Metodi computazionali per l'annotazione di genomi e proteomi

Il progresso tecnologico nel campo della biologia molecolare, pone la comunità scientifica di fronte all’esigenza di dare un’interpretazione all’enormità di sequenze biologiche che a mano a mano vanno a costituire le banche dati, siano esse proteine o acidi nucleici. In questo contesto la bioinformatica gioca un ruolo di primaria importanza. Un nuovo livello di possibilità conoscitive è stato introdotto con le tecnologie di Next Generation Sequencing (NGS), per mezzo delle quali è possibile ottenere interi genomi o trascrittomi in poco tempo e con bassi costi. Tra le applicazioni del NGS più rilevanti ci sono senza dubbio quelle oncologiche che prevedono la caratterizzazione genomica di tessuti tumorali e lo sviluppo di nuovi approcci diagnostici e terapeutici per il trattamento del cancro. Con l’analisi NGS è possibile individuare il set completo di variazioni che esistono nel genoma tumorale come varianti a singolo nucleotide, riarrangiamenti cromosomici, inserzioni e delezioni. Va però sottolineato che le variazioni trovate nei geni vanno in ultima battuta osservate dal punto di vista degli effetti a livello delle proteine in quanto esse sono le responsabili più dirette dei fenotipi alterati riscontrabili nella cellula tumorale. L’expertise bioinformatica va quindi collocata sia a livello dell’analisi del dato prodotto per mezzo di NGS ma anche nelle fasi successive ove è necessario effettuare l’annotazione dei geni contenuti nel genoma sequenziato e delle relative strutture proteiche che da esso sono espresse, o, come nel caso dello studio mutazionale, la valutazione dell’effetto della variazione genomica. È in questo contesto che si colloca il lavoro presentato: da un lato lo sviluppo di metodologie computazionali per l’annotazione di sequenze proteiche e dall’altro la messa a punto di una pipeline di analisi di dati prodotti con tecnologie NGS in applicazioni oncologiche avente come scopo finale quello della individuazione e caratterizzazione delle mutazioni genetiche tumorali a livello proteico.

Transcriptional regulation of human mu-opioid receptor gene: functional characterization of activating and inhibitory transcription factors

The organization of the nervous and immune systems is characterized by obvious differences and striking parallels. Both systems need to relay information across very short and very long distances. The nervous system communicates over both long and short ranges primarily by means of more or less hardwired intercellular connections, consisting of axons, dendrites, and synapses. Longrange communication in the immune system occurs mainly via the ordered and guided migration of immune cells and systemically acting soluble factors such as antibodies, cytokines, and chemokines. Its short-range communication either is mediated by locally acting soluble factors or transpires during direct cell–cell contact across specialized areas called “immunological synapses” (Kirschensteiner et al., 2003). These parallels in intercellular communication are complemented by a complex array of factors that induce cell growth and differentiation: these factors in the immune system are called cytokines; in the nervous system, they are called neurotrophic factors. Neither the cytokines nor the neurotrophic factors appear to be completely exclusive to either system (Neumann et al., 2002). In particular, mounting evidence indicates that some of the most potent members of the neurotrophin family, for example, nerve growth factor (NGF) and brainderived neurotrophic factor (BDNF), act on or are produced by immune cells (Kerschensteiner et al., 1999) There are, however, other neurotrophic factors, for example the insulin-like growth factor-1 (IGF-1), that can behave similarly (Kermer et al., 2000). These factors may allow the two systems to “cross-talk” and eventually may provide a molecular explanation for the reports that inflammation after central nervous system (CNS) injury has beneficial effects (Moalem et al., 1999). In order to shed some more light on such a cross-talk, therefore, transcription factors modulating mu-opioid receptor (MOPr) expression in neurons and immune cells are here investigated. More precisely, I focused my attention on IGF-I modulation of MOPr in neurons and T-cell receptor induction of MOPr expression in T-lymphocytes. Three different opioid receptors [mu (MOPr), delta (DOPr), and kappa (KOPr)] belonging to the G-protein coupled receptor super-family have been cloned. They are activated by structurallyrelated exogenous opioids or endogenous opioid peptides, and contribute to the regulation of several functions including pain transmission, respiration, cardiac and gastrointestinal functions, and immune response (Zollner and Stein 2007). MOPr is expressed mainly in the central nervous system where it regulates morphine-induced analgesia, tolerance and dependence (Mayer and Hollt 2006). Recently, induction of MOPr expression in different immune cells induced by cytokines has been reported (Kraus et al., 2001; Kraus et al., 2003). The human mu-opioid receptor gene (OPRM1) promoter is of the TATA-less type and has clusters of potential binding sites for different transcription factors (Law et al. 2004). Several studies, primarily focused on the upstream region of the OPRM1 promoter, have investigated transcriptional regulation of MOPr expression. Presently, however, it is still not completely clear how positive and negative transcription regulators cooperatively coordinate cellor tissue-specific transcription of the OPRM1 gene, and how specific growth factors influence its expression. IGF-I and its receptors are widely distributed throughout the nervous system during development, and their involvement in neurogenesis has been extensively investigated (Arsenijevic et al. 1998; van Golen and Feldman 2000). As previously mentioned, such neurotrophic factors can be also produced and/or act on immune cells (Kerschenseteiner et al., 2003). Most of the physiologic effects of IGF-I are mediated by the type I IGF surface receptor which, after ligand binding-induced autophosphorylation, associates with specific adaptor proteins and activates different second messengers (Bondy and Cheng 2004). These include: phosphatidylinositol 3-kinase, mitogen-activated protein kinase (Vincent and Feldman 2002; Di Toro et al. 2005) and members of the Janus kinase (JAK)/STAT3 signalling pathway (Zong et al. 2000; Yadav et al. 2005). REST plays a complex role in neuronal cells by differentially repressing target gene expression (Lunyak et al. 2004; Coulson 2005; Ballas and Mandel 2005). REST expression decreases during neurogenesis, but has been detected in the adult rat brain (Palm et al. 1998) and is up-regulated in response to global ischemia (Calderone et al. 2003) and induction of epilepsy (Spencer et al. 2006). Thus, the REST concentration seems to influence its function and the expression of neuronal genes, and may have different effects in embryonic and differentiated neurons (Su et al. 2004; Sun et al. 2005). In a previous study, REST was elevated during the early stages of neural induction by IGF-I in neuroblastoma cells. REST may contribute to the down-regulation of genes not yet required by the differentiation program, but its expression decreases after five days of treatment to allow for the acquisition of neural phenotypes. Di Toro et al. proposed a model in which the extent of neurite outgrowth in differentiating neuroblastoma cells was affected by the disappearance of REST (Di Toro et al. 2005). The human mu-opioid receptor gene (OPRM1) promoter contains a DNA sequence binding the repressor element 1 silencing transcription factor (REST) that is implicated in transcriptional repression. Therefore, in the fist part of this thesis, I investigated whether insulin-like growth factor I (IGF-I), which affects various aspects of neuronal induction and maturation, regulates OPRM1 transcription in neuronal cells in the context of the potential influence of REST. A series of OPRM1-luciferase promoter/reporter constructs were transfected into two neuronal cell models, neuroblastoma-derived SH-SY5Y cells and PC12 cells. In the former, endogenous levels of human mu-opioid receptor (hMOPr) mRNA were evaluated by real-time PCR. IGF-I upregulated OPRM1 transcription in: PC12 cells lacking REST, in SH-SY5Y cells transfected with constructs deficient in the REST DNA binding element, or when REST was down-regulated in retinoic acid-differentiated cells. IGF-I activates the signal transducer and activator of transcription-3 (STAT3) signaling pathway and this transcription factor, binding to the STAT1/3 DNA element located in the promoter, increases OPRM1 transcription. T-cell receptor (TCR) recognizes peptide antigens displayed in the context of the major histocompatibility complex (MHC) and gives rise to a potent as well as branched intracellular signalling that convert naïve T-cells in mature effectors, thus significantly contributing to the genesis of a specific immune response. In the second part of my work I exposed wild type Jurkat CD4+ T-cells to a mixture of CD3 and CD28 antigens in order to fully activate TCR and study whether its signalling influence OPRM1 expression. Results were that TCR engagement determined a significant induction of OPRM1 expression through the activation of transcription factors AP-1, NF-kB and NFAT. Eventually, I investigated MOPr turnover once it has been expressed on T-cells outer membrane. It turned out that DAMGO induced MOPr internalisation and recycling, whereas morphine did not. Overall, from the data collected in this thesis we can conclude that that a reduction in REST is a critical switch enabling IGF-I to up-regulate human MOPr, helping these findings clarify how human MOPr expression is regulated in neuronal cells, and that TCR engagement up-regulates OPRM1 transcription in T-cells. My results that neurotrophic factors a and TCR engagement, as well as it is reported for cytokines, seem to up-regulate OPRM1 in both neurons and immune cells suggest an important role for MOPr as a molecular bridge between neurons and immune cells; therefore, MOPr could play a key role in the cross-talk between immune system and nervous system and in particular in the balance between pro-inflammatory and pro-nociceptive stimuli and analgesic and neuroprotective effects.

Fault detection in rotating machines by vibration signal processing techniques

Machines with moving parts give rise to vibrations and consequently noise. The setting up and the status of each machine yield to a peculiar vibration signature. Therefore, a change in the vibration signature, due to a change in the machine state, can be used to detect incipient defects before they become critical. This is the goal of condition monitoring, in which the informations obtained from a machine signature are used in order to detect faults at an early stage. There are a large number of signal processing techniques that can be used in order to extract interesting information from a measured vibration signal. This study seeks to detect rotating machine defects using a range of techniques including synchronous time averaging, Hilbert transform-based demodulation, continuous wavelet transform, Wigner-Ville distribution and spectral correlation density function. The detection and the diagnostic capability of these techniques are discussed and compared on the basis of experimental results concerning gear tooth faults, i.e. fatigue crack at the tooth root and tooth spalls of different sizes, as well as assembly faults in diesel engine. Moreover, the sensitivity to fault severity is assessed by the application of these signal processing techniques to gear tooth faults of different sizes.

Structure determination of proteins and peptides in solution: simulation, chirality and NMR studies

The study of protein fold is a central problem in life science, leading in the last years to several attempts for improving our knowledge of the protein structures. In this thesis this challenging problem is tackled by means of molecular dynamics, chirality and NMR studies. In the last decades, many algorithms were designed for the protein secondary structure assignment, which reveals the local protein shape adopted by segments of amino acids. In this regard, the use of local chirality for the protein secondary structure assignment was demonstreted, trying to correlate as well the propensity of a given amino acid for a particular secondary structure. The protein fold can be studied also by Nuclear Magnetic Resonance (NMR) investigations, finding the average structure adopted from a protein. In this context, the effect of Residual Dipolar Couplings (RDCs) in the structure refinement was shown, revealing a strong improvement of structure resolution. A wide extent of this thesis is devoted to the study of avian prion protein. Prion protein is the main responsible of a vast class of neurodegenerative diseases, known as Bovine Spongiform Encephalopathy (BSE), present in mammals, but not in avian species and it is caused from the conversion of cellular prion protein to the pathogenic misfolded isoform, accumulating in the brain in form of amiloyd plaques. In particular, the N-terminal region, namely the initial part of the protein, is quite different between mammal and avian species but both of them contain multimeric sequences called Repeats, octameric in mammals and hexameric in avians. However, such repeat regions show differences in the contained amino acids, in particular only avian hexarepeats contain tyrosine residues. The chirality analysis of avian prion protein configurations obtained from molecular dynamics reveals a high stiffness of the avian protein, which tends to preserve its regular secondary structure. This is due to the presence of prolines, histidines and especially tyrosines, which form a hydrogen bond network in the hexarepeat region, only possible in the avian protein, and thus probably hampering the aggregation.

Adaptive multiscale biological signal processing

Biological processes are very complex mechanisms, most of them being accompanied by or manifested as signals that reflect their essential characteristics and qualities. The development of diagnostic techniques based on signal and image acquisition from the human body is commonly retained as one of the propelling factors in the advancements in medicine and biosciences recorded in the recent past. It is a fact that the instruments used for biological signal and image recording, like any other acquisition system, are affected by non-idealities which, by different degrees, negatively impact on the accuracy of the recording. This work discusses how it is possible to attenuate, and ideally to remove, these effects, with a particular attention toward ultrasound imaging and extracellular recordings. Original algorithms developed during the Ph.D. research activity will be examined and compared to ones in literature tackling the same problems; results will be drawn on the base of comparative tests on both synthetic and in-vivo acquisitions, evaluating standard metrics in the respective field of application. All the developed algorithms share an adaptive approach to signal analysis, meaning that their behavior is not dependent only on designer choices, but driven by input signal characteristics too. Performance comparisons following the state of the art concerning image quality assessment, contrast gain estimation and resolution gain quantification as well as visual inspection highlighted very good results featured by the proposed ultrasound image deconvolution and restoring algorithms: axial resolution up to 5 times better than algorithms in literature are possible. Concerning extracellular recordings, the results of the proposed denoising technique compared to other signal processing algorithms pointed out an improvement of the state of the art of almost 4 dB.

Statistical methods for biomedical signal analysis and processing

Statistical modelling and statistical learning theory are two powerful analytical frameworks for analyzing signals and developing efficient processing and classification algorithms. In this thesis, these frameworks are applied for modelling and processing biomedical signals in two different contexts: ultrasound medical imaging systems and primate neural activity analysis and modelling. In the context of ultrasound medical imaging, two main applications are explored: deconvolution of signals measured from a ultrasonic transducer and automatic image segmentation and classification of prostate ultrasound scans. In the former application a stochastic model of the radio frequency signal measured from a ultrasonic transducer is derived. This model is then employed for developing in a statistical framework a regularized deconvolution procedure, for enhancing signal resolution. In the latter application, different statistical models are used to characterize images of prostate tissues, extracting different features. These features are then uses to segment the images in region of interests by means of an automatic procedure based on a statistical model of the extracted features. Finally, machine learning techniques are used for automatic classification of the different region of interests. In the context of neural activity signals, an example of bio-inspired dynamical network was developed to help in studies of motor-related processes in the brain of primate monkeys. The presented model aims to mimic the abstract functionality of a cell population in 7a parietal region of primate monkeys, during the execution of learned behavioural tasks.

Heterogeneous multicore systems for signal processing

This thesis explores the capabilities of heterogeneous multi-core systems, based on multiple Graphics Processing Units (GPUs) in a standard desktop framework. Multi-GPU accelerated desk side computers are an appealing alternative to other high performance computing (HPC) systems: being composed of commodity hardware components fabricated in large quantities, their price-performance ratio is unparalleled in the world of high performance computing. Essentially bringing “supercomputing to the masses”, this opens up new possibilities for application fields where investing in HPC resources had been considered unfeasible before. One of these is the field of bioelectrical imaging, a class of medical imaging technologies that occupy a low-cost niche next to million-dollar systems like functional Magnetic Resonance Imaging (fMRI). In the scope of this work, several computational challenges encountered in bioelectrical imaging are tackled with this new kind of computing resource, striving to help these methods approach their true potential. Specifically, the following main contributions were made: Firstly, a novel dual-GPU implementation of parallel triangular matrix inversion (TMI) is presented, addressing an crucial kernel in computation of multi-mesh head models of encephalographic (EEG) source localization. This includes not only a highly efficient implementation of the routine itself achieving excellent speedups versus an optimized CPU implementation, but also a novel GPU-friendly compressed storage scheme for triangular matrices. Secondly, a scalable multi-GPU solver for non-hermitian linear systems was implemented. It is integrated into a simulation environment for electrical impedance tomography (EIT) that requires frequent solution of complex systems with millions of unknowns, a task that this solution can perform within seconds. In terms of computational throughput, it outperforms not only an highly optimized multi-CPU reference, but related GPU-based work as well. Finally, a GPU-accelerated graphical EEG real-time source localization software was implemented. Thanks to acceleration, it can meet real-time requirements in unpreceeded anatomical detail running more complex localization algorithms. Additionally, a novel implementation to extract anatomical priors from static Magnetic Resonance (MR) scansions has been included.

Development of bionanotechnological strategies for signal enhancement in nucleic acids biosensors

Nucleic acid biosensors represent a powerful tool for clinical and environmental pathogens detection. For applications such as point-of-care biosensing, it is fundamental to develop sensors that should be automatic, inexpensive, portable and require a professional skill of the user that should be as low as possible. With the goal of determining the presence of pathogens when present in very small amount, such as for the screening of pathogens in drinking water, an amplification step must be implemented. Often this type of determinations should be performed with simple, automatic and inexpensive hardware: the use of a chemical (or nanotechnological) isothermal solution would be desirable. My Ph.D. project focused on the study and on the testing of four isothermal reactions which can be used to amplify the nucleic acid analyte before the binding event on the surface sensor or to amplify the signal after that the hybridization event with the probe. Recombinase polymerase amplification (RPA) and ligation-mediated rolling circle amplification (L-RCA) were investigated as methods for DNA and RNA amplification. Hybridization chain reaction (HCR) and Terminal deoxynucleotidil transferase-mediated amplification were investigated as strategies to achieve the enhancement of the signal after the surface hybridization event between target and probe. In conclusion, it can be said that only a small subset of the biochemical strategies that are proved to work in solution towards the amplification of nucleic acids does truly work in the context of amplifying the signal of a detection system for pathogens. Amongst those tested during my Ph.D. activity, recombinase polymerase amplification seems the best candidate for a useful implementation in diagnostic or environmental applications.

Advanced signal and receiver design for next generation OFDM systems

This thesis deal with the design of advanced OFDM systems. Both waveform and receiver design have been treated. The main scope of the Thesis is to study, create, and propose, ideas and novel design solutions able to cope with the weaknesses and crucial aspects of modern OFDM systems. Starting from the the transmitter side, the problem represented by low resilience to non-linear distortion has been assessed. A novel technique that considerably reduces the Peak-to-Average Power Ratio (PAPR) yielding a quasi constant signal envelope in the time domain (PAPR close to 1 dB) has been proposed.The proposed technique, named Rotation Invariant Subcarrier Mapping (RISM),is a novel scheme for subcarriers data mapping,where the symbols belonging to the modulation alphabet are not anchored, but maintain some degrees of freedom. In other words, a bit tuple is not mapped on a single point, rather it is mapped onto a geometrical locus, which is totally or partially rotation invariant. The final positions of the transmitted complex symbols are chosen by an iterative optimization process in order to minimize the PAPR of the resulting OFDM symbol. Numerical results confirm that RISM makes OFDM usable even in severe non-linear channels. Another well known problem which has been tackled is the vulnerability to synchronization errors. Indeed in OFDM system an accurate recovery of carrier frequency and symbol timing is crucial for the proper demodulation of the received packets. In general, timing and frequency synchronization is performed in two separate phases called PRE-FFT and POST-FFT synchronization. Regarding the PRE-FFT phase, a novel joint symbol timing and carrier frequency synchronization algorithm has been presented. The proposed algorithm is characterized by a very low hardware complexity, and, at the same time, it guarantees very good performance in in both AWGN and multipath channels. Regarding the POST-FFT phase, a novel approach for both pilot structure and receiver design has been presented. In particular, a novel pilot pattern has been introduced in order to minimize the occurrence of overlaps between two pattern shifted replicas. This allows to replace conventional pilots with nulls in the frequency domain, introducing the so called Silent Pilots. As a result, the optimal receiver turns out to be very robust against severe Rayleigh fading multipath and characterized by low complexity. Performance of this approach has been analytically and numerically evaluated. Comparing the proposed approach with state of the art alternatives, in both AWGN and multipath fading channels, considerable performance improvements have been obtained. The crucial problem of channel estimation has been thoroughly investigated, with particular emphasis on the decimation of the Channel Impulse Response (CIR) through the selection of the Most Significant Samples (MSSs). In this contest our contribution is twofold, from the theoretical side, we derived lower bounds on the estimation mean-square error (MSE) performance for any MSS selection strategy,from the receiver design we proposed novel MSS selection strategies which have been shown to approach these MSE lower bounds, and outperformed the state-of-the-art alternatives. Finally, the possibility of using of Single Carrier Frequency Division Multiple Access (SC-FDMA) in the Broadband Satellite Return Channel has been assessed. Notably, SC-FDMA is able to improve the physical layer spectral efficiency with respect to single carrier systems, which have been used so far in the Return Channel Satellite (RCS) standards. However, it requires a strict synchronization and it is also sensitive to phase noise of local radio frequency oscillators. For this reason, an effective pilot tone arrangement within the SC-FDMA frame, and a novel Joint Multi-User (JMU) estimation method for the SC-FDMA, has been proposed. As shown by numerical results, the proposed scheme manages to satisfy strict synchronization requirements and to guarantee a proper demodulation of the received signal.

Analog Signal Acquisition and Conditioning for Near-Field Capacitive Communication and Active Combined EEG-EIT Monitoring

The work of the present thesis is focused on the implementation of microelectronic voltage sensing devices, with the purpose of transmitting and extracting analog information between devices of different nature at short distances or upon contact. Initally, chip-to-chip communication has been studied, and circuitry for 3D capacitive coupling has been implemented. Such circuits allow the communication between dies fabricated in different technologies. Due to their novelty, they are not standardized and currently not supported by standard CAD tools. In order to overcome such burden, a novel approach for the characterization of such communicating links has been proposed. This results in shorter design times and increased accuracy. Communication between an integrated circuit (IC) and a probe card has been extensively studied as well. Today wafer probing is a costly test procedure with many drawbacks, which could be overcome by a different communication approach such as capacitive coupling. For this reason wireless wafer probing has been investigated as an alternative approach to standard on-contact wafer probing. Interfaces between integrated circuits and biological systems have also been investigated. Active electrodes for simultaneous electroencephalography (EEG) and electrical impedance tomography (EIT) have been implemented for the first time in a 0.35 um process. Number of wires has been minimized by sharing the analog outputs and supply on a single wire, thus implementing electrodes that require only 4 wires for their operation. Minimization of wires reduces the cable weight and thus limits the patient's discomfort. The physical channel for communication between an IC and a biological medium is represented by the electrode itself. As this is a very crucial point for biopotential acquisitions, large efforts have been carried in order to investigate the different electrode technologies and geometries and an electromagnetic model is presented in order to characterize the properties of the electrode to skin interface.

Pyrolysis of peptides and proteins. Analytical study and environmental applications

Analytical pyrolysis was used to investigate the formation of diketopiperazines (DKPs) which are cyclic dipeptides formed from the thermal degradation of proteins. A quali/quantitative procedure was developed combining microscale flash pyrolysis at 500 °C with gas chromatography-mass spectrometry (GC-MS) of DKPs trapped onto an adsorbent phase. Polar DKPs were silylated prior to GC-MS. Particular attention was paid to the identification of proline (Pro) containing DKPs due to their greater facility of formation. The GC-MS characteristics of more than 80 original and silylated DKPs were collected from the pyrolysis of sixteen linear dipeptides and four model proteins (e.g. bovine serum albumin, BSA). The structure of a novel DKP, cyclo(pyroglutamic-Pro) was established by NMR and ESI-MS analysis, while the structures of other novel DKPs remained tentative. DKPs resulted rather specific markers of amino acid sequence in proteins, even though the thermal degradation of DKPs should be taken into account. Structural information of DKPs gathered from the pyrolysis of model compounds was employed to the identification of these compounds in the pyrolysate of proteinaceous samples, including intrinsecally unfolded protein (IUP). Analysis of the liquid fraction (bio-oil) obtained from the pyrolysis of microalgae Nannochloropsis gaditana, Scenedesmus spp with a bench scale reactor showed that DKPs constituted an important pool of nitrogen-containing compounds. Conversely, the level of DKPs was rather low in the bio-oil of Botryococcus braunii. The developed micropyrolysis procedure was applied in combination with thermogravimetry (TGA) and infrared spectroscopy (FT-IR) to investigate surface interaction between BSA and synthetic chrysotile. The results showed that the thermal behavior of BSA (e.g. DKPs formation) was affected by the different form of doped synthetic chrysotile. The typical DKPs evolved from collagen were quantified in the pyrolysates of archaeological bones from Vicenne Necropolis in order to evaluate their conservation status in combination with TGA, FTIR and XRD analysis.

Synthesis of Modified Amino Acids and Insertion in Peptides and Mimetics. Structural Aspects and Impact on Biological Activity.

I studied the effects exerted by the modifications on structures and biological activities of the compounds so obtained. I prepared peptide analogues containing unusual amino acids such as halogenated, alkylated (S)- or (R)-tryptophans, useful for the synthesis of mimetics of the endogenous opioid peptide endomorphin-1, or 2-oxo-1,3-oxazolidine-4-carboxylic acids, utilized as pseudo-prolines having a clear all-trans configuration of the preceding peptide bond. The latter gave access to a series of constrained peptidomimetics with potential interest in medicinal chemistry and in the field of the foldamers. In particular, I have dedicated much efforts to the preparation of cyclopentapeptides containing D-configured, alfa-, or beta-aminoacids, and also of cyclotetrapeptides including the retro-inverso modification. The conformational analyses confirmed that these cyclic compounds can be utilized as rigid scaffolds mimicking gamma- or beta-turns, allowing to generate new molecular and 3D diversity. Much work has been dedicated to the structural analysis in solution and in the receptor-bound state, fundamental for giving a rationale to the experimentally determined bioactivity, as well as for predicting the activity of virtual compounds (in silico pre-screen). The conformational analyses in solution has been done mostly by NMR (2D gCosy, Roesy, VT, molecular dynamics, etc.). A special section is dedicated to the prediction of plausible poses of the ligands when bound to the receptors by Molecular Docking. This computational method proved to be a powerful tool for the investigation of ligand-receptor interactions, and for the design of selective agonists and antagonists. Another practical use of cyclic peptidomimetics was the synthesis and biological evaluation of cyclic analogues of endomorphin-1 lacking in a protonable amino group. The studies revealed that a inverse type II beta-turn on D-Trp-Phe constituted the bioactive conformation.

Development of new therapeutic approaches in the treatments of Inflammatory Bowel Diseases: functional food and nutraceuticals vs synthetic peptides based vaccines

Inflammatory Bowel Diseases (IBD) are intestinal chronic relapsing diseases which ethiopathogenesis remains uncertain. Several group have attempted to study the role of factors involved such as genetic susceptibility, environmental factors such as smoke, diet, sex, immunological factors as well as the microbioma. None of the treatments available satisfy several criteria at the same time such as safety, long-term remission, histopatological healing, and specificity. We used two different approaches for the development of new therapeutic treatment for Inflammatory Bowel Disease. The first is focused on the understanding of the potential role of functional food and nutraceuticals nutrients in the treatment of IBD. To do so, we investigated the role of Curcuma longa in the treatment of chemical induced colitis in mice model. Since Curcma Longa has been investigated for its antinflammatory role related to the TNFα pathway as well investigators have reported few cases of patients with ulcerative colites treated with this herbs, we harbored the hypothesis of a role of Curcuma Longa in the treatment f IBD as well as we decided to assess its role in intestinal motility. The second part is based on an immunological approach to develop new drugs to induce suppression in Crohn’s disease or to induce mucosa immunity such as in colonrectal tumor. The main idea behind this approach is that we could manipulate relevant cell-cell interactions using synthetic peptides. We demonstrated the role of the unique interaction between molecules expressed on intestinal epithelial cells such as CD1d and CEACAM5 and on CD8+ T cells. In normal condition this interaction has a role for the expansion of the suppressor CD8+ T cells. Here, we characterized this interaction, we defined which are the epitope involved in the binding and we attempted to develop synthetic peptides from the N domain of CEACAM5 in order to manipulate it.