Uncovering the structure and function of Pseudomonas aeruginosa periplasmic proteins by an in silico approach.

Pseudomonas aeruginosa is an opportunistic human pathogen highly relevant from a biomedical viewpoint. It is one of the main causes of infection in hospitalized patients and a major cause of mortality of cystic fibrosis patients. This is also due to its ability to develop resistance to antibiotics by various mechanisms. Therefore, it is urgent and desirable to identify novel targets for the development of new antibacterial drugs against Pseudomonas aeruginosa. In this work this problem was tackled by an in silico approach aimed at providing a reliable structural model and functional annotation for the Pseudomonas aeruginosa periplasmic proteins for which these data are not available yet. A total of 83 protein sequences were analyzed, and the corresponding structural models were built, leading to the identification of 32 periplasmic 'substrate-binding proteins', 14 enzymes and 4 proteins with different functions, including lipids and metals binding. The most interesting cases were found within the 'enzymes' group with the identification of a lipase, which can be regarded as a virulence factor, a protease involved in the assembly of ß-barrel membrane proteins and a l,d-transpeptidase, which could contribute to confer resistance to ß-lactam antibiotics to the bacterium.Communicated by Ramaswamy H. Sarma.

Peptidomimetic Targeting of Cavß2 Overcomes Dysregulation of the L-Type Calcium Channel Density and Recovers Cardiac Function.

BACKGROUND: L-type calcium channels (LTCCs) play important roles in regulating cardiomyocyte physiology, which is governed by appropriate LTCC trafficking to and density at the cell surface. Factors influencing the expression, half-life, subcellular trafficking, and gating of LTCCs are therefore critically involved in conditions of cardiac physiology and disease. METHODS: Yeast 2-hybrid screenings, biochemical and molecular evaluations, protein interaction assays, fluorescence microscopy, structural molecular modeling, and functional studies were used to investigate the molecular mechanisms through which the LTCC Cavß2 chaperone regulates channel density at the plasma membrane. RESULTS: On the basis of our previous results, we found a direct linear correlation between the total amount of the LTCC pore-forming Cavα1.2 and the Akt-dependent phosphorylation status of Cavß2 both in a mouse model of diabetic cardiac disease and in 6 diabetic and 7 nondiabetic cardiomyopathy patients with aortic stenosis undergoing aortic valve replacement. Mechanistically, we demonstrate that a conformational change in Cavß2 triggered by Akt phosphorylation increases LTCC density at the cardiac plasma membrane, and thus the inward calcium current, through a complex pathway involving reduction of Cavα1.2 retrograde trafficking and protein degradation through the prevention of dynamin-mediated LTCC endocytosis; promotion of Cavα1.2 anterograde trafficking by blocking Kir/Gem-dependent sequestration of Cavß2, thus facilitating the chaperoning of Cavα1.2; and promotion of Cavα1.2 transcription by the prevention of Kir/Gem-mediated shuttling of Cavß2 to the nucleus, where it limits the transcription of Cavα1.2 through recruitment of the heterochromatin protein 1γ epigenetic repressor to the Cacna1c promoter. On the basis of this mechanism, we developed a novel mimetic peptide that, through targeting of Cavß2, corrects LTCC life-cycle alterations, facilitating the proper function of cardiac cells. Delivery of mimetic peptide into a mouse model of diabetic cardiac disease associated with LTCC abnormalities restored impaired calcium balance and recovered cardiac function. CONCLUSIONS: We have uncovered novel mechanisms modulating LTCC trafficking and life cycle and provide proof of concept for the use of Cavß2 mimetic peptide as a novel therapeutic tool for the improvement of cardiac conditions correlated with alterations in LTCC levels and function.

Sequence and Structure Analysis of Distantly-Related Viruses Reveals Extensive Gene Transfer between Viruses and Hosts and among Viruses.

The origin and evolution of viruses is a subject of ongoing debate. In this study, we provide a full account of the evolutionary relationships between proteins of significant sequence and structural similarity found in viruses that belong to different classes according to the Baltimore classification. We show that such proteins can be found in viruses from all Baltimore classes. For protein families that include these proteins, we observe two patterns of the taxonomic spread. In the first pattern, they can be found in a large number of viruses from all implicated Baltimore classes. In the other pattern, the instances of the corresponding protein in species from each Baltimore class are restricted to a few compact clades. Proteins with the first pattern of distribution are products of so-called viral hallmark genes reported previously. Additionally, this pattern is displayed by the envelope glycoproteins from Flaviviridae and Bunyaviridae and helicases of superfamilies 1 and 2 that have homologs in cellular organisms. The second pattern can often be explained by horizontal gene transfer from the host or between viruses, an example being Orthomyxoviridae and Coronaviridae hemagglutinin esterases. Another facet of horizontal gene transfer comprises multiple independent introduction events of genes from cellular organisms into otherwise unrelated viruses.

LIBRA: LIgand Binding site Recognition Application.

MOTIVATION: In recent years, structural genomics and ab initio molecular modeling activities are leading to the availability of a large number of structural models of proteins whose biochemical function is not known. The aim of this study was the development of a novel software tool that, given a protein's structural model, predicts the presence and identity of active sites and/or ligand binding sites. RESULTS: The algorithm implemented by ligand binding site recognition application (LIBRA) is based on a graph theory approach to find the largest subset of similar residues between an input protein and a collection of known functional sites. The algorithm makes use of two predefined databases for active sites and ligand binding sites, respectively, derived from the Catalytic Site Atlas and the Protein Data Bank. Tests indicate that LIBRA is able to identify the correct binding/active site in 90% of the cases analyzed, 90% of which feature the identified site as ranking first. As far as ligand binding site recognition is concerned, LIBRA outperforms other structure-based ligand binding sites detection tools with which it has been compared. AVAILABILITY AND IMPLEMENTATION: The application, developed in Java SE 7 with a Swing GUI embedding a JMol applet, can be run on any OS equipped with a suitable Java Virtual Machine (JVM), and is available at the following URL: http://www.computationalbiology.it/software/LIBRAv1.zip.

A general computational approach for repeat protein design.

Repeat proteins have considerable potential for use as modular binding reagents or biomaterials in biomedical and nanotechnology applications. Here we describe a general computational method for building idealized repeats that integrates available family sequences and structural information with Rosetta de novo protein design calculations. Idealized designs from six different repeat families were generated and experimentally characterized; 80% of the proteins were expressed and soluble and more than 40% were folded and monomeric with high thermal stability. Crystal structures determined for members of three families are within 1Å root-mean-square deviation to the design models. The method provides a general approach for fast and reliable generation of stable modular repeat protein scaffolds.

ASSIST: a fast versatile local structural comparison tool.

MOTIVATION: Structural genomics initiatives are increasingly leading to the determination of the 3D structure of target proteins whose catalytic function is not known. The aim of this work was that of developing a novel versatile tool for searching structural similarity, which allows to predict the catalytic function, if any, of these proteins. RESULTS: The algorithm implemented by the tool is based on local structural comparison to find the largest subset of similar residues between an input protein and known functional sites. The method uses a geometric hashing approach where information related to residue pairs from the input structures is stored in a hash table and then is quickly retrieved during the comparison step. Tests on proteins belonging to different functional classes, done using the Catalytic Site Atlas entries as targets, indicate that the algorithm is able to identify the correct functional class of the input protein in the vast majority of the cases. AVAILABILITY AND IMPLEMENTATION: The application was developed in Java SE 6, with a Java Swing Graphic User Interface (GUI). The system can be run locally on any operating system (OS) equipped with a suitable Java Virtual Machine, and is available at the following URL: http://www.computationalbiology.it/software/ASSISTv1.zip.

GA/GB fold switching may modulate fatty acid transfer from human serum albumin to bacteria.

Human serum albumin (HSA) accounts for most of the functions of plasma. Among others, HSA serves as a carrier and a solubilizer for many endogenous and exogenous ligands, including fatty acids (FAs) as well as peptides and proteins such as the GA module of the bacterial poly(A)-binding (PAB) protein. Although the biological function(s) of the GA module of the bacterial PAB protein is unknown, the acquisition of the GA module adds selective advantages to the bacterium in terms of growth rate and increase in virulence, probably by providing the bacteria with FAs and, possibly, other nutrients transported by HSA. Here, we hypothesize that the GA module may undergo a structural transition from the all-α form to the 4ß+α form typical of the GB domains upon binding of a FA molecule, as part of the mechanism which allows the bacterial PAB protein to extract FAs from HSA.