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.

Computational methods for the analysis of protein structure and function

The vast majority of known proteins have not yet been experimentally characterized and little is known about their function. The design and implementation of computational tools can provide insight into the function of proteins based on their sequence, their structure, their evolutionary history and their association with other proteins. Knowledge of the three-dimensional (3D) structure of a protein can lead to a deep understanding of its mode of action and interaction, but currently the structures of <1% of sequences have been experimentally solved. For this reason, it became urgent to develop new methods that are able to computationally extract relevant information from protein sequence and structure. The starting point of my work has been the study of the properties of contacts between protein residues, since they constrain protein folding and characterize different protein structures. Prediction of residue contacts in proteins is an interesting problem whose solution may be useful in protein folding recognition and de novo design. The prediction of these contacts requires the study of the protein inter-residue distances related to the specific type of amino acid pair that are encoded in the so-called contact map. An interesting new way of analyzing those structures came out when network studies were introduced, with pivotal papers demonstrating that protein contact networks also exhibit small-world behavior. In order to highlight constraints for the prediction of protein contact maps and for applications in the field of protein structure prediction and/or reconstruction from experimentally determined contact maps, I studied to which extent the characteristic path length and clustering coefficient of the protein contacts network are values that reveal characteristic features of protein contact maps. Provided that residue contacts are known for a protein sequence, the major features of its 3D structure could be deduced by combining this knowledge with correctly predicted motifs of secondary structure. In the second part of my work I focused on a particular protein structural motif, the coiled-coil, known to mediate a variety of fundamental biological interactions. Coiled-coils are found in a variety of structural forms and in a wide range of proteins including, for example, small units such as leucine zippers that drive the dimerization of many transcription factors or more complex structures such as the family of viral proteins responsible for virus-host membrane fusion. The coiled-coil structural motif is estimated to account for 5-10% of the protein sequences in the various genomes. Given their biological importance, in my work I introduced a Hidden Markov Model (HMM) that exploits the evolutionary information derived from multiple sequence alignments, to predict coiled-coil regions and to discriminate coiled-coil sequences. The results indicate that the new HMM outperforms all the existing programs and can be adopted for the coiled-coil prediction and for large-scale genome annotation. Genome annotation is a key issue in modern computational biology, being the starting point towards the understanding of the complex processes involved in biological networks. The rapid growth in the number of protein sequences and structures available poses new fundamental problems that still deserve an interpretation. Nevertheless, these data are at the basis of the design of new strategies for tackling problems such as the prediction of protein structure and function. Experimental determination of the functions of all these proteins would be a hugely time-consuming and costly task and, in most instances, has not been carried out. As an example, currently, approximately only 20% of annotated proteins in the Homo sapiens genome have been experimentally characterized. A commonly adopted procedure for annotating protein sequences relies on the "inheritance through homology" based on the notion that similar sequences share similar functions and structures. This procedure consists in the assignment of sequences to a specific group of functionally related sequences which had been grouped through clustering techniques. The clustering procedure is based on suitable similarity rules, since predicting protein structure and function from sequence largely depends on the value of sequence identity. However, additional levels of complexity are due to multi-domain proteins, to proteins that share common domains but that do not necessarily share the same function, to the finding that different combinations of shared domains can lead to different biological roles. In the last part of this study I developed and validate a system that contributes to sequence annotation by taking advantage of a validated transfer through inheritance procedure of the molecular functions and of the structural templates. After a cross-genome comparison with the BLAST program, clusters were built on the basis of two stringent constraints on sequence identity and coverage of the alignment. The adopted measure explicity answers to the problem of multi-domain proteins annotation and allows a fine grain division of the whole set of proteomes used, that ensures cluster homogeneity in terms of sequence length. A high level of coverage of structure templates on the length of protein sequences within clusters ensures that multi-domain proteins when present can be templates for sequences of similar length. This annotation procedure includes the possibility of reliably transferring statistically validated functions and structures to sequences considering information available in the present data bases of molecular functions and structures.

De Novo Design of secondary structures: Synthesis and conformational studies

Chemists have long sought to extrapolate the power of biological catalysis and recognition to synthetic systems. These efforts have focused largely on low molecular weight catalysts and receptors; however, biological systems themselves rely almost exclusively on polymers, proteins and RNA, to perform complex chemical functions. Proteins and RNA are unique in their ability to adopt compact, well-ordered conformations, and specific folding provides precise spatial orientation of the functional groups that comprise the “active site”. These features suggest that identification of new polymer backbones with discrete and predictable folding propensities (“foldamers”) will provide a basis for design of molecular machines with unique capabilities. The foldamer approach complements current efforts to design unnatural properties into polypeptides and polynucleotides. The aim of this thesis is the synthesis and conformational studies of new classes of foldamers, using a peptidomimetic approach. Moreover their attitude to be utilized as ionophores, catalysts, and nanobiomaterials were analyzed in solution and in the solid state. This thesis is divided in thematically chapters that are reported below. It begins with a very general introduction (page 4) which is useful, but not strictly necessary, to the expert reader. It is worth mentioning that paragraph I.3 (page 22) is the starting point of this work and paragraph I.5 (page 32) isrequired to better understand the results of chapters 4 and 5. In chapter 1 (page 39) is reported the synthesis and conformational analysis of a novel class of foldamers containing (S)-β3-homophenylglycine [(S)-β3-hPhg] and D- 4-carboxy-oxazolidin-2-one (D-Oxd) residues in alternate order is reported. The experimental conformational analysis performed in solution by IR, 1HNMR, and CD spectroscopy unambiguously proved that these oligomers fold into ordered structures with increasing sequence length. Theoretical calculations employing ab initio MO theory suggest a helix with 11-membered hydrogenbonded rings as the preferred secondary structure type. The novel structures enrich the field of peptidic foldamers and might be useful in the mimicry of native peptides. In chapter 2 cyclo-(L-Ala-D-Oxd)3 and cyclo-(L-Ala-DOxd) 4 were prepared in the liquid phase with good overall yields and were utilized for bivalent ions chelation (Ca2+, Mg2+, Cu2+, Zn2+ and Hg2+); their chelation skill was analyzed with ESI-MS, CD and 1HNMR techniques and the best results were obtained with cyclo-(L-Ala-D-Oxd)3 and Mg2+ or Ca2+. Chapter 3 describes an application of oligopeptides as catalysts for aldol reactions. Paragraph 3.1 concerns the use of prolinamides as catalysts of the cross aldol addition of hydroxyacetone to aromatic aldeydes, whereas paragraphs 3.2 and 3.3 are about the catalyzed aldol addition of acetone to isatins. By means of DFT and AIM calculations, the steric and stereoelectronic effects that control the enantioselectivity in the cross-aldol addition of acetone to isatin catalysed by L-proline have been studied, also in the presence of small quantities of water. In chapter 4 is reported the synthesis and the analysis of a new fiber-like material, obtained from the selfaggregation of the dipeptide Boc-L-Phe-D-Oxd-OBn, which spontaneously forms uniform fibers consisting of parallel infinite linear chains arising from singleintermolecular N-H···O=C hydrogen bonds. This is the absolute borderline case of a parallel β-sheet structure. Longer oligomers of the same series with general formula Boc-(L-Phe-D-Oxd)n-OBn (where n = 2-5), are described in chapter 5. Their properties in solution and in the solid state were analyzed, in correlation with their attitude to form intramolecular hydrogen bond. In chapter 6 is reported the synthesis of imidazolidin-2- one-4-carboxylate and (tetrahydro)-pyrimidin-2-one-5- carboxylate, via an efficient modification of the Hofmann rearrangement. The reaction affords the desired compounds from protected asparagine or glutamine in good to high yield, using PhI(OAc)2 as source of iodine(III).

Studio di biomateriali usati come scaffold per Tissue Engineering e loro caratterizzazione con tecniche spettroscopiche vibrazionali e di analisi termica

This research investigated someone of the main problems connected to the application of Tissue Engineering in the prosthetic field, in particular about the characterization of the scaffolding materials and biomimetic strategies adopted in order to promote the implant integration. The spectroscopic and thermal analysis techniques were usefully applied to characterize the chemico-physical properties of the materials such as – crystallinity; – relative composition in case of composite materials; – Structure and conformation of polymeric and peptidic chains; – mechanism and degradation rate; – Intramolecular and intermolecular interactions (hydrogen bonds, aliphatic interactions). This kind of information are of great importance in the comprehension of the interactions that scaffold undergoes when it is in contact with biological tissues; this information are fundamental to predict biodegradation mechanisms and to understand how chemico-physical properties change during the degradation process. In order to fully characterize biomaterials, this findings must be integrated by information relative to mechanical aspects and in vitro and in vivo behavior thanks to collaborations with biomedical engineers and biologists. This study was focussed on three different systems that correspond to three different strategies adopted in Tissue Engineering: biomimetic replica of fibrous 3-D structure of extracellular matrix (PCL-PLLA), incorporation of an apatitic phase similar to bone inorganic phase to promote biomineralization (PCL-HA), surface modification with synthetic oligopeptides that elicit the interaction with osteoblasts. The characterization of the PCL-PLLA composite underlined that the degradation started along PLLA fibres, which are more hydrophylic, and they serve as a guide for tissue regeneration. Moreover it was found that some cellular lines are more active in the colonization of the scaffold. In the PCL-HA composite, the weight ratio between the polymeric and the inorganic phase plays an essential role both in the degradation process and in the biomineralization of the material. The study of self-assembling peptides allowed to clarify the influence of primary structure on intermolecular and intermolecular interactions, that lead to the formation of the secondary structure and it was possible to find a new class of oligopeptides useful to functionalize materials surface. Among the analytical techniques used in this study, Raman vibrational spectroscopy played a major role, being non-destructive and non-invasive, two properties that make it suitable to degradation studies and to morphological characterization. Also micro-IR spectroscopy was useful in the comprehension of peptide structure on oxidized titanium: up to date this study was one of the first to employ this relatively new technique in the biomedical field.

Eterogeneità delle proprietà fisico – chimiche della proteina prionica patologica e variabilità fenotipica ceppo specifica nella malattia di Creutzfeldt – Jakob

Transmissible spongiform encephalopathies (TSEs), or prion diseases, are neurodegenerative disorders that affect humans and mammals. Creutzfeldt-Jakob disease (CJD), the most common TSE in humans, can be sporadic (sCJD), genetic (gCJD), or acquired by infection. All TSEs are characterised by the accumulation of PrPSc, a misfolded form of the cellular protein PrPC. PrPSc is insoluble in detergents, partially resistant to proteolysis and shows a highly enriched β-sheet secondary structure. Six clinico-pathological phenotypes of sCJD have been characterized which correlate at the molecular level with two types (1 or 2) of PrPSc with distinctive physicochemical properties and the genotype at the polymorphic (methionine or valine) codon 129 of the prion protein gene. According to the protein-only hypothesis, which postulates that prions are composed exclusively of PrPSc, the strains of prions that are largely responsible for the wide spectrum of TSE phenotypes are enciphered in PrPSc conformation. In support to this view, studies mainly conducted in experimental scrapie, have shown that several prion strains can be identified based on distinguishing PrPSc biochemical properties. To further contribute to the understanding of the molecular basis of strains and to develop more sensitive strain typing assays in humans we have analyzed PrPSc biochemical properties in two experimental setting. In the first we compared the size of the core after protease digestion and the glycoform pattern of PrPSc before and after transmission of human prions to non human primates or bank voles, whereas in the second we analyzed the conformational stability of PrPSc associated with sCJD, vCJD or fCJD using guanidine hydrochloride (GdnHCl) as denaturant. Combining the results of the two studies, we were able to distinguish five human strains for at least one biochemical property. The present data extend our knowledge about the extent of strain variation and its relationship with PrPSc properties in human TSEs.

Hsp90 characterization and inhibition: a multi-methodological study

Many physiological and pathological processes are mediated by the activity of proteins assembled in homo and/or hetero-oligomers. The correct recognition and association of these proteins into a functional complex is a key step determining the fate of the whole pathway. This has led to an increasing interest in selecting molecules able to modulate/inhibit these protein-protein interactions. In particular, our research was focused on Heat Shock Protein 90 (Hsp90), responsible for the activation and maturation and disposition of many client proteins [1], [2] [3]. Circular Dichroism (CD) spectroscopy, Surface Plasmon Resonance (SPR) and Affinity Capillary Electrophoresis (ACE) were used to characterize the Hsp90 target and, furthermore, its inhibition process via C-terminal domain driven by the small molecule Coumermycin A1. Circular Dichroism was used as powerful technique to characterize Hsp90 and its co-chaperone Hop in solution for secondary structure content, stability to different pHs, temperatures and solvents. Furthermore, CD was used to characterize ATP but, unfortunately, we were not able to monitor an interaction between ATP and Hsp90. The utility of SPR technology, on the other hand, arises from the possibility of immobilizing the protein on a chip through its N-terminal domain to later study the interaction with small molecules able to disrupt the Hsp90 dimerization on the C-terminal domain. The protein was attached on SPR chip using the “amine coupling” chemistry so that the C-terminal domain was free to interact with Coumermycin A1. The goal of the experiment was achieved by testing a range of concentrations of the small molecule Coumermycin A1. Despite to the large difference in the molecular weight of the protein (90KDa) and the drug (1110.08 Da), we were able to calculate the affinity constant of the interaction that was found to be 11.2 µm. In order to confirm the binding constant calculated for the Hsp90 on the chip, we decided to use Capillary Electrophoresis to test the Coumermycin binding to Hsp90. First, this technique was conveniently used to characterize the Hsp90 sample in terms of composition and purity. The experimental conditions were settled on two different systems, the bared fused silica and the PVA-coated capillary. We were able to characterize the Hsp90 sample in both systems. Furthermore, we employed an application of capillary electrophoresis, the Affinity Capillary Electrophoresis (ACE), to measure and confirm the binding constant calculated for Coumermycin on Optical Biosensor. We found a KD = 19.45 µM. This result compares favorably with the KD previously obtained on biosensor. This is a promising result for the use of our novel approach to screen new potential inhibitors of Hsp90 C-terminal domain.

De Novo Design of Foldamers for Preparation of Nanostructured Materials

This thesis deals with the synthesis and the conformation analysis of hybrid foldamers containing the 4-carboxyoxazolidin-2-one unit or related molecules, in which an imido-type function is obtained by coupling the nitrogen of the heterocycle with the carboxylic acid moiety of the next unit. The imide group is characterized by a nitrogen atom connected to an endocyclic and an exocyclic carbonyl, which tend always to adopt the trans conformation. As a consequence of this locally constrained disposition effect, these imide-type oligomers are forced to fold in ordered conformations. The synthetic approach is highly tuneable with endless variations, so, simply by changing the design and the synthesis, a wide variety of foldamers with the required properties may be prepared “on demand”. Thus a wide variety of unusual secondary structures and interesting supramolecular materials may be obtained with hybrid foldamers. The behaviour in the solid state of some of these compounds has been analyzed in detail, thus showing the formation of different kinds of supramolecular materials that may be used for several applications. A winning example is the production of a bolaamphiphilic gelators that may also be doped with small amounts of dansyl containing compounds, needed to show the cellular uptake into IGROV-1 cells, by confocal laser scanning microscopy. These gels are readily internalized by cells and are biologically inactive, making them very good candidates in the promising field of drug delivery. In the last part of the thesis, a particular attention was directed to the search of new scaffolds that behave as constrained amino acid mimetics, showing that tetramic acids derivatives could be good candidates for the synthesis and applications of molecules having an ordered secondary structure.

Learning with Kernels on Graphs: DAG-based kernels, data streams and RNA function prediction.

In many application domains data can be naturally represented as graphs. When the application of analytical solutions for a given problem is unfeasible, machine learning techniques could be a viable way to solve the problem. Classical machine learning techniques are defined for data represented in a vectorial form. Recently some of them have been extended to deal directly with structured data. Among those techniques, kernel methods have shown promising results both from the computational complexity and the predictive performance point of view. Kernel methods allow to avoid an explicit mapping in a vectorial form relying on kernel functions, which informally are functions calculating a similarity measure between two entities. However, the definition of good kernels for graphs is a challenging problem because of the difficulty to find a good tradeoff between computational complexity and expressiveness. Another problem we face is learning on data streams, where a potentially unbounded sequence of data is generated by some sources. There are three main contributions in this thesis. The first contribution is the definition of a new family of kernels for graphs based on Directed Acyclic Graphs (DAGs). We analyzed two kernels from this family, achieving state-of-the-art results from both the computational and the classification point of view on real-world datasets. The second contribution consists in making the application of learning algorithms for streams of graphs feasible. Moreover,we defined a principled way for the memory management. The third contribution is the application of machine learning techniques for structured data to non-coding RNA function prediction. In this setting, the secondary structure is thought to carry relevant information. However, existing methods considering the secondary structure have prohibitively high computational complexity. We propose to apply kernel methods on this domain, obtaining state-of-the-art results.

Transposable elements: structure and dynamic of the autonomous retrotransposon R2 in Arthropoda with non-canonical reproduction

Eukaryotic ribosomal DNA constitutes a multi gene family organized in a cluster called nucleolar organizer region (NOR); this region is composed usually by hundreds to thousands of tandemly repeated units. Ribosomal genes, being repeated sequences, evolve following the typical pattern of concerted evolution. The autonomous retroelement R2 inserts in the ribosomal gene 28S, leading to defective 28S rDNA genes. R2 element, being a retrotransposon, performs its activity in the genome multiplying its copy number through a “copy and paste” mechanism called target primed reverse transcription. It consists in the retrotranscription of the element’s mRNA into DNA, then the DNA is integrated in the target site. Since the retrotranscription can be interrupted, but the integration will be carried out anyway, truncated copies of the element will also be present in the genome. The study of these truncated variants is a tool to examine the activity of the element. R2 phylogeny appears, in general, not consistent with that of its hosts, except some cases (e.g. Drosophila spp. and Reticulitermes spp.); moreover R2 is absent in some species (Fugu rubripes, human, mouse, etc.), while other species have more R2 lineages in their genome (the turtle Mauremys reevesii, the Japanese beetle Popilia japonica, etc). R2 elements here presented are isolated in 4 species of notostracan branchiopods and in two species of stick insects, whose reproductive strategies range from strict gonochorism to unisexuality. From sequencing data emerges that in Triops cancriformis (Spanish gonochoric population), in Lepidurus arcticus (two putatively unisexual populations from Iceland) and in Bacillus rossius (gonochoric population from Capalbio) the R2 elements are complete and encode functional proteins, reflecting the general features of this family of transposable elements. On the other hand, R2 from Italian and Austrian populations of T. cancriformis (respectively unisexual and hermaphroditic), Lepidurus lubbocki (two elements within the same Italian population, gonochoric but with unfunctional males) and Bacillus grandii grandii (gonochoric population from Ponte Manghisi) have sequences that encode incomplete or non-functional proteins in which it is possible to recognize only part of the characteristic domains. In Lepidurus couesii (Italian gonochoric populations) different elements were found as in L. lubbocki, and the sequencing is still in progress. Two hypothesis are given to explain the inconsistency of R2/host phylogeny: vertical inheritance of the element followed by extinction/diversification or horizontal transmission. My data support previous study that state the vertical transmission as the most likely explanation; nevertheless horizontal transfer events can’t be excluded. I also studied the element’s activity in Spanish populations of T. cancriformis, in L. lubbocki, in L. arcticus and in gonochoric and parthenogenetic populations of B. rossius. In gonochoric populations of T. cancriformis and B. rossius I found that each individual has its own private set of truncated variants. The situation is the opposite for the remaining hermaphroditic/parthenogenetic species and populations, all individuals sharing – in the so far analyzed samples - the majority of variants. This situation is very interesting, because it isn’t concordant with the Muller’s ratchet theory that hypothesizes the parthenogenetic populations being either devoided of transposable elements or TEs overloaded. My data suggest a possible epigenetic mechanism that can block the retrotransposon activity, and in this way deleterious mutations don’t accumulate.

Computational analyses on the structure-function relation in ion channels

Ion channels are protein molecules, embedded in the lipid bilayer of the cell membranes. They act as powerful sensing elements switching chemicalphysical stimuli into ion-fluxes. At a glance, ion channels are water-filled pores, which can open and close in response to different stimuli (gating), and one once open select the permeating ion species (selectivity). They play a crucial role in several physiological functions, like nerve transmission, muscular contraction, and secretion. Besides, ion channels can be used in technological applications for different purpose (sensing of organic molecules, DNA sequencing). As a result, there is remarkable interest in understanding the molecular determinants of the channel functioning. Nowadays, both the functional and the structural characteristics of ion channels can be experimentally solved. The purpose of this thesis was to investigate the structure-function relation in ion channels, by computational techniques. Most of the analyses focused on the mechanisms of ion conduction, and the numerical methodologies to compute the channel conductance. The standard techniques for atomistic simulation of complex molecular systems (Molecular Dynamics) cannot be routinely used to calculate ion fluxes in membrane channels, because of the high computational resources needed. The main step forward of the PhD research activity was the development of a computational algorithm for the calculation of ion fluxes in protein channels. The algorithm - based on the electrodiffusion theory - is computational inexpensive, and was used for an extensive analysis on the molecular determinants of the channel conductance. The first record of ion-fluxes through a single protein channel dates back to 1976, and since then measuring the single channel conductance has become a standard experimental procedure. Chapter 1 introduces ion channels, and the experimental techniques used to measure the channel currents. The abundance of functional data (channel currents) does not match with an equal abundance of structural data. The bacterial potassium channel KcsA was the first selective ion channels to be experimentally solved (1998), and after KcsA the structures of four different potassium channels were revealed. These experimental data inspired a new era in ion channel modeling. Once the atomic structures of channels are known, it is possible to define mathematical models based on physical descriptions of the molecular systems. These physically based models can provide an atomic description of ion channel functioning, and predict the effect of structural changes. Chapter 2 introduces the computation methods used throughout the thesis to model ion channels functioning at the atomic level. In Chapter 3 and Chapter 4 the ion conduction through potassium channels is analyzed, by an approach based on the Poisson-Nernst-Planck electrodiffusion theory. In the electrodiffusion theory ion conduction is modeled by the drift-diffusion equations, thus describing the ion distributions by continuum functions. The numerical solver of the Poisson- Nernst-Planck equations was tested in the KcsA potassium channel (Chapter 3), and then used to analyze how the atomic structure of the intracellular vestibule of potassium channels affects the conductance (Chapter 4). As a major result, a correlation between the channel conductance and the potassium concentration in the intracellular vestibule emerged. The atomic structure of the channel modulates the potassium concentration in the vestibule, thus its conductance. This mechanism explains the phenotype of the BK potassium channels, a sub-family of potassium channels with high single channel conductance. The functional role of the intracellular vestibule is also the subject of Chapter 5, where the affinity of the potassium channels hEag1 (involved in tumour-cell proliferation) and hErg (important in the cardiac cycle) for several pharmaceutical drugs was compared. Both experimental measurements and molecular modeling were used in order to identify differences in the blocking mechanism of the two channels, which could be exploited in the synthesis of selective blockers. The experimental data pointed out the different role of residue mutations in the blockage of hEag1 and hErg, and the molecular modeling provided a possible explanation based on different binding sites in the intracellular vestibule. Modeling ion channels at the molecular levels relates the functioning of a channel to its atomic structure (Chapters 3-5), and can also be useful to predict the structure of ion channels (Chapter 6-7). In Chapter 6 the structure of the KcsA potassium channel depleted from potassium ions is analyzed by molecular dynamics simulations. Recently, a surprisingly high osmotic permeability of the KcsA channel was experimentally measured. All the available crystallographic structure of KcsA refers to a channel occupied by potassium ions. To conduct water molecules potassium ions must be expelled from KcsA. The structure of the potassium-depleted KcsA channel and the mechanism of water permeation are still unknown, and have been investigated by numerical simulations. Molecular dynamics of KcsA identified a possible atomic structure of the potassium-depleted KcsA channel, and a mechanism for water permeation. The depletion from potassium ions is an extreme situation for potassium channels, unlikely in physiological conditions. However, the simulation of such an extreme condition could help to identify the structural conformations, so the functional states, accessible to potassium ion channels. The last chapter of the thesis deals with the atomic structure of the !- Hemolysin channel. !-Hemolysin is the major determinant of the Staphylococcus Aureus toxicity, and is also the prototype channel for a possible usage in technological applications. The atomic structure of !- Hemolysin was revealed by X-Ray crystallography, but several experimental evidences suggest the presence of an alternative atomic structure. This alternative structure was predicted, combining experimental measurements of single channel currents and numerical simulations. This thesis is organized in two parts, in the first part an overview on ion channels and on the numerical methods adopted throughout the thesis is provided, while the second part describes the research projects tackled in the course of the PhD programme. The aim of the research activity was to relate the functional characteristics of ion channels to their atomic structure. In presenting the different research projects, the role of numerical simulations to analyze the structure-function relation in ion channels is highlighted.

Studio di ausili tecnologici compensativi di supporto all'iter di apprendimento matematico secondario e universitario degli studenti con dislessia

Data coming out from various researches carried out over the last years in Italy on the problem of school dispersion in secondary school show that difficulty in studying mathematics is one of the most frequent reasons of discomfort reported by students. Nevertheless, it is definitely unrealistic to think we can do without such knowledge in today society: mathematics is largely taught in secondary school and it is not confined within technical-scientific courses only. It is reasonable to say that, although students may choose academic courses that are, apparently, far away from mathematics, all students will have to come to terms, sooner or later in their life, with this subject. Among the reasons of discomfort given by the study of mathematics, some mention the very nature of this subject and in particular the complex symbolic language through which it is expressed. In fact, mathematics is a multimodal system composed by oral and written verbal texts, symbol expressions, such as formulae and equations, figures and graphs. For this, the study of mathematics represents a real challenge to those who suffer from dyslexia: this is a constitutional condition limiting people performances in relation to the activities of reading and writing and, in particular, to the study of mathematical contents. Here the difficulties in working with verbal and symbolic codes entail, in turn, difficulties in the comprehension of texts from which to deduce operations that, once combined together, would lead to the problem final solution. Information technologies may support this learning disorder effectively. However, these tools have some implementation limits, restricting their use in the study of scientific subjects. Vocal synthesis word processors are currently used to compensate difficulties in reading within the area of classical studies, but they are not used within the area of mathematics. This is because the vocal synthesis (or we should say the screen reader supporting it) is not able to interpret all that is not textual, such as symbols, images and graphs. The DISMATH software, which is the subject of this project, would allow dyslexic users to read technical-scientific documents with the help of a vocal synthesis, to understand the spatial structure of formulae and matrixes, to write documents with a technical-scientific content in a format that is compatible with main scientific editors. The system uses LaTex, a text mathematic language, as mediation system. It is set up as LaTex editor, whose graphic interface, in line with main commercial products, offers some additional specific functions with the capability to support the needs of users who are not able to manage verbal and symbolic codes on their own. LaTex is translated in real time into a standard symbolic language and it is read by vocal synthesis in natural language, in order to increase, through the bimodal representation, the ability to process information. The understanding of the mathematic formula through its reading is made possible by the deconstruction of the formula itself and its “tree” representation, so allowing to identify the logical elements composing it. Users, even without knowing LaTex language, are able to write whatever scientific document they need: in fact the symbolic elements are recalled by proper menus and automatically translated by the software managing the correct syntax. The final aim of the project, therefore, is to implement an editor enabling dyslexic people (but not only them) to manage mathematic formulae effectively, through the integration of different software tools, so allowing a better teacher/learner interaction too.

The physical city and the urban structure: detecting amenity zones and applying urban morphology to New York

The city is a collection of built structures and infrastructure embedded in socio-cultural processes: any investigation into a city’s transformations involves considerations on the degree to which its composite elements respond to socio-economical changes. The main purpose of this research is to investigate how transformations in the functional requirements of New York’s society have spurred, since the 1970s, changes in both the city’s urban structure and physical form. The present work examines the rise of Amenity Zones in New York, and investigates the transformations that have occurred in New York’s built environment since the 1970s. By applying qualitative measures and analyzing the relationship between urban amenities and the creative class, the present work has investigated changes in the urban structure and detected a hierarchical series of amenity zones classes, namely, Super Amenity Zones (SAZs), Nodal Amenity Zones (NAZs) and Peripheral Amenity Zones (PAZs). This series allows for a more comprehensive reading of the urban structure in a complex city like New York, bringing advancements to the amenity zone’s methodology. In order to examine the manner in which the other component of the city, the physical form, has changed or adapted to the new socio-economic condition, the present research has applied Conzenian analysis to a select study area, Atlantic Avenue. The results of this analysis reveal that, contrary to the urban structure, which changes rapidly, the physical form of New York is hard to modify completely, due to the resilience of the town plan and its elements, and to preservation laws; the city rather adapts to socio-economical changes through process of adaptive reuses or conversion. Concluding, this research has examined the dialectic between the ever-changing needs of society and the complexity of the built environment and urban structure, showing the different degrees to which the urban landscape modifies, reacts and sometimes adapts to the population’s functional requirements.

Fluid-structure interaction by a coupled lattice Boltzmann-finite element approach

In this thesis, a strategy to model the behavior of fluids and their interaction with deformable bodies is proposed. The fluid domain is modeled by using the lattice Boltzmann method, thus analyzing the fluid dynamics by a mesoscopic point of view. It has been proved that the solution provided by this method is equivalent to solve the Navier-Stokes equations for an incompressible flow with a second-order accuracy. Slender elastic structures idealized through beam finite elements are used. Large displacements are accounted for by using the corotational formulation. Structural dynamics is computed by using the Time Discontinuous Galerkin method. Therefore, two different solution procedures are used, one for the fluid domain and the other for the structural part, respectively. These two solvers need to communicate and to transfer each other several information, i.e. stresses, velocities, displacements. In order to guarantee a continuous, effective, and mutual exchange of information, a coupling strategy, consisting of three different algorithms, has been developed and numerically tested. In particular, the effectiveness of the three algorithms is shown in terms of interface energy artificially produced by the approximate fulfilling of compatibility and equilibrium conditions at the fluid-structure interface. The proposed coupled approach is used in order to solve different fluid-structure interaction problems, i.e. cantilever beams immersed in a viscous fluid, the impact of the hull of the ship on the marine free-surface, blood flow in a deformable vessels, and even flapping wings simulating the take-off of a butterfly. The good results achieved in each application highlight the effectiveness of the proposed methodology and of the C++ developed software to successfully approach several two-dimensional fluid-structure interaction problems.

New computational biology tools for the systematic analysis of the structure and expression of human genes

From the late 1980s, the automation of sequencing techniques and the computer spread gave rise to a flourishing number of new molecular structures and sequences and to proliferation of new databases in which to store them. Here are presented three computational approaches able to analyse the massive amount of publicly avalilable data in order to answer to important biological questions. The first strategy studies the incorrect assignment of the first AUG codon in a messenger RNA (mRNA), due to the incomplete determination of its 5' end sequence. An extension of the mRNA 5' coding region was identified in 477 in human loci, out of all human known mRNAs analysed, using an automated expressed sequence tag (EST)-based approach. Proof-of-concept confirmation was obtained by in vitro cloning and sequencing for GNB2L1, QARS and TDP2 and the consequences for the functional studies are discussed. The second approach analyses the codon bias, the phenomenon in which distinct synonymous codons are used with different frequencies, and, following integration with a gene expression profile, estimates the total number of codons present across all the expressed mRNAs (named here "codonome value") in a given biological condition. Systematic analyses across different pathological and normal human tissues and multiple species shows a surprisingly tight correlation between the codon bias and the codonome bias. The third approach is useful to studies the expression of human autism spectrum disorder (ASD) implicated genes. ASD implicated genes sharing microRNA response elements (MREs) for the same microRNA are co-expressed in brain samples from healthy and ASD affected individuals. The different expression of a recently identified long non coding RNA which have four MREs for the same microRNA could disrupt the equilibrium in this network, but further analyses and experiments are needed.