LIBP-Pred: web server for lipid binding proteins using structural network parameters; PDB mining of human cancer biomarkers and drug targets in parasites and bacteria

Lipid-Binding Proteins (LIBPs) or Fatty Acid-Binding Proteins (FABPs) play an important role in many diseases such as different types of cancer, kidney injury, atherosclerosis, diabetes, intestinal ischemia and parasitic infections. Thus, the computational methods that can predict LIBPs based on 3D structure parameters became a goal of major importance for drug-target discovery, vaccine design and biomarker selection. In addition, the Protein Data Bank (PDB) contains 3000+ protein 3D structures with unknown function. This list, as well as new experimental outcomes in proteomics research, is a very interesting source to discover relevant proteins, including LIBPs. However, to the best of our knowledge, there are no general models to predict new LIBPs based on 3D structures. We developed new Quantitative Structure-Activity Relationship (QSAR) models based on 3D electrostatic parameters of 1801 different proteins, including 801 LIBPs. We calculated these electrostatic parameters with the MARCH-INSIDE software and they correspond to the entire protein or to specific protein regions named core, inner, middle, and surface. We used these parameters as inputs to develop a simple Linear Discriminant Analysis (LDA) classifier to discriminate 3D structure of LIBPs from other proteins. We implemented this predictor in the web server named LIBP-Pred, freely available at , along with other important web servers of the Bio-AIMS portal. The users can carry out an automatic retrieval of protein structures from PDB or upload their custom protein structural models from their disk created with LOMETS server. We demonstrated the PDB mining option performing a predictive study of 2000+ proteins with unknown function. Interesting results regarding the discovery of new Cancer Biomarkers in humans or drug targets in parasites have been discussed here in this sense.     

3D entropy and moments prediction of enzyme classes and experimental-theoretic study of peptide fingerprints in Leishmania parasites

The number of protein 3D structures without function annotation in Protein Data Bank (PDB) has been steadily increased. This fact has led in turn to an increment of demand for theoretical models to give a quick characterization of these proteins. In this work, we present a new and fast Markov chain model (MCM) to predict the enzyme classification (EC) number. We used both linear discriminant analysis (LDA) and/or artificial neural networks (ANN) in order to compare linear vs. non-linear classifiers. The LDA model found is very simple (three variables) and at the same time is able to predict the first EC number with an overall accuracy of 79% for a data set of 4755 proteins (859 enzymes and 3896 non-enzymes) divided into both training and external validation series. In addition, the best non-linear ANN model is notably more complex but has an overall accuracy of 98.85%. It is important to emphasize that this method may help us to predict not only new enzyme proteins but also to select peptide candidates found on the peptide mass fingerprints (PMFs) of new proteins that may improve enzyme activity. In order to illustrate the use of the model in this regard, we first report the 2D electrophoresis (2DE) and MADLI-TOF mass spectra characterization of the PMF of a new possible malate dehydrogenase sequence from Leishmania infantum. Next, we used the models to predict the contribution to a specific enzyme action of 30 peptides found in the PMF of the new protein. We implemented the present model in a server at portal Bio-AIMS (http://miaja.tic.udc.es/Bio-AIMS/EnzClassPred.php). This free on-line tool is based on PHP/HTML/Python and MARCH-INSIDE routines. This combined strategy may be used to identify and predict peptides of prokaryote and eukaryote parasites and their hosts as well as other superior organisms, which may be of interest in drug development or target identification.     

The C-terminus of Toxoplasma RON2 provides the crucial link between AMA1 and the host-associated invasion complex

Host cell invasion by apicomplexan parasites requires formation of the moving junction (MJ), a ring-like apposition between the parasite and host plasma membranes that the parasite migrates through during entry. The Toxoplasma MJ is a secreted complex including TgAMA1, a transmembrane protein on the parasite surface, and a complex of rhoptry neck proteins (TgRON2/4/5/8) described as host cell-associated. How these proteins connect the parasite and host cell has not previously been described. Here we show that TgRON2 localizes to the MJ and that two short segments flanking a hydrophobic stretch near its C-terminus (D3 and D4) independently associate with the ectodomain of TgAMA1. Pre-incubation of parasites with D3 (fused to glutathione S-transferase) dramatically reduces invasion but does not prevent injection of rhoptry bulb proteins. Hence, the entire C-terminal region of TgRON2 forms the crucial bridge between TgAMA1 and the rest of the MJ complex but this association is not required for rhoptry protein injection.     

A comparative view at comprehensive information resources on three-dimensional structures of biological macro-molecules.

The rapidly increasing amount of information on three-dimensional (3D) structures of biological macro-molecules has still an insufficient impact on genome analysis, functional genomics and proteomics as well as on many other fields in biomedicine including disease-related research. There are, however, attempts to make structural data more easily accessible to the bench biologist. As members of the world-wide Protein Data Bank (wwPDB), the RCSB Protein Data Bank (PDB), the Protein Data Bank Japan and the Macromolecular Structure Database are the primary information resources for 3D structures of proteins, nucleic acids, carbohydrates and complexes thereof. In addition, a number of secondary resources have been set up that also provide information on all currently known structures in a relatively comprehensive manner and not focusing on specific features only. They include PDBsum, the OCA browser-database for protein structure/function, the Molecular Modeling Database and the Jena Library of Biological Macromolecules--JenaLib. Both the primary and secondary resources often merge the information in the PDB files with data from other resources and offer additional analysis tools thereby adding value to the original PDB data. Here, we briefly describe these resources from a user's point of view and from a comparative perspective. It is our aim to guide researchers outside the structure biology field in getting the most out of the 3D structure resources.     

RCSB Protein Data Bank: Enabling biomedical research and drug discovery

Analyses of publicly available structural data reveal interesting insights into the impact of the three‐dimensional (3D) structures of protein targets important for discovery of new drugs (e.g., G‐protein‐coupled receptors, voltage‐gated ion channels, ligand‐gated ion channels, transporters, and E3 ubiquitin ligases). The Protein Data Bank (PDB) archive currently holds > 155,000 atomic‐level 3D structures of biomolecules experimentally determined using crystallography, nuclear magnetic resonance spectroscopy, and electron microscopy. The PDB was established in 1971 as the first open‐access, digital‐data resource in biology, and is now managed by the Worldwide PDB partnership (wwPDB; wwPDB.org ). US PDB operations are the responsibility of the Research Collaboratory for Structural Bioinformatics PDB (RCSB PDB). The RCSB PDB serves millions of RCSB.org users worldwide by delivering PDB data integrated with ～40 external biodata resources, providing rich structural views of fundamental biology, biomedicine, and energy sciences. Recently published work showed that the PDB archival holdings facilitated discovery of ～90% of the 210 new drugs approved by the US Food and Drug Administration 2010–2016. We review user‐driven development of RCSB PDB services, examine growth of the PDB archive in terms of size and complexity, and present examples and opportunities for structure‐guided drug discovery for challenging targets (e.g., integral membrane proteins).     

An antibody-based ELISA for quantification of Ani s 1, a major allergen from Anisakis simplex

Anisakis simplex is a nematode parasite that can infect humans who have eaten raw or undercooked seafood. Larvae invading the gastrointestinal mucosa excrete/secrete proteins that are implicated in the pathogenesis of anisakiasis and can induce IgE-mediated symptoms. Since Ani s 1 is a potent secreted allergen with important clinical relevance, its measurement could assess the quality of allergenic products used in diagnosis/immunotherapy of Anisakis allergy and track the presence of A. simplex parasites in fish foodstuffs. An antibody-based ELISA for quantification of Ani s 1 has been developed based on monoclonal antibody 4F2 as capture antibody and biotin-labelled polyclonal antibodies against Ani s 1 as detection reagent. The dose-response standard curves, obtained with natural and recombinant antigens, ranged from 4 to 2000 ng/ml and were identical and parallel to that of the A. simplex extract. The linear portion of the dose-response curve with nAni s 1 was between 15 and 250 ng/ml with inter-assay and intra-assays coefficients of variation less than 20% and 10%, respectively. The assay was specific since there was no cross-reaction with other extracts (except Ascaris extracts) and was highly sensitive (detection limit of 1.8 ng/ml), being able to detect Ani s 1 in fish extracts from codfish and monkfish.     

The Diagnosis of Human Fascioliasis by Enzyme-Linked Immunosorbent Assay (ELISA) Using Recombinant Cathepsin L Protease

Background

Fascioliasis is a worldwide parasitic disease of domestic animals caused by helminths of the genus Fasciola. In many parts of the world, particularly in poor rural areas where animal disease is endemic, the parasite also infects humans. Adult parasites reside in the bile ducts of the host and therefore diagnosis of human fascioliasis is usually achieved by coprological examinations that search for parasite eggs that are carried into the intestine with the bile juices. However, these methods are insensitive due to the fact that eggs are released sporadically and may be missed in low-level infections, and fasciola eggs may be misclassified as other parasites, leading to problems with specificity. Furthermore, acute clinical symptoms as a result of parasites migrating to the bile ducts appear before the parasite matures and begins egg laying. A human immune response to Fasciola antigens occurs early in infection. Therefore, an immunological method such as ELISA may be a more reliable, easy and cheap means to diagnose human fascioliasis than coprological analysis.

Methodology/Principal findings

Using a panel of serum from Fasciola hepatica-infected patients and from uninfected controls we have optimized an enzyme-linked immunosorbent assay (ELISA) which employs a recombinant form of the major F. hepatica cathepsin L1 as the antigen for the diagnosis of human fascioliasis. We examined the ability of the ELISA test to discern fascioliasis from various other helminth and non-helminth parasitic diseases.

Conclusions/Significance

A sensitive and specific fascioliasis ELISA test has been developed. This test is rapid and easy to use and can discriminate fasciola-infected individuals from patients harbouring other parasites with at least 99.9% sensitivity and 99.9% specificity. This test will be a useful standardized method not only for testing individual samples but also in mass screening programs to assess the extent of human fascioliasis in regions where this zoonosis is suspected.     

Fasciola hepatica and Schistosoma mansoni: identification of common proteins by comparative proteomic analysis

It is not unusual to find common molecules among parasites of different species, genera, or phyla. When those molecules are antigenic, they may be used for developing drugs or vaccines that simultaneously target different species or genera of parasite. In the present study, we used a proteomic-based approach to identify proteins that are common to adult Fasciola hepatica and Schistosoma mansoni. Whole-worm extracts from each parasite were separated by 2-dimensional electrophoresis (2-DE), and digital images of both proteomes were superimposed using imaging software to identify proteins with identical isoelectric points and molecular weights. Protein identities were determined by mass spectrometry. Imaging and immunoblot analyses identified 28 immunoreactive proteins that are common to both parasites. Among these molecules are antioxidant proteins (thioredoxin and glutathione-S-transferase), glycolytic enzymes (glyceraldehyde 6-phosphate dehydrogenase and enolase), proteolytic enzymes (cathepsin-L and -D), inhibitors (Kunitz-type, Stefin-1), proteins with chaperone activity (heat shock protein 70 and fatty acid-binding protein), and structural proteins (calcium-binding protein, actin, and myosin). Some of the identified proteins could be used to develop drugs and vaccines against fascioliasis and schistosomiasis.     

Comparative proteomic analysis of Fasciola hepatica juveniles and Schistosoma bovis schistosomula

Protein interactions between host and parasites can influence the infection success and severity. The aim of this investigation was to identify the proteins from two trematodes potentially localized at the host-parasite interface. We performed the proteomic profiles from in vivo obtained immature lung stage Schistosoma bovis schistosomula and in vitro excysted juveniles from Fasciola hepatica, parasites of ruminants and man usually giving rise to chronic infections. Proteomes from those parasites were obtained after digestion with trypsin and the peptides generated were identified by mass spectrometry, both before and after parasites' treatment with 70% methanol. The comparison of the two proteome sets from each parasite and between them, the analysis of their relative abundance and of their potential exposure to the host from living parasites, together with the specific immunolocalization of two of the identified molecules, show that this approach could assist in the identification of parasite exposed proteins and in the definition of molecules common for the two parasites with potential interaction with the host. Further characterization of these molecules could guide to define new common anti-parasitic targets and potential vaccine candidates.     

Structural and functional analysis of hypothetical proteins in mouse hippocampus from two-dimensional gel electrophoresis

Protein profiling in five individual mouse strains showed strain-specific expression of three hypothetical proteins (HPs). As functional and structural assignment of HPs were based on predictions and low identity to known structures, HPs were identified by MALDI-TOF/TOF, and their proposed tentative function was determined by enzyme assays. Three identified HPs were extracted from gels and renatured, and pyridoxal phosphate phosphatase, inorganic pyrophosphate phosphatase, and antioxidant activities were revealed, findings in agreement with functional predictions.     

The HSSP database of protein structure-sequence alignments.

HSSP (homology-derived structures of proteins) is a derived database merging structural (2-D and 3-D) and sequence information (1-D). For each protein of known 3D structure from the Protein Data Bank, the database has a file with all sequence homologues, properly aligned to the PDB protein. Homologues are very likely to have the same 3D structure as the PDB protein to which they have been aligned. As a result, the database is not only a database of sequence aligned sequence families, but it is also a database of implied secondary and tertiary structures.     

Extracellular Vesicles from Parasitic Helminths Contain Specific Excretory/Secretory Proteins and Are Internalized in Intestinal Host Cells

The study of host-parasite interactions has increased considerably in the last decades, with many studies focusing on the identification of parasite molecules (i.e. surface or excretory/secretory proteins (ESP)) as potential targets for new specific treatments and/or diagnostic tools. In parallel, in the last few years there have been significant advances in the field of extracellular vesicles research. Among these vesicles, exosomes of endocytic origin, with a characteristic size ranging from 30–100 nm, carry several atypical secreted proteins in different organisms, including parasitic protozoa. Here, we present experimental evidence for the existence of exosome-like vesicles in parasitic helminths, specifically the trematodes Echinostoma caproni and Fasciola hepatica. These microvesicles are actively released by the parasites and are taken up by host cells. Trematode extracellular vesicles contain most of the proteins previously identified as components of ESP, as confirmed by proteomic, immunogold labeling and electron microscopy studies. In addition to parasitic proteins, we also identify host proteins in these structures. The existence of extracellular vesicles explains the secretion of atypical proteins in trematodes, and the demonstration of their uptake by host cells suggests an important role for these structures in host-parasite communication, as described for other infectious agents.     

A database for Plasmodium falciparum protein models

There is an urgent need for developing alternate strategies to combat Malaria caused by Plasmodium falciparum (P. falciparum) because of growing drug resistance and increased incidents of infection in humans. 3D models of P. falciparum annotated proteins using molecular modeling techniques will enhance our understanding about the mechanism of host parasite interactions for the identification of drug targets and malarial vaccine design. Potential structural templates for P. falciparum annotated proteins were selected from PDB (protein databank) using BLASTP (basic local alignment search tool for proteins). This exercise identified 476 Plasmodium proteins with one or more known structural templates (>or= 40 % identity) for further modeling. The pair-wise sequence alignments generated for protein modeling were manually checked for error. The models were then constructed using MODELLER (a comparative protein modelling program for modelling protein structures) followed by energy minimization in AMBER force field and checked for error using PROCHECK. AVAILABILITY: http://bioinfo.icgeb.res.in/codes/model.html.     

Prediction of protein secondary structure from circular dichroism using theoretically derived spectra

Circular dichroism (CD) is a spectroscopic technique commonly used to investigate the structure of proteins. Major secondary structure types, alpha‐helices and beta‐strands, produce distinctive CD spectra. Thus, by comparing the CD spectrum of a protein of interest to a reference set consisting of CD spectra of proteins of known structure, predictive methods can estimate the secondary structure of the protein. Currently available methods, including K2D2, use such experimental CD reference sets, which are very small in size when compared to the number of tertiary structures available in the Protein Data Bank (PDB). Conversely, given a PDB structure, it is possible to predict a theoretical CD spectrum from it. The methodological framework for this calculation was established long ago but only recently a convenient implementation called DichroCalc has been developed. In this study, we set to determine whether theoretically derived spectra could be used as reference set for accurate CD based predictions of secondary structure. We used DichroCalc to calculate the theoretical CD spectra of a nonredundant set of structures representing most proteins in the PDB, and applied a straightforward approach for predicting protein secondary structure content using these theoretical CD spectra as reference set. We show that this method improves the predictions, particularly for the wavelength interval between 200 and 240 nm and for beta‐strand content. We have implemented this method, called K2D3, in a publicly accessible web server at http://www. ogic.ca/projects/k2d3 . Proteins 2012. © 2011 Wiley Periodicals, Inc.     

Computational prediction of protein interactions related to the invasion of erythrocytes by malarial parasites

Background

The invasion of red blood cells (RBCs) by malarial parasites is an essential step in the life cycle of Plasmodium falciparum. Human-parasite surface protein interactions play a critical role in this process. Although several interactions between human and parasite proteins have been discovered, the mechanism related to invasion remains poorly understood because numerous human-parasite protein interactions have not yet been identified. High-throughput screening experiments are not feasible for malarial parasites due to difficulty in expressing the parasite proteins. Here, we performed computational prediction of the PPIs involved in malaria parasite invasion to elucidate the mechanism by which invasion occurs.

Results

In this study, an expectation maximization algorithm was used to estimate the probabilities of domain-domain interactions (DDIs). Estimates of DDI probabilities were then used to infer PPI probabilities. We found that our prediction performance was better than that based on the information of D. melanogaster alone when information related to the six species was used. Prediction performance was assessed using protein interaction data from S. cerevisiae, indicating that the predicted results were reliable. We then used the estimates of DDI probabilities to infer interactions between 490 parasite and 3,787 human membrane proteins. A small-scale dataset was used to illustrate the usability of our method in predicting interactions between human and parasite proteins. The positive predictive value (PPV) was lower than that observed in S. cerevisiae. We integrated gene expression data to improve prediction accuracy and to reduce false positives. We identified 80 membrane proteins highly expressed in the schizont stage by fast Fourier transform method. Approximately 221 erythrocyte membrane proteins were identified using published mass spectral datasets. A network consisting of 205 interactions was predicted. Results of network analysis suggest that SNARE proteins of parasites and APP of humans may function in the invasion of RBCs by parasites.

Conclusions

We predicted a small-scale PPI network that may be involved in parasite invasion of RBCs by integrating DDI information and expression profiles. Experimental studies should be conducted to validate the predicted interactions. The predicted PPIs help elucidate the mechanism of parasite invasion and provide directions for future experimental investigations.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-014-0393-z) contains supplementary material, which is available to authorized users.     

Parasite communities of common dolphins (Delphinus delphis) from Patagonia: the relation with host distribution and diet and comparison with sympatric hosts

We studied the helminths of 18 common dolphins, Delphinus delphis, from northern Patagonia. Parasites were found only in the gastrointestinal tract. Four species were in the stomach, the nematode Anisakis simplex, the acanthocephalan Corynosoma cetaceum, and the digeneans Braunina cordiformis and Pholeter gastrophilus, plus 1 digenean in the hepatopancreatic ducts, Oschmarinella rochebruni. Infection levels were low (0-155 parasites). Braunina cordiformis and C. cetaceum were the most prevalent species. Anisakis simplex was mainly concentrated in the forestomach, B. cordiformis in the main stomach, and C. cetaceum in the pyloric stomach. Component diversity was low and component evenness was intermediate. Infracommunity diversity was also low, and the mean evenness was higher than at the component community level. Low prevalence in common dolphins is consistent with parasite assemblages of other cetaceans off Patagonia. None of the parasites found is specific to this host species within the study area. We suggest that potential prey are probably important in parasite transmission in this and other dolphins from the Patagonian region.     

Het-PDB Navi.: a database for protein-small molecule interactions

The genomes of more than 100 species have been sequenced, and the biological functions of encoded proteins are now actively being researched. Protein function is based on interactions between proteins and other molecules. One approach to assuming protein function based on genomic sequence is to predict interactions between an encoded protein and other molecules. As a data source for such predictions, knowledge regarding known protein-small molecule interactions needs to be compiled. We have, therefore, surveyed interactions between proteins and other molecules in Protein Data Bank (PDB), the protein three-dimensional (3D) structure database. Among 20,685 entries in PDB (April, 2003), 4,189 types of small molecules were found to interact with proteins. Biologically relevant small molecules most often found in PDB were metal ions, such as calcium, zinc, and magnesium. Sugars and nucleotides were the next most common. These molecules are known to act as cofactors for enzymes and/or stabilizers of proteins. In each case of interactions between a protein and small molecule, we found preferred amino acid residues at the interaction sites. These preferences can be the basis for predicting protein function from genomic sequence and protein 3D structures. The data pertaining to these small molecules were collected in a database named Het-PDB Navi., which is freely available at http://daisy.nagahama-i-bio.ac.jp/golab/hetpdbnavi.html and linked to the official PDB home page.     

Search for glucose/galactose-binding proteins in newly discovered protein sequences using molecular modeling techniques and structural analysis

Sugar moieties serve as specificity markers in a wide variety of biochemical functions, and periplasmic glucose/galactose-binding proteins (GGBPs) serve as the primary receptors for transport and chemotaxis. Recently, complete genome sequencing projects have revealed many open reading frames for such receptors. On the basis of the homology search with the known x-ray structures (PDB ID: 3GBP/1GCA) of a periplasmic receptor protein from Salmonella typhimurium, we selected four putative proteins with amino acid identities between 30 and 48% for the prediction of three-dimensional (3D) structures of the proteins as well as their complexes with glucose and galactose. We could successfully identify the key residues involved in coordination with calcium ion spanning over two loop structures. We calculated the ligand-binding affinities and hydrogen bonding patterns of the modeled structures and compared with those of the x-ray structures. The calculation of free energies of binding of the modeled structures to glucose and galactose in the presence of water suggested that two of four putative proteins can form complexes with dissociation constants in the micromolar range (1-10 microM). Electrostatic potentials on the surfaces near the sugar and calcium-binding sites of the modeled structures were predominately negative as found in case of the x-ray structure. Taken together, our results suggest that the products of two newly discovered genes would serve as receptors for the transport of glucose and galactose.     

MIND-BEST: Web server for drugs and target discovery; design, synthesis, and assay of MAO-B inhibitors and theoretical-experimental study of G3PDH protein from Trichomonas gallinae

Many drugs with very different affinity to a large number of receptors are described. Thus, in this work, we selected drug-target pairs (DTPs/nDTPs) of drugs with high affinity/nonaffinity for different targets. Quantitative structure-activity relationship (QSAR) models become a very useful tool in this context because they substantially reduce time and resource-consuming experiments. Unfortunately, most QSAR models predict activity against only one protein target and/or they have not been implemented on a public Web server yet, freely available online to the scientific community. To solve this problem, we developed a multitarget QSAR (mt-QSAR) classifier combining the MARCH-INSIDE software for the calculation of the structural parameters of drug and target with the linear discriminant analysis (LDA) method in order to seek the best model. The accuracy of the best LDA model was 94.4% (3,859/4,086 cases) for training and 94.9% (1,909/2,012 cases) for the external validation series. In addition, we implemented the model into the Web portal Bio-AIMS as an online server entitled MARCH-INSIDE Nested Drug-Bank Exploration & Screening Tool (MIND-BEST), located at http://miaja.tic.udc.es/Bio-AIMS/MIND-BEST.php . This online tool is based on PHP/HTML/Python and MARCH-INSIDE routines. Finally, we illustrated two practical uses of this server with two different experiments. In experiment 1, we report for the first time a MIND-BEST prediction, synthesis, characterization, and MAO-A and MAO-B pharmacological assay of eight rasagiline derivatives, promising for anti-Parkinson drug design. In experiment 2, we report sampling, parasite culture, sample preparation, 2-DE, MALDI-TOF and -TOF/TOF MS, MASCOT search, 3D structure modeling with LOMETS, and MIND-BEST prediction for different peptides as new protein of the found in the proteome of the bird parasite Trichomonas gallinae, which is promising for antiparasite drug targets discovery.