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.