robust and fast tools to identify unknown allosteric pathways. The characterization and predictions of such allosteric spots could elucidate and fully exploit the power of allosteric modulation in enzymes and DNA-protein complexes, with great potential applications in enzyme engineering and drug discovery.