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.

Characterization of the Staphylococcus aureus bone sialoprotein-binding protein SdrE and the serine protease EpiP

In an attempt to develop a Staphylococcus aureus vaccine, we have applied reverse vaccinology approach, mainly based on in silico screening and proteomics. By using this approach SdrE, a protein belonging to serine-aspartate repeat protein family was identified as potential vaccine antigen against S. aureus. We have investigated the biochemical properties as well as the vaccine potential of SdrE and its highly conserved CnaBE3 domain. We found the protein SdrE to be resistant to trypsin. Further analysis of the resistant fragment revealed that it comprises a CnaBE3 domain, which also showed partial trypsin resistant behavior. Furthermore, intact mass spectrometry of rCnaBE3 suggested the possible presence of isopeptide bond or some other post-translational modification in the protein.However, this observation needs further investigation. Differential Scanning Fluorimetry study reveals that calcium play role in protein folding and provides stability to SdrE. At the end we have demonstrated that SdrE is immunogenic against clinical strain of S. aureus in murine abscess model. In the second part, I characterized a protein, annotated as epidermin leader peptide processing serine protease (EpiP), as a novel S. aureus vaccine candidate. The crystal structure of the rEpiP was solved at 2.05 Å resolution by x-ray crystallography . The structure showed that rEpiP was cleaved somewhere between residues 95 and 100 and cleavage occurs through an autocatalytic intra-molecular mechanism. In addition, the protein expressed by S. aureus cells also appeared to undergo a similar processing event. To determine if the protein acts as a serine protease, we mutated the catalytic serine 393 residue to alanine, generating rEpiP-S393A and solved its crystal structure at a resolution of 1.95 Å. rEpiP-S393A was impaired in its protease activity, as expected. Protective efficacy of rEpiP and the non-cleaving mutant protein was comparable, implying that the two forms are interchangeable for vaccination purposes.

Characterization of the structure and iron uptake mechanisms of the Staphylococcus aureus ferric hydroxamate-binding lipoprotein FhuD2

The Reverse Vaccinology (RV) approach allows using genomic information for the delineation of new protein-based vaccines starting from an in silico analysis. The first powerful example of the application of the RV approach is given by the development of a protein-based vaccine against serogroup B Meningococcus. A similar approach was also used to identify new Staphylococcus aureus vaccine candidates, including the ferric hydroxamate-binding lipoprotein FhuD2. S. aureus is a widespread human pathogen, which employs various different strategies for iron uptake, including: (i) siderophore-mediated iron acquisition using the endogenous siderophores staphyloferrin A and B, (ii) siderophore-mediated iron acquisition using xeno-siderophores (the pathway exploited by FhuD2) and (iii) heme-mediated iron acquisition. In this work the high resolution crystal structure of FhuD2 in the iron (III)-siderophore-bound form was determined. FhuD2 belongs to the Periplasmic Binding Protein family (PBP ) class III, and is principally formed by two globular domains, at the N- and C-termini of the protein, that make up a cleft where ferrichrome-iron (III) is bound. The N- and C-terminal domains, connected by a single long α-helix, present Rossmann-like folds, showing a β-stranded core and an α-helical periphery, which do not undergo extensive structural rearrangement when they interact with the ligand, typical of class III PBP members. The structure shows that ferrichrome-bound iron does not come directly into contact with the protein; rather, the metal ion is fully coordinated by six oxygen donors of the hydroxamate groups of three ornithine residues, which, with the three glycine residues, make up the peptide backbone of ferrichrome. Furthermore, it was found that iron-free ferrichrome is able to subtract iron from transferrin. This study shows for the first time the structure of FhuD2, which was found to bind to siderophores ,and that the protein plays an important role in S. aureus colonization and infection phases.