How hydrophobicity shapes the architecture of protein assemblies.

The interactions that give rise to protein self-assembly are basically electrical and hydrophobic in origin. The electrical interactions are approached in this study as the interaction between electrostatic dipoles originated by the asymmetric distribution of their charged amino acids. However, hydrophobicity is not easily derivable from basic physicochemical principles. Its treatment is carried out here considering a hydrophobic force field originated by "hydrophobic charges". These charges are indices obtained experimentally from the free energies of transferring amino acids from polar to hydrophobic media. Hydrophobic dipole moments are used here in a manner analogous to electric dipole moments, and an empirical expression of interaction energy between hydrophobic dipoles is derived. This methodology is used with two examples of self-assembly systems of different complexity. It was found that the hydrophobic dipole moments of proteins tend to interact in such a way that they align parallel to each other in a completely analogous way to how phospholipids are oriented in biological membranes to form the well-known double layer. In this biological membrane model (BM model), proteins tend to interact in a similar way, although in this case this alignment is modulated by the tendency of the corresponding electrostatic dipoles to counter-align. Helical conformation of influenza virus PDBid: 6Z5L. Two monomers are shown in cyan and green. The corresponding dipole moment vectors are shown in red (electric dipoles) and blue (hydrophobic dipoles). From the inset figure, it can be seen that the growth of the helix is due to electrical attraction of the monomers, overcoming a hydrophobic repulsion (see text).

The importance of hydrophobic interactions in the structure of transcription systems.

Hydrophobic forces play a crucial role in both the stability of B DNA and its interactions with proteins. In the present study, we postulate that the hydrophobic effect is an essential component in establishing specificity in the interaction transcription factor proteins with their consensus DNA sequence partners. The PDB coordinates of more than 50 transcription systems have been used to analyze the hydrophobic attraction of proteins towards their DNA consensus. This analysis includes computing the hydrophobic energy of the interacting molecules by means of their hydrophobic moments. Hydrophobic moments have successfully been used in previous studies involving self-assembly protein systems. In the present case, in spite of some variability, we found specificity in transcription factors when interacting with their respective consensus DNA sequences. By applying our model of biological membrane pattern for hydrophobic interactions, we postulate that hydrophobic forces constitute the necessary intermediate interaction between the unspecific electrostatic attraction for DNA phosphate groups and the very short-range interaction promoting hydrogen bonds. We conclude that hydrophobic interactions serve as the intermediate force guiding transcriptions factors towards the proper hydrogen bonds to their DNAs.

MultitaskProtDB-II: an update of a database of multitasking/moonlighting proteins.

Multitasking, or moonlighting, is the capability of some proteins to execute two or more biological functions. MultitaskProtDB-II is a database of multifunctional proteins that has been updated. In the previous version, the information contained was: NCBI and UniProt accession numbers, canonical and additional biological functions, organism, monomeric/oligomeric states, PDB codes and bibliographic references. In the present update, the number of entries has been increased from 288 to 694 moonlighting proteins. MultitaskProtDB-II is continually being curated and updated. The new database also contains the following information: GO descriptors for the canonical and moonlighting functions, three-dimensional structure (for those proteins lacking PDB structure, a model was made using Itasser and Phyre), the involvement of the proteins in human diseases (78% of human moonlighting proteins) and whether the protein is a target of a current drug (48% of human moonlighting proteins). These numbers highlight the importance of these proteins for the analysis and explanation of human diseases and target-directed drug design. Moreover, 25% of the proteins of the database are involved in virulence of pathogenic microorganisms, largely in the mechanism of adhesion to the host. This highlights their importance for the mechanism of microorganism infection and vaccine design. MultitaskProtDB-II is available at http://wallace.uab.es/multitaskII.

Vector description of electric and hydrophobic interactions in protein homodimers.

This article describes the formation of homodimers from their constituting monomers, based on the rules set by a simple model of electric and hydrophobic interactions. These interactions are described in terms of the electric dipole moment (D) and hydrophobic moment vectors (H) of proteins. The distribution of angles formed by the two dipole moments of monomers constituting dimers were analysed, as well as the distribution of angles formed by the two hydrophobic moments. When these distributions were fitted to Gaussian curves, it was found that for biological dimers, the D vectors tend mostly to adopt a perpendicular arrangement with respect to each other, in which the constituting dipoles have the least interaction. A minor population tends towards an antiparallel arrangement implying maximum electric attraction. Also in biological dimers, the H vectors of most monomers tend to interact in such a way that the total hydrophobic moment of the dimer increases with respect to those of the monomers. This shows that hydrophobic moments have a tendency to align. In dimers originating in the crystallisation process, the distribution of angles formed by both hydrophobic and electric dipole moments appeared rather featureless, probably because of unspecific interactions in the crystallisation processes. The model does not describe direct interactions between H and D vectors although the distribution of angles formed by both vectors in dimers was analysed. It was found that in most cases these angles tended to be either small (both moments aligned parallel to each other) or large (antiparallel disposition).

MultitaskProtDB: a database of multitasking proteins.

We have compiled MultitaskProtDB, available online at http://wallace.uab.es/multitask, to provide a repository where the many multitasking proteins found in the literature can be stored. Multitasking or moonlighting is the capability of some proteins to execute two or more biological functions. Usually, multitasking proteins are experimentally revealed by serendipity. This ability of proteins to perform multitasking functions helps us to understand one of the ways used by cells to perform many complex functions with a limited number of genes. Even so, the study of this phenomenon is complex because, among other things, there is no database of moonlighting proteins. The existence of such a tool facilitates the collection and dissemination of these important data. This work reports the database, MultitaskProtDB, which is designed as a friendly user web page containing >288 multitasking proteins with their NCBI and UniProt accession numbers, canonical and additional biological functions, monomeric/oligomeric states, PDB codes when available and bibliographic references. This database also serves to gain insight into some characteristics of multitasking proteins such as frequencies of the different pairs of functions, phylogenetic conservation and so forth.

MGDB: crossing the marker genes of a user microarray with a database of public-microarrays marker genes.

SUMMARY: The microarrays performed by scientific teams grow exponentially. These microarray data could be useful for researchers around the world, but unfortunately they are underused. To fully exploit these data, it is necessary (i) to extract these data from a repository of the high-throughput gene expression data like Gene Expression Omnibus (GEO) and (ii) to make the data from different microarrays comparable with tools easy to use for scientists. We have developed these two solutions in our server, implementing a database of microarray marker genes (Marker Genes Data Base). This database contains the marker genes of all GEO microarray datasets and it is updated monthly with the new microarrays from GEO. Thus, researchers can see whether the marker genes of their microarray are marker genes in other microarrays in the database, expanding the analysis of their microarray to the rest of the public microarrays. This solution helps not only to corroborate the conclusions regarding a researcher's microarray but also to identify the phenotype of different subsets of individuals under investigation, to frame the results with microarray experiments from other species, pathologies or tissues, to search for drugs that promote the transition between the studied phenotypes, to detect undesirable side effects of the treatment applied, etc. Thus, the researcher can quickly add relevant information to his/her studies from all of the previous analyses performed in other studies as long as they have been deposited in public repositories. AVAILABILITY: Marker-gene database tool: http://ibb.uab.es/mgdb

Can bioinformatics help in the identification of moonlighting proteins?

Protein multitasking or moonlighting is the capability of certain proteins to execute two or more unique biological functions. This ability to perform moonlighting functions helps us to understand one of the ways used by cells to perform many complex functions with a limited number of genes. Usually, moonlighting proteins are revealed experimentally by serendipity, and the proteins described probably represent just the tip of the iceberg. It would be helpful if bioinformatics could predict protein multifunctionality, especially because of the large amounts of sequences coming from genome projects. In the present article, we describe several approaches that use sequences, structures, interactomics and current bioinformatics algorithms and programs to try to overcome this problem. The sequence analysis has been performed: (i) by remote homology searches using PSI-BLAST, (ii) by the detection of functional motifs, and (iii) by the co-evolutionary relationship between amino acids. Programs designed to identify functional motifs/domains are basically oriented to detect the main function, but usually fail in the detection of secondary ones. Remote homology searches such as PSI-BLAST seem to be more versatile in this task, and it is a good complement for the information obtained from protein-protein interaction (PPI) databases. Structural information and mutation correlation analysis can help us to map the functional sites. Mutation correlation analysis can be used only in very restricted situations, but can suggest how the evolutionary process of the acquisition of the second function took place.

Sheltering DNA in self-organizing, protein-only nano-shells as artificial viruses for gene delivery.

By recruiting functional domains supporting DNA condensation, cell binding, internalization, endosomal escape and nuclear transport, modular single-chain polypeptides can be tailored to associate with cargo DNA for cell-targeted gene therapy. Recently, an emerging architectonic principle at the nanoscale has permitted tagging protein monomers for self-organization as protein-only nanoparticles. We have studied here the accommodation of plasmid DNA into protein nanoparticles assembled with the synergistic assistance of end terminal poly-arginines (R9) and poly-histidines (H6). Data indicate a virus-like organization of the complexes, in which a DNA core is surrounded by a solvent-exposed protein layer. This finding validates end-terminal cationic peptides as pleiotropic tags in protein building blocks for the mimicry of viral architecture in artificial viruses, representing a promising alternative to the conventional use of viruses and virus-like particles for nanomedicine and gene therapy. FROM THE CLINICAL EDITOR: Finding efficient gene delivery methods still represents a challenge and is one of the bottlenecks to the more widespread application of gene therapy. The findings presented in this paper validate the application of end-terminal cationic peptides as pleiotropic tags in protein building blocks for "viral architecture mimicking" in artificial viruses, representing a promising alternative to the use of viruses and virus-like particles for gene delivery.

Role of Moonlighting Proteins in Disease: Analyzing the Contribution of Canonical and Moonlighting Functions in Disease Progression.

The term moonlighting proteins refers to those proteins that present alternative functions performed by a single polypeptide chain acquired throughout evolution (called canonical and moonlighting, respectively). Over 78% of moonlighting proteins are involved in human diseases, 48% are targeted by current drugs, and over 25% of them are involved in the virulence of pathogenic microorganisms. These facts encouraged us to study the link between the functions of moonlighting proteins and disease. We found a large number of moonlighting functions activated by pathological conditions that are highly involved in disease development and progression. The factors that activate some moonlighting functions take place only in pathological conditions, such as specific cellular translocations or changes in protein structure. Some moonlighting functions are involved in disease promotion while others are involved in curbing it. The disease-impairing moonlighting functions attempt to restore the homeostasis, or to reduce the damage linked to the imbalance caused by the disease. The disease-promoting moonlighting functions primarily involve the immune system, mesenchyme cross-talk, or excessive tissue proliferation. We often find moonlighting functions linked to the canonical function in a pathological context. Moonlighting functions are especially coordinated in inflammation and cancer. Wound healing and epithelial to mesenchymal transition are very representative. They involve multiple moonlighting proteins with a different role in each phase of the process, contributing to the current-phase phenotype or promoting a phase switch, mitigating the damage or intensifying the remodeling. All of this implies a new level of complexity in the study of pathology genesis, progression, and treatment. The specific protein function involved in a patient's progress or that is affected by a drug must be elucidated for the correct treatment of diseases.

RGD-based cell ligands for cell-targeted drug delivery act as potent trophic factors.

Integrin-binding, Arg-Gly-Asp (RGD)-containing peptides are the most widely used agents to deliver drugs, nanoparticles, and imaging agents. Although in nature, several protein-mediated signal transduction events depend on RGD motifs, the potential of RGD-empowered materials in triggering undesired cell-signaling cascades has been neglected. Using an RGD-functionalized protein nanoparticle, we show here that the RGD motif acts as a powerful trophic factor, supporting extracellular signal-regulated kinase 1/2 (ERK1/2)-linked cell proliferation and partial differentiation of PC12 cells, a neuronlike model. FROM THE CLINICAL EDITOR: This work focuses on RGD peptides, which are among the most commonly used tags for targeted drug delivery. They also promote protoneurite formation and expression of neuronal markers (MAP2) in model PC12 cells, which is an unexpected but relevant event in the functionalization of drugs and their nanocarriers.

Self-assembling, protein-based intracellular bacterial organelles: emerging vehicles for encapsulating, targeting and delivering therapeutical cargoes.

Many bacterial species contain intracellular nano- and micro-compartments consisting of self-assembling proteins that form protein-only shells. These structures are built up by combinations of a reduced number of repeated elements, from 60 repeated copies of one unique structural element self-assembled in encapsulins of 24 nm to 10,000-20,000 copies of a few protein species assembled in a organelle of around 100-150 nm in cross-section. However, this apparent simplicity does not correspond to the structural and functional sophistication of some of these organelles. They package, by not yet definitely solved mechanisms, one or more enzymes involved in specific metabolic pathways, confining such reactions and sequestering or increasing the inner concentration of unstable, toxics or volatile intermediate metabolites. From a biotechnological point of view, we can use the self assembling properties of these particles for directing shell assembling and enzyme packaging, mimicking nature to design new applications in biotechnology. Upon appropriate engineering of the building blocks, they could act as a new family of self-assembled, protein-based vehicles in Nanomedicine to encapsulate, target and deliver therapeutic cargoes to specific cell types and/or tissues. This would provide a new, intriguing platform of microbial origin for drug delivery.

Biological activities of histidine-rich peptides; merging biotechnology and nanomedicine.

Histidine-rich peptides are commonly used in recombinant protein production as purification tags, allowing the one-step affinity separation of the His-tagged proteins from the extracellular media or cell extracts. Genetic engineering makes feasible the post-purification His-tag removal by inserting, between the tag and the main protein body, a target site for trans-acting proteases or a self-proteolytic peptide with regulatable activities. However, for technical ease, His tags are often not removed and the fusion proteins eventually used in this form. In this commentary, we revise the powerful biological properties of histidine-rich peptides as endosomolytic agents and as architectonic tags in nanoparticle formation, for which they are exploited in drug delivery and other nanomedical applications. These activities, generally unknown to biotechnologists, can unwillingly modulate the functionality and biotechnological performance of recombinant proteins in which they remain trivially attached.

Pathogen Moonlighting Proteins: From Ancestral Key Metabolic Enzymes to Virulence Factors.

Moonlighting and multitasking proteins refer to proteins with two or more functions performed by a single polypeptide chain. An amazing example of the Gain of Function (GoF) phenomenon of these proteins is that 25% of the moonlighting functions of our Multitasking Proteins Database (MultitaskProtDB-II) are related to pathogen virulence activity. Moreover, they usually have a canonical function belonging to highly conserved ancestral key functions, and their moonlighting functions are often involved in inducing extracellular matrix (ECM) protein remodeling. There are three main questions in the context of moonlighting proteins in pathogen virulence: (A) Why are a high percentage of pathogen moonlighting proteins involved in virulence? (B) Why do most of the canonical functions of these moonlighting proteins belong to primary metabolism? Moreover, why are they common in many pathogen species? (C) How are these different protein sequences and structures able to bind the same set of host ECM protein targets, mainly plasminogen (PLG), and colonize host tissues? By means of an extensive bioinformatics analysis, we suggest answers and approaches to these questions. There are three main ideas derived from the work: first, moonlighting proteins are not good candidates for vaccines. Second, several motifs that might be important in the adhesion to the ECM were identified. Third, an overrepresentation of GO codes related with virulence in moonlighting proteins were seen.

Rational engineering of a human GFP-like protein scaffold for humanized targeted nanomedicines.

Green fluorescent protein (GFP) is a widely used scaffold for protein-based targeted nanomedicines because of its high biocompatibility, biological neutrality and outstanding structural stability. However, being immunogenicity a major concern in the development of drug carriers, the use of exogenous proteins such as GFP in clinics might be inadequate. Here we report a human nidogen-derived protein (HSNBT), rationally designed to mimic the structural and functional properties of GFP as a scaffold for nanomedicine. For that, a GFP-like ß-barrel, containing the G2 domain of the human nidogen, has been rationally engineered to obtain a biologically neutral protein that self-assembles as 10nm-nanoparticles. This scaffold is the basis of a humanized nanoconjugate, where GFP, from the well-characterized protein T22-GFP-H6, has been substituted by the nidogen-derived GFP-like HSNBT protein. The resulting construct T22-HSNBT-H6, is a humanized CXCR4-targeted nanoparticle that selectively delivers conjugated genotoxic Floxuridine into cancer CXCR4+ cells. Indeed, the administration of T22-HSNBT-H6-FdU in a CXCR4-overexpressing colorectal cancer mouse model results in an even more efficient selective antitumoral effect than that shown by its GFP-counterpart, in absence of systemic toxicity. Therefore, the newly developed GFP-like protein scaffold appears as an ideal candidate for the development of humanized protein nanomaterials and successfully supports the tumor-targeted nanoscale drug T22-HSNBT-H6-FdU. STATEMENT OF SIGNIFICANCE: Targeted nanomedicine seeks for humanized and biologically neutral protein carriers as alternative of widely used but immunogenic exogenous protein scaffolds such as green fluorescent protein (GFP). This work reports for the first time the rational engineering of a human homolog of the GFP based in the human nidogen (named HSNBT) that shows full potential to be used in humanized protein-based targeted nanomedicines. This has been demonstrated in T22-HSNBT-H6-FdU, a humanized CXCR4-targeted protein nanoconjugate able to selectively deliver its genotoxic load into cancer cells.

DockAnalyse: an application for the analysis of protein-protein interactions.

BACKGROUND: Is it possible to identify what the best solution of a docking program is? The usual answer to this question is the highest score solution, but interactions between proteins are dynamic processes, and many times the interaction regions are wide enough to permit protein-protein interactions with different orientations and/or interaction energies. In some cases, as in a multimeric protein complex, several interaction regions are possible among the monomers. These dynamic processes involve interactions with surface displacements between the proteins to finally achieve the functional configuration of the protein complex. Consequently, there is not a static and single solution for the interaction between proteins, but there are several important configurations that also have to be analyzed. RESULTS: To extract those representative solutions from the docking output datafile, we have developed an unsupervised and automatic clustering application, named DockAnalyse. This application is based on the already existing DBscan clustering method, which searches for continuities among the clusters generated by the docking output data representation. The DBscan clustering method is very robust and, moreover, solves some of the inconsistency problems of the classical clustering methods like, for example, the treatment of outliers and the dependence of the previously defined number of clusters. CONCLUSIONS: DockAnalyse makes the interpretation of the docking solutions through graphical and visual representations easier by guiding the user to find the representative solutions. We have applied our new approach to analyze several protein interactions and model the dynamic protein interaction behavior of a protein complex. DockAnalyse might also be used to describe interaction regions between proteins and, therefore, guide future flexible dockings. The application (implemented in the R package) is accessible.

PCOPGene-Net: holistic characterisation of cellular states from microarray data based on continuous and non-continuous analysis of gene-expression relationships.

BACKGROUND: Microarray technology is so expensive and powerful that it is essential to extract maximum value from microarray data, specially from large-sample-series microarrays. Our web tools attempt to respond to these researchers' needs by facilitating the possibility to test and formulate from a hypothesis to entire models under a holistic point of view. RESULTS: PCOPGene-Net is a web application for facilitating the study of the relationships among gene expressions under microarray conditions, to classify these conditions and to study their effect on expression relationships. Furthermore, the system guides the researcher in the navigation through the microarray data by providing the most suitable genes and information for the researcher's interests at each moment. We achieve all of these by means of the zoom-out operation, the zoom-in operation, the non-continuous analysis and crossing the PCOPGene results with external data-servers. CONCLUSION: PCOPGene-Net helps to identify cellular states and the genes involved in these. All of that is accomplished in a flexible way, guided by the researcher's interests and taking advantage of the ability of our system to relate gene expressions, even when these relationships are non-continuous and cannot be found using linear or non-linear analytical methods. Currently, our tools are used for tumour-progression study from a holistic point of view.

Bioinformatics annotation of the hypothetical proteins found by omics techniques can help to disclose additional virulence factors.

The advent of genomics should have facilitated the identification of microbial virulence factors, a key objective for vaccine design. When the bacterial pathogen infects the host it expresses a set of genes, a number of them being virulence factors. Among the genes identified by techniques as microarrays, in vivo expression technology, signature-tagged mutagenesis and differential fluorescence induction there are many related to cellular stress, basal metabolism, etc., which cannot be directly involved in virulence, or at least cannot be considered useful candidates to be deleted for designing a live attenuated vaccine. Among the genes disclosed by these methodologies there are a number of hypothetical or unknown proteins. As they can hide some true virulence factors, we have reannotated all of these hypothetical proteins from several respiratory pathogens by a careful and in-depth analysis of each one. Although some of the re-annotations match with functions that can be related to microbial virulence, the identification of virulence factors remains difficult.

Analysis of nonlinear relations between expression profiles by the principal curves of oriented-points approach.

DNA microarray technology enables high-throughput gene expression analysis and allows researchers to test the activity of thousands of genes at one time in multiple cellular conditions. This approach is based on principal curves of oriented points (PCOP) analysis and minimum spanning trees to analyze temporal and nontemporal series data to relate the genes. PCOP is a very suitable method, non-hypothesis-driven, for nonlinear relationship recognition between multivariable sets of data. Initially, a gene-relations tree is generated from the correlation between each pair of genes, calculated by PCOP analysis. Next, the researcher can introduce the query genes to be studied into the zoom-in operation, and the system selects the genes which connect the previously provided ones, beyond the activation pathways, using the minimum spanning tree. Thus, this zoom-in operation generates the nonlinear pattern of the intraset expression behavior for the new gene set. This inner expression pattern relates the query and selected genes to study their mutual interdependence in detail. This detailed information is especially useful in the biomedical environment, where such information is not possible to obtain by applying the current analytical methods.

Prediction of protein function improving sequence remote alignment search by a fuzzy logic algorithm.

The functional annotation of the new protein sequences represents a major drawback for genomic science. The best way to suggest the function of a protein from its sequence is by finding a related one for which biological information is available. Current alignment algorithms display a list of protein sequence stretches presenting significant similarity to different protein targets, ordered by their respective mathematical scores. However, statistical and biological significance do not always coincide, therefore, the rearrangement of the program output according to more biological characteristics than the mathematical scoring would help functional annotation. A new method that predicts the putative function for the protein integrating the results from the PSI-BLAST program and a fuzzy logic algorithm is described. Several protein sequence characteristics have been checked in their ability to rearrange a PSI-BLAST profile according more to their biological functions. Four of them: amino acid content, matched segment length and hydropathic and flexibility profiles positively contributed, upon being integrated by a fuzzy logic algorithm into a program, BYPASS, to the accurate prediction of the function of a protein from its sequence.