The Cysteine-Rich Protein Thimet Oligopeptidase as a Model of the Structural Requirements for S-glutathiolation and Oxidative Oligomerization

Thimet oligopeptidase (EP24.15) is a cysteine-rich metallopeptidase containing fifteen Cys residues and no intra-protein disulfide bonds. Previous work on this enzyme revealed that the oxidative oligomerization of EP24.15 is triggered by S-glutathiolation at physiological GSSG levels (10-50 mu M) via a mechanism based on thiol-disulfide exchange. In the present work, our aim was to identify EP24.15 Cys residues that are prone to S-glutathiolation and to determine which structural features in the cysteinyl bulk are responsible for the formation of mixed disulfides through the reaction with GSSG and, in this particular case, the Cys residues within EP24.15 that favor either S-glutathiolation or inter-protein thiol-disulfide exchange. These studies were conducted by in silico structural analyses and simulations as well as site-specific mutation. S-glutathiolation was determined by mass spectrometric analyses and western blotting with anti-glutathione antibody. The results indicated that the stabilization of a thiolate sulfhydryl and the solvent accessibility of the cysteines are necessary for S-thiolation. The Solvent Access Surface analysis of the Cys residues prone to glutathione modification showed that the S-glutathiolated Cys residues are located inside pockets where the sulfur atom comes into contact with the solvent and that the positively charged amino acids are directed toward these Cys residues. The simulation of a covalent glutathione docking onto the same Cys residues allowed for perfect glutathione posing. A mutation of the Arg residue 263 that forms a saline bridge to the Cys residue 175 significantly decreased the overall S-glutathiolation and oligomerization of EP24.15. The present results show for the first time the structural requirements for protein S-glutathiolation by GSSG and are consistent with our previous hypothesis that EP24.15 oligomerization is dependent on the electron transfer from specific protonated Cys residues of one molecule to previously S-glutathionylated Cys residues of another one.

The Diversity of Polyketide Synthase Genes from Sugarcane-Derived Fungi

The chemical ecology and biotechnological potential of metabolites from endophytic and rhizosphere fungi are receiving much attention. A collection of 17 sugarcane-derived fungi were identified and assessed by PCR for the presence of polyketide synthase (PKS) genes. The fungi were all various genera of ascomycetes, the genomes of which encoded 36 putative PKS sequences, 26 shared sequence homology with beta-ketoacyl synthase domains, while 10 sequences showed homology to known fungal C-methyltransferase domains. A neighbour-joining phylogenetic analysis of the translated sequences could group the domains into previously established chemistry-based clades that represented non-reducing, partially reducing and highly reducing fungal PKSs. We observed that, in many cases, the membership of each clade also reflected the taxonomy of the fungal isolates. The functional assignment of the domains was further confirmed by in silico secondary and tertiary protein structure predictions. This genome mining study reveals, for the first time, the genetic potential of specific taxonomic groups of sugarcane-derived fungi to produce specific types of polyketides. Future work will focus on isolating these compounds with a view to understanding their chemical ecology and likely biotechnological potential.

Consensus hologram QSAR modeling for the prediction of human intestinal absorption

Consistent in silico models for ADME properties are useful tools in early drug discovery. Here, we report the hologram QSAR modeling of human intestinal absorption using a dataset of 638 compounds with experimental data associated. The final validated models are consistent and robust for the consensus prediction of this important pharmacokinetic property and are suitable for virtual screening applications. (C) 2012 Elsevier Ltd. All rights reserved.

Sugarwin: A Sugarcane Insect-Induced Gene with Antipathogenic Activity

In sugarcane fields, colonization of the stalk by opportunistic fungi usually occurs after the caterpillar Diatraea saccharalis attacks the sugarcane plant. Plants respond to insect attack by inducing and accumulating a large set of defense proteins. Two homologues of a barley wound-inducible protein (BARWIN), sugarcane wound-inducible proteins SUGARWIN1 and SUGARWIN2, have been identified in sugarcane by an in silico analysis. Antifungal properties have been described for a number of BARWIN homologues. We report that a SUGARWIN:green fluorescent protein fusion protein is located in the endoplasmic reticulum and in the extracellular space of sugarcane plants. The induction of sugarwin transcripts occurs in response to mechanical wounding, D. saccharalis damage, and methyl jasmonate treatment. The accumulation of transcripts is late induced and is restricted to the site of the wound. Although the transcripts of sugarwin genes were strongly increased following insect attack, the protein itself did not show any effect on insect development; rather, it altered fungal morphology, leading to the apoptosis of the germlings. These results suggest that, in the course of evolution, sugarwin-encoding genes were recruited by sugarcane due to their antipathogenic activity. We rationalize that sugarcane is able to induce sugarwin gene expression in response to D. saccharalis feeding as a concerted plant response to the anticipated invasion by the fungi that typically penetrate the plant stalk after insect damage.

Endo-xylanase GH11 activation by the fungal metabolite eugenitin

Eugenitin, a chromone derivative and a metabolite of the endophyte Mycoleptodiscus indicus, at 5 mM activated a recombinant GH11 endo-xylanase by 40 %. The in silico prediction of ligand-binding sites on the three-dimensional structure of the endo-xylanase revealed that eugenitin interacts mainly by a hydrogen bond with a serine residue and a stacking interaction of the heterocyclic aromatic ring system with a tryptophan residue. Eugenitin improved the GH11 endo-xylanase activity on different substrates, modified the optimal pH and temperature activities and slightly affected the kinetic parameters of the enzyme.

A Combined Study Using Ligand-Based Design, Synthesis, and Pharmacological Evaluation of Analogues of the Acetaminophen Ortho-Regioisomer with Potent Analgesic Activity

A ligand-based drug design study was performed to acetaminophen regioisomers as analgesic candidates employing quantum chemical calculations at the DFT/B3LYP level of theory and the 6-31G* basis set. To do so, many molecular descriptors were used such as highest occupied molecular orbital, ionization potential, HO bond dissociation energies, and spin densities, which might be related to quench reactivity of the tyrosyl radical to give N-acetyl-p-benzosemiquinone-imine through an initial electron withdrawing or hydrogen atom abstraction. Based on this in silico work, the most promising molecule, orthobenzamol, was synthesized and tested. The results expected from the theoretical prediction were confirmed in vivo using mouse models of nociception such as writhing, paw licking, and hot plate tests. All biological results suggested an antinociceptive activity mediated by opioid receptors. Furthermore, at 90 and 120 min, this new compound had an effect that was comparable to morphine, the standard drug for this test. Finally, the pharmacophore model is discussed according to the electronic properties derived from quantum chemistry calculations.

Somatotroph pituitary adenoma with acromegaly and autosomal dominant polycystic kidney disease: SSTR5 polymorphism and PKD1 mutation

A 39-year-old woman with autosomal dominant polycystic kidney disease (ADPKD) presented with acromegaly and a pituitary macroadenoma. There was a family history of this renal disorder. She had undergone surgery for pituitary adenoma 6 years prior. Physical examination disclosed bitemporal hemianopsia and elevation of both basal growth hormone (GH) 106 ng/mL (normal 0-5) and insulin-like growth factor (IGF-1) 811 ng/mL (normal 48-255) blood levels. A magnetic resonance imaging scan disclosed a 3.0 cm sellar and suprasellar mass with both optic chiasm compression and left cavernous sinus invasion. Pathologic, cytogenetic, molecular and in silico analysis was undertaken. Histologic, immunohistochemical and ultrastructural studies of the lesion disclosed a sparsely granulated somatotroph adenoma. Standard chromosome analysis on the blood sample showed no abnormality. Sequence analysis of the coding regions of PKD1 and PKD2 employing DNA from both peripheral leukocytes and the tumor revealed the most common PKD1 mutation, 5014_5015delAG. Analysis of the entire SSTR5 gene disclosed the variant c.142C > A (p.L48M, rs4988483) in the heterozygous state in both blood and tumor, while no pathogenic mutations were noted in the MEN1, AIP, p27Kip1 and SSTR2 genes. To our knowledge, this is the fourth reported case of a GH-producing pituitary adenoma associated with ADPKD, but the first subjected to extensive morphological, ultrastructural, cytogenetic and molecular studies. The physical proximity of the PKD1 and SSTR5 genes on chromosome 16 suggests a causal relationship between ADPKD and somatotroph adenoma.

A quantitative proteomic and transcriptomic comparison of human mesenchymal stem cells from bone marrow and umbilical cord vein

Human mesenchymal stem cells (hMSCs) are adult multipotent cells that have high therapeutic potential due to their immunological properties. They can be isolated from several different tissues with bone marrow (BM) being the most common source. Because the isolation procedure is invasive, other tissues such as human umbilical cord vein (UCV) have been considered. However, their interchangeability remains unclear. In the present study, total protein extracts of BM-hMSCs and UCV-hMSCs were quantitatively compared using gel-LC-MS/MS. Previous SAGE analysis of the same cells was re-annotated to enable comparison and combination of these two data sets. We observed a more than 63% correlation between proteomic and transcriptomic data. In silico analysis of highly expressed genes in cells of both origins suggests that they can be modulated by microRNA, which can change protein abundance. Our results showed that MSCs from both tissues shared high similarity in metabolic and functional processes relevant to their therapeutic potential, especially in the immune system process, response to stimuli, and processes related to the delivery of the hMSCs to a given tissue, such as migration and adhesion. Hence, our results support the idea that the more accessible UCV could be a potentially less invasive source of MSCs.

Self assembly of human septin 2 into amyloid filaments

Septins are a conserved group of GTP-binding proteins that form hetero-oligomeric complexes which assemble into filaments. These are essential for septin function, including their role in cytokinesis, cell division, exocytosis and membrane trafficking. Septin 2 (SEPT2) is a member of the septin family and has been associated with neurofibrillary tangles and other pathological features of senile plaques in Alzheimer's disease. An in silico analysis of the amino acid sequence of SEPT2 identified regions with a significant tendency to aggregate and/or form amyloid. These were all observed within the GTP-binding domain. This was consistent with the experimental identification of a structure rich in beta-sheet during temperature induced unfolding transitions observed for both the full length protein and the GTP-binding domain alone. This intermediate state is characterized by irreversible aggregation and has the ability to bind Thioflavin-T, suggesting its amyloid nature. Under electron microscopy, fibers extending for several micrometers in length could be visualized. The results shown in this study support the hypothesis that single septins, when present in excess or with unbalanced stoichiometries, may be unstable and assemble into amyloid-like structures. (C) 2011 Elsevier Masson SAS. All rights reserved.

SAG2A protein from Toxoplasma gondii interacts with both innate and adaptive immune compartments of infected hosts

Abstract Background Toxoplasma gondii is an intracellular parasite that causes relevant clinical disease in humans and animals. Several studies have been performed in order to understand the interactions between proteins of the parasite and host cells. SAG2A is a 22 kDa protein that is mainly found in the surface of tachyzoites. In the present work, our aim was to correlate the predicted three-dimensional structure of this protein with the immune system of infected hosts. Methods To accomplish our goals, we performed in silico analysis of the amino acid sequence of SAG2A, correlating the predictions with in vitro stimulation of antigen presenting cells and serological assays. Results Structure modeling predicts that SAG2A protein possesses an unfolded C-terminal end, which varies its conformation within distinct strain types of T. gondii. This structure within the protein shelters a known B-cell immunodominant epitope, which presents low identity with its closest phyllogenetically related protein, an orthologue predicted in Neospora caninum. In agreement with the in silico observations, sera of known T. gondii infected mice and goats recognized recombinant SAG2A, whereas no serological cross-reactivity was observed with samples from N. caninum animals. Additionally, the C-terminal end of the protein was able to down-modulate pro-inflammatory responses of activated macrophages and dendritic cells. Conclusions Altogether, we demonstrate herein that recombinant SAG2A protein from T. gondii is immunologically relevant in the host-parasite interface and may be targeted in therapeutic and diagnostic procedures designed against the infection.

New insights regarding HCV-NS5A structure/function and indication of genotypic differences

Abstract Background HCV is prevalent throughout the world. It is a major cause of chronic liver disease. There is no effective vaccine and the most common therapy, based on Peginterferon, has a success rate of ~50%. The mechanisms underlying viral resistance have not been elucidated but it has been suggested that both host and virus contribute to therapy outcome. Non-structural 5A (NS5A) protein, a critical virus component, is involved in cellular and viral processes. Methods The present study analyzed structural and functional features of 345 sequences of HCV-NS5A genotypes 1 or 3, using in silico tools. Results There was residue type composition and secondary structure differences between the genotypes. In addition, second structural variance were statistical different for each response group in genotype 3. A motif search indicated conserved glycosylation, phosphorylation and myristoylation sites that could be important in structural stabilization and function. Furthermore, a highly conserved integrin ligation site was identified, and could be linked to nuclear forms of NS5A. ProtFun indicated NS5A to have diverse enzymatic and nonenzymatic activities, participating in a great range of cell functions, with statistical difference between genotypes. Conclusion This study presents new insights into the HCV-NS5A. It is the first study that using bioinformatics tools, suggests differences between genotypes and response to therapy that can be related to NS5A protein features. Therefore, it emphasizes the importance of using bioinformatics tools in viral studies. Data acquired herein will aid in clarifying the structure/function of this protein and in the development of antiviral agents.

Purification, characterization and structural determination of chitinases produced by Moniliophthora perniciosa

The enzyme chitinase from Moniliophthora perniciosa the causative agent of the witches' broom disease in Theobroma cacao, was partially purified with ammonium sulfate and filtration by Sephacryl S-200 using sodium phosphate as an extraction buffer. Response surface methodology (RSM) was used to determine the optimum pH and temperature conditions. Four different isoenzymes were obtained: ChitMp I, ChitMp II, ChitMp III and ChitMp IV. ChitMp I had an optimum temperature at 44-73ºC and an optimum pH at 7.0-8.4. ChitMp II had an optimum temperature at 45-73ºC and an optimum pH at 7.0-8.4. ChitMp III had an optimum temperature at 54-67ºC and an optimum pH at 7.3-8.8. ChitMp IV had an optimum temperature at 60ºC and an optimum pH at 7.0. For the computational biology, the primary sequence was determined in silico from the database of the Genome/Proteome Project of M. perniciosa, yielding a sequence with 564 bp and 188 amino acids that was used for the three-dimensional design in a comparative modeling methodology. The generated models were submitted to validation using Procheck 3.0 and ANOLEA. The model proposed for the chitinase was subjected to a dynamic analysis over a 1 ns interval, resulting in a model with 91.7% of the residues occupying favorable places on the Ramachandran plot and an RMS of 2.68.

Ecology of marine bacteroidetes: a genomics approach

Institut de Ciències del Mar (ICM-CSIC). Doctorado en oceanografía. Con mención de Calidad de la ANECA

Design and implementation of bioinformatics tools for large scale genome annotation

The continuous increase of genome sequencing projects produced a huge amount of data in the last 10 years: currently more than 600 prokaryotic and 80 eukaryotic genomes are fully sequenced and publically available. However the sole sequencing process of a genome is able to determine just raw nucleotide sequences. This is only the first step of the genome annotation process that will deal with the issue of assigning biological information to each sequence. The annotation process is done at each different level of the biological information processing mechanism, from DNA to protein, and cannot be accomplished only by in vitro analysis procedures resulting extremely expensive and time consuming when applied at a this large scale level. Thus, in silico methods need to be used to accomplish the task. The aim of this work was the implementation of predictive computational methods to allow a fast, reliable, and automated annotation of genomes and proteins starting from aminoacidic sequences. The first part of the work was focused on the implementation of a new machine learning based method for the prediction of the subcellular localization of soluble eukaryotic proteins. The method is called BaCelLo, and was developed in 2006. The main peculiarity of the method is to be independent from biases present in the training dataset, which causes the over‐prediction of the most represented examples in all the other available predictors developed so far. This important result was achieved by a modification, made by myself, to the standard Support Vector Machine (SVM) algorithm with the creation of the so called Balanced SVM. BaCelLo is able to predict the most important subcellular localizations in eukaryotic cells and three, kingdom‐specific, predictors were implemented. In two extensive comparisons, carried out in 2006 and 2008, BaCelLo reported to outperform all the currently available state‐of‐the‐art methods for this prediction task. BaCelLo was subsequently used to completely annotate 5 eukaryotic genomes, by integrating it in a pipeline of predictors developed at the Bologna Biocomputing group by Dr. Pier Luigi Martelli and Dr. Piero Fariselli. An online database, called eSLDB, was developed by integrating, for each aminoacidic sequence extracted from the genome, the predicted subcellular localization merged with experimental and similarity‐based annotations. In the second part of the work a new, machine learning based, method was implemented for the prediction of GPI‐anchored proteins. Basically the method is able to efficiently predict from the raw aminoacidic sequence both the presence of the GPI‐anchor (by means of an SVM), and the position in the sequence of the post‐translational modification event, the so called ω‐site (by means of an Hidden Markov Model (HMM)). The method is called GPIPE and reported to greatly enhance the prediction performances of GPI‐anchored proteins over all the previously developed methods. GPIPE was able to predict up to 88% of the experimentally annotated GPI‐anchored proteins by maintaining a rate of false positive prediction as low as 0.1%. GPIPE was used to completely annotate 81 eukaryotic genomes, and more than 15000 putative GPI‐anchored proteins were predicted, 561 of which are found in H. sapiens. In average 1% of a proteome is predicted as GPI‐anchored. A statistical analysis was performed onto the composition of the regions surrounding the ω‐site that allowed the definition of specific aminoacidic abundances in the different considered regions. Furthermore the hypothesis that compositional biases are present among the four major eukaryotic kingdoms, proposed in literature, was tested and rejected. All the developed predictors and databases are freely available at: BaCelLo http://gpcr.biocomp.unibo.it/bacello eSLDB http://gpcr.biocomp.unibo.it/esldb GPIPE http://gpcr.biocomp.unibo.it/gpipe

Computational methods for genome screening

Motivation An actual issue of great interest, both under a theoretical and an applicative perspective, is the analysis of biological sequences for disclosing the information that they encode. The development of new technologies for genome sequencing in the last years, opened new fundamental problems since huge amounts of biological data still deserve an interpretation. Indeed, the sequencing is only the first step of the genome annotation process that consists in the assignment of biological information to each sequence. Hence given the large amount of available data, in silico methods became useful and necessary in order to extract relevant information from sequences. The availability of data from Genome Projects gave rise to new strategies for tackling the basic problems of computational biology such as the determination of the tridimensional structures of proteins, their biological function and their reciprocal interactions. Results The aim of this work has been the implementation of predictive methods that allow the extraction of information on the properties of genomes and proteins starting from the nucleotide and aminoacidic sequences, by taking advantage of the information provided by the comparison of the genome sequences from different species. In the first part of the work a comprehensive large scale genome comparison of 599 organisms is described. 2,6 million of sequences coming from 551 prokaryotic and 48 eukaryotic genomes were aligned and clustered on the basis of their sequence identity. This procedure led to the identification of classes of proteins that are peculiar to the different groups of organisms. Moreover the adopted similarity threshold produced clusters that are homogeneous on the structural point of view and that can be used for structural annotation of uncharacterized sequences. The second part of the work focuses on the characterization of thermostable proteins and on the development of tools able to predict the thermostability of a protein starting from its sequence. By means of Principal Component Analysis the codon composition of a non redundant database comprising 116 prokaryotic genomes has been analyzed and it has been showed that a cross genomic approach can allow the extraction of common determinants of thermostability at the genome level, leading to an overall accuracy in discriminating thermophilic coding sequences equal to 95%. This result outperform those obtained in previous studies. Moreover, we investigated the effect of multiple mutations on protein thermostability. This issue is of great importance in the field of protein engineering, since thermostable proteins are generally more suitable than their mesostable counterparts in technological applications. A Support Vector Machine based method has been trained to predict if a set of mutations can enhance the thermostability of a given protein sequence. The developed predictor achieves 88% accuracy.