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.

The secondary market for life insurance policies in the United States market evolution and product valuation

In this work we discuss the secondary market for life insurance policies in the United States of America. First, we give an overview of the life settlement market: how it came into existence, its growth prospects and the ethical issues it arises. Secondly, we discuss the characteristics of the different life insurance products present in the market and describe how life settlements are originated. Life settlement transactions tend to be long and complex transactions that require the involvement of a number of parties. Also, a direct investment into life insurance policies is fraught with a number of practical issues and entails risks that are not directly related to longevity. This may reduce the efficiency of a direct investment in physical policies. For these reasons, a synthetic longevity market has evolved. The number of parties involved in a synthetic longevity transaction is typically smaller and the broker-dealer transferring the longevity exposure will be retaining most or all of the risks a physical investment entails. Finally, we describe the main methods used in the market to evaluate life settlement investments and the role of life expectancy providers.

Polymorphs solvates and co-crystals of molecular materials

The scope of my research project is to produce and characterize new crystalline forms of organic compounds, focusing the attention on co-crystals and then transferring these notions on APIs to produce co-crystals of potential interest in the pharmaceutical field. In the first part of this work co-crystallization experiments were performed using as building blocks the family of aliphatic dicarboxylic acids HOOC-(CH2)n-COOH, with n= 2-8. This class of compounds has always been an object of study because it is characterized by an interesting phenomenon of alternation of melting points: the acids with an even number of carbon atoms show a melting point higher than those with an odd one. The acids were co-crystallized with four dipyridyl molecules (formed by two pyridine rings with a different number of bridging carbon atoms) through the formation of intermolecular interactions N•••(H)O. The bases used were: 4,4’-bipyridine (BPY), 1,2-bis(4-pyridyl)ethane (BPA), 1,2-(di-4-pyridyl)ethylene (BPE) and 1,2-bis(4-pyridyl)propane (BPP). The co-crystals obtained by solution synthesis were characterized by different solid-state techniques to determine the structure and to see how the melting points in co-crystals change. In the second part of this study we tried to obtain new crystal forms of compounds of pharmaceutical interest. The APIs studied are: O-desmethylvenlafaxine, Lidocaine, Nalidixic Acid and Sulfadiazine. Each API was subjected to Polymorph Screening and Salt/Co-crystal Screening experiments to identify new crystal forms characterized by different properties. In a typical Salt/Co-crystal Screening the sample was made to react with a co-former (solid or liquid) through different methods: crystallization by solution, grinding, kneading and solid-gas reactions. The new crystal forms obtained were characterized by different solid state techniques (X-ray single crystal diffraction, X-ray powder diffraction, Differential Scanning Calorimetry, Thermogravimetric Analysis, Evolved gas analysis, FT-IR – ATR, Solid State N.M.R).

Studio numerico e sperimentale delle miscele di aggregati per i conglomerati bituminosi

I crescenti volumi di traffico che interessano le pavimentazioni stradali causano sollecitazioni tensionali di notevole entità che provocano danni permanenti alla sovrastruttura. Tali danni ne riducono la vita utile e comportano elevati costi di manutenzione. Il conglomerato bituminoso è un materiale multifase composto da inerti, bitume e vuoti d'aria. Le proprietà fisiche e le prestazioni della miscela dipendono dalle caratteristiche dell'aggregato, del legante e dalla loro interazione. L’approccio tradizionalmente utilizzato per la modellazione numerica del conglomerato bituminoso si basa su uno studio macroscopico della sua risposta meccanica attraverso modelli costitutivi al continuo che, per loro natura, non considerano la mutua interazione tra le fasi eterogenee che lo compongono ed utilizzano schematizzazioni omogenee equivalenti. Nell’ottica di un’evoluzione di tali metodologie è necessario superare questa semplificazione, considerando il carattere discreto del sistema ed adottando un approccio di tipo microscopico, che consenta di rappresentare i reali processi fisico-meccanici dai quali dipende la risposta macroscopica d’insieme. Nel presente lavoro, dopo una rassegna generale dei principali metodi numerici tradizionalmente impiegati per lo studio del conglomerato bituminoso, viene approfondita la teoria degli Elementi Discreti Particellari (DEM-P), che schematizza il materiale granulare come un insieme di particelle indipendenti che interagiscono tra loro nei punti di reciproco contatto secondo appropriate leggi costitutive. Viene valutata l’influenza della forma e delle dimensioni dell’aggregato sulle caratteristiche macroscopiche (tensione deviatorica massima) e microscopiche (forze di contatto normali e tangenziali, numero di contatti, indice dei vuoti, porosità, addensamento, angolo di attrito interno) della miscela. Ciò è reso possibile dal confronto tra risultati numerici e sperimentali di test triassiali condotti su provini costituiti da tre diverse miscele formate da sfere ed elementi di forma generica.