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.

Reactivity of activated electrophiles and nucleophiles: labile intermediates and properties of the reaction products

The main topic of my Ph.D. thesis is the study of nucleophilic and electrophilic aromatic substitution reaction, in particular from a mechanistic point of view. The research was mainly focused on the reactivity of superactivated aromatic systems. In spite of their high reactivity (hence the high reaction’s rate), we were able to identify and in some case to isolate -complexes until now only hypothesized. For example, interesting results comes from the study of the protonation of the supernucleophiles tris(dialkylamino)benzenes. However, the best result obtained in this field was the isolation and structural characterization of the first stables zwitterionic Wheland-Meisenheimer complexes by using 2,4-dipyrrolidine-1,3-thiazole as supernucleophile and 4,6-dinitrobenzofuroxan or 4,6-dinitrotetrazolepyridine as superelectrophile. These reactions were also studied by means of computational chemistry, which allowed us to better investigate on the energetic and properties of the reactions and reactants studied. We also discovered, in some case fortuitously, some relevant properties and application of the compounds we synthesized, such as fluorescence in solid state and nanoparticles, or textile dyeing. We decided to investigate all these findings also by collaborating with other research groups. During a period in the “Laboratoire de Structure et Réactivité des Systèmes Moléculaires Complexes-SRSMC, Université de Lorraine et CNRS, France, I carried out computational studies on new iron complexes for the use as dyes in Dye Sensitized Solar Cells (DSSC). Furthermore, thanks to this new expertise, I was involved in a collaboration for the study of the ligands’ interaction in biological systems. A collaboration with University of Urbino allowed us to investigate on the reactivity of 1,2-diaza-1,3-dienes toward nucleophiles such as amino and phosphine derivatives, which led to the synthesis of new products some of which are 6 or 7 member heterocycles containing both phosphorus and nitrogen atoms.

Spectroscopic investigation on photoreactivity, structure and polymorphism of organic molecular crystals

The study of the spectroscopic phenomena in organic solids, in combination with other techniques, is an effective tool for the understanding of the structural properties of materials based on these compounds. This Ph.D. work was dedicated to the spectroscopic investigation of some relevant processes occurring in organic molecular crystals, with the goal of expanding the knowledge on the relationship between structure, dynamics and photoreactivity of these systems. Vibrational spectroscopy has been the technique of choice, always in combination with X-ray diffraction structural studies and often the support of computational methods. The vibrational study of the molecular solid state reaches its full potential when it includes the low-wavenumber region of the lattice-phonon modes, which probe the weak intermolecular interactions and are the fingerprints of the lattice itself. Microscopy is an invaluable addition in the investigation of processes that take place in the micro-meter scale of the crystal micro-domains. In chemical and phase transitions, as well as in polymorph screening and identification, the combination of Raman microscopy and lattice-phonon detection has provided useful information. Research on the fascinating class of single-crystal-to-single-crystal photoreactions, has shown how the homogeneous mechanism of these transformations can be identified by lattice-phonon microscopy, in agreement with the continuous evolution of their XRD patterns. On describing the behavior of the photodimerization mechanism of vitamin K3, the focus was instead on the influence of its polymorphism in governing the product isomerism. Polymorphism is the additional degree of freedom of molecular functional materials, and by advancing in its control and properties, functionalities can be promoted for useful applications. Its investigation focused on thin-film phases, widely employed in organic electronics. The ambiguities in phase identification often emerging by other experimental methods were successfully solved by vibrational measurements.