Proteins from eggs of the spittlebug Mahanarva spectabilis (Hemiptera: Cercopidae) reveal clues about its diapause regulation.

Embryo development in eggs of the spittlebug Mahanarva spectabilis (Distant) (Hemiptera: Cercopidae) passes through four phases (known as S1 to S4) being stopped at S2 during diapause. Studies about the molecular basis of diapause in spittlebugs are nonexistent. Here, we analyzed proteins from non-diapausing (ND), diapausing (D) and post-diapausing (PD) eggs of the spittlebug M. spectabilis. In total, we identified 87 proteins where 12 were in common among the developmental and diapause phases and 19 remained as uncharacterized. Non-diapausing eggs (S2ND and S4ND) showed more proteins involved in information storage and processing than the diapausing ones (S2D). Eggs in post-diapausing (S4PD) had a higher number of proteins associated with metabolism than S2D. The network of protein interactions and metabolic processes allowed the identification of different sets of molecular interactions for each developmental and diapause phases. Two heat shock proteins (Hsp65 and Hsp70) along with two proteins associated with intracellular signaling (MAP4K and a serine/threonine-protein phosphatase) were found only in diapausing and/or post-diapausing eggs and are interesting targets to be explored in future experiments. These results shine a light on one key biological process for spittlebug survival and represent the first search for proteins linked to diapause in this important group of insects.

Propedia: a database for protein-peptide identification based on a hybrid clustering algorithm.

BACKGROUND: Protein-peptide interactions play a fundamental role in a wide variety of biological processes, such as cell signaling, regulatory networks, immune responses, and enzyme inhibition. Peptides are characterized by low toxicity and small interface areas; therefore, they are good targets for therapeutic strategies, rational drug planning and protein inhibition. Approximately 10% of the ethical pharmaceutical market is protein/peptide-based. Furthermore, it is estimated that 40% of protein interactions are mediated by peptides. Despite the fast increase in the volume of biological data, particularly on sequences and structures, there remains a lack of broad and comprehensive protein-peptide databases and tools that allow the retrieval, characterization and understanding of protein-peptide recognition and consequently support peptide design. RESULTS: We introduce Propedia, a comprehensive and up-to-date database with a web interface that permits clustering, searching and visualizing of protein-peptide complexes according to varied criteria. Propedia comprises over 19,000 high-resolution structures from the Protein Data Bank including structural and sequence information from protein-peptide complexes. The main advantage of Propedia over other peptide databases is that it allows a more comprehensive analysis of similarity and redundancy. It was constructed based on a hybrid clustering algorithm that compares and groups peptides by sequences, interface structures and binding sites. Propedia is available through a graphical, user-friendly and functional interface where users can retrieve, and analyze complexes and download each search data set. We performed case studies and verified that the utility of Propedia scores to rank promissing interacting peptides. In a study involving predicting peptides to inhibit SARS-CoV-2 main protease, we showed that Propedia scores related to similarity between different peptide complexes with SARS-CoV-2 main protease are in agreement with molecular dynamics free energy calculation. CONCLUSIONS: Propedia is a database and tool to support structure-based rational design of peptides for special purposes. Protein-peptide interactions can be useful to predict, classifying and scoring complexes or for designing new molecules as well. Propedia is up-to-date as a ready-to-use webserver with a friendly and resourceful interface and is available at: https://bioinfo.dcc.ufmg.br/propedia.

Leaf metabolic profiles of two soybean genotypes differentially affect the survival and the digestibility of Anticarsia gemmatalis caterpillars.

Insect pests such as Anticarsia gemmatalis cause defoliation and yield losses. Soybean breeding has obtained resistant genotypes, however the mechanism remains unknown. Studies indicated the presence of deterrents compounds in the resistant genotype IAC17, and their leaf metabolite profiles were compared to the susceptible genotype UFV105, which was elicited or not by caterpillar infestation. Cluster analysis indicated a significative distinction between these profiles as well as differences in plant defense pathways. Methylquercetins were constitutively present in the largest concentrations, specifically in the IAC17. Relationship between the resistance and the levels of phytohormones jasmonic acid, abscisic acid and salicylic acid was not observed. However, 1-aminocyclopropane -1carboxylic acid levels indicated that the ethylene may be involved in the constitutive biosynthesis of bioactive compounds. Extracts were added to the diets at three different concentrations to evaluate the effect on caterpillar survival. Lowest survival rates were observed when extracts from the resistant IAC 17 were used, at the lowest concentrations. Survival rates were not higher when IAC 17 infested by caterpillars were used. On the other hand, when extracts from the susceptible were used, the survival reductions were only observed in the highest extract concentrations. These supplementations of the diet reduced the digestive capacity, agreeing with the proteolytic activities, whereas malformations of the intestinal cells were dose dependent. The inhibitory effects persisted in higher dilutions only for the IAC17. Constitutive resistance was also explained by higher levels of protease inhibition. These results can be useful to elucidate the genes and cascades controlling the resistance.

ppiGReMLIN: a graph mining based detection of conserved structural arrangements in protein-protein interfaces.

BACKGROUND: Protein-protein interactions (PPIs) are fundamental in many biological processes and understanding these interactions is key for a myriad of applications including drug development, peptide design and identification of drug targets. The biological data deluge demands efficient and scalable methods to characterize and understand protein-protein interfaces. In this paper, we present ppiGReMLIN, a graph based strategy to infer interaction patterns in a set of protein-protein complexes. Our method combines an unsupervised learning strategy with frequent subgraph mining in order to detect conserved structural arrangements (patterns) based on the physicochemical properties of atoms on protein interfaces. To assess the ability of ppiGReMLIN to point out relevant conserved substructures on protein-protein interfaces, we compared our results to experimentally determined patterns that are key for protein-protein interactions in 2 datasets of complexes, Serine-protease and BCL-2. RESULTS: ppiGReMLIN was able to detect, in an automatic fashion, conserved structural arrangements that represent highly conserved interactions at the specificity binding pocket of trypsin and trypsin-like proteins from Serine-protease dataset. Also, for the BCL-2 dataset, our method pointed out conserved arrangements that include critical residue interactions within the conserved motif LXXXXD, pivotal to the binding specificity of BH3 domains of pro-apoptotic BCL-2 proteins towards apoptotic suppressors. Quantitatively, ppiGReMLIN was able to find all of the most relevant residues described in literature for our datasets, showing precision of at least 69% up to 100% and recall of 100%. CONCLUSIONS: ppiGReMLIN was able to find highly conserved structures on the interfaces of protein-protein complexes, with minimum support value of 60%, in datasets of similar proteins. We showed that the patterns automatically detected on protein interfaces by our method are in agreement with interaction patterns described in the literature.

visGReMLIN: graph mining-based detection and visualization of conserved motifs at 3D protein-ligand interface at the atomic level.

BACKGROUND: Interactions between proteins and non-proteic small molecule ligands play important roles in the biological processes of living systems. Thus, the development of computational methods to support our understanding of the ligand-receptor recognition process is of fundamental importance since these methods are a major step towards ligand prediction, target identification, lead discovery, and more. This article presents visGReMLIN, a web server that couples a graph mining-based strategy to detect motifs at the protein-ligand interface with an interactive platform to visually explore and interpret these motifs in the context of protein-ligand interfaces. RESULTS: To illustrate the potential of visGReMLIN, we conducted two cases in which our strategy was compared with previous experimentally and computationally determined results. visGReMLIN allowed us to detect patterns previously documented in the literature in a totally visual manner. In addition, we found some motifs that we believe are relevant to protein-ligand interactions in the analyzed datasets. CONCLUSIONS: We aimed to build a visual analytics-oriented web server to detect and visualize common motifs at the protein-ligand interface. visGReMLIN motifs can support users in gaining insights on the key atoms/residues responsible for protein-ligand interactions in a dataset of complexes.

Does mechanical damage on soybean induces the production of flavonoids?

The response of plants to grazing includes the production of chemical defense compounds such as proteases inhibitors and secondary metabolites as flavonoids, which makes them less palatable to feeding and negatively affecting the physiology of insects. The aim of this study was to evaluate the phytochemical response of soybean cultivars (Glycine max (L.) Merrill) resistant (IAC-17, IAC-24) and susceptible (IAC-P1) to insects after mechanical damage. These cultivars were mechanically injured, and after 24 hours samples of these plants were analyzed by HPLC to identify and quantify flavonoids. The flavonoids daidzein, quercetin, and rutin were quantified, with the highest concentration of daidzin in soybean cultivars after mechanical damage. Rutin was biosynthesized by IAC-24. The cultivars IAC-PL1, IAC-17, and IAC-24 did not show a flavonoid response to mechanical damage. The soybean cultivars are not dependent on mechanical damage to produce flavonoids.

Broad range flavonoid profiling by LC/MS of soybean genotypes contrasting for resistance to Anticarsia gemmatalis (Lepidoptera: Noctuidae).

Attack by herbivores is a major biotic stress limiting the soybean crop production. Plant defenses against caterpillars include the production of secondary metabolites such as flavonoids, which constitute a diverse group of plant secondary metabolites. Thus, a more discriminate metabolic profiling between genotypes are important for a more comprehensive and reliable characterization of soybean resistance. Therefore, in this study a non-targeted LC/MS-based for analysis of flavonoid profiles of soybean genotypes contrasting to the resistance to A. gemmatalis was applied. Clustering analysis revealed profiles highly distinct between the susceptible UFV 105 AP and the resistant IAC 17 genotypes. This comparative approach enables to identify directly from leaf extract some new compounds related to resistance, some of which were present in higher abundance specifically in the IAC 17 genotype: four Quercetin conjugates, Rutin (Quercetin 3-O-Rutinoside), Quercetin-3,7-O- di-glucoside, Quercetin-3-O-rhamnosylglycoside-7-O-glucoside and Quercetin-3-O-rhamnopyranosyl-glucopyranoside-rhamnopyranoside; two Genistein conjugates, Genistein-7-O-diglucoside-dimalonylated and Genistein-7-O-6-O-malonylglucoside; and one Daidzein conjugate, Daidzein-7-O-Glucoside-malonate. The most abundant flavonoid glycoconjugates in soybean leaves belongs to Quercetin and Kaempferol classes. However, only one from the identified compounds was classified as a Kaempferol. The Kaempferol-3-O-L-rhamnopyranosyl-glucopyranoside showed high abundance in the resistant genotype IAC 17. The metabolic profiles generated by LC/MS allowed the reconstruction of the flavonoid biosynthetic pathways, which revealed a constitutive character for herbivory resistance in the resistant genotype IAC-17 and a metabolic regulation for the rechanneling of Quercetin, Kaempferol and Genistein conjugates in soybean. Highest relative abundances were detected for glyconjugates, such as Rutin, Quercetin 3-O-rhamnosylglycoside-7-O-glucoside and Quercitin-3-O-rhamnopyranosyl-glucopyranoside-rhamnopyranoside in the leaves of the resistant genotype.

Low Doses of Simvastatin Potentiate the Effect of Sodium Alendronate in Inhibiting Bone Resorption and Restore Microstructural and Mechanical Bone Properties in Glucocorticoid-Induced Osteoporosis.

By using an experimental model of dexamethasone-induced osteoporosis we investigated the effects of different therapeutic schemes combining sodium alendronate (SA) and simvastatin on bone mineral and protein composition, microstructural and mechanical remodeling. Wistar rats were randomized into eight groups: G1: non-osteoporotic; G2: osteoporotic; G3, G4, and G5: osteoporotic+SA (0.2, 0.4, and 0.8 mg/kg, respectively); G6, G7, and G8: osteoporotic+SA (0.2, 0.4, and 0.8 mg/kg, respectively)+simvastatin (0.4, 0.6, and 1 mg/kg, respectively). Osteoporosis was induced by dexamethasone (7 mg/kg, i.m.) once a week for 5 weeks. All treatments were administered for 8 weeks. Dexamethasone increased serum levels of alkaline phosphatase, calcium, phosphorus, and urea, especially in non-treated animals, which showed severe osteoporosis. Dexamethasone also induced bone microstructural fragility and reduced mechanical resistance, which were associated with a marked depletion in mineral mass, collagenous and non-collagenous protein levels in cortical and cancellous bone. Although SA has attenuated osteoporosis severity, the effectiveness of drug therapy was enhanced combining alendronate and simvastatin. The restoration in serum parameters, organic and inorganic bone mass, and mechanical behavior showed a dose-dependent effect that was potentially related to the complementary mechanisms by which each drug acts to induce bone anabolism, accelerating tissue repair.

Dental health status in crack/cocaine-addicted men: a cross-sectional study.

The aim of this study was to evaluate the association between crack/cocaine addiction and dental health in men. Forty crack/cocaine-addicted patients and 120 nonaddicted patients (≥18 years) underwent full-mouth dental examinations. Decayed, missing, and filled teeth (DMFT) were identified using the criteria recommended by the World Health Organization. Crack/cocaine addiction was determined, based on the medical records and interviews of each patient. All drug-addicted patients used both crack and cocaine. The chi-square test and logistic regression analysis were used to assess the association between DMFT and crack/cocaine addiction (p ≤ 0.05). Decayed teeth showed a positive association with crack/cocaine addiction (odds ratio (OR) = 3.65; 95% confidence interval (CI), 1.68-7.92; p = 0.001), whereas filled and missing teeth showed a negative association (filled teeth: OR = 0.37; 95% CI, 0.18-0.76; p = 0.008; missing teeth: OR = 0.33; 95% CI, 0.13-0.81; p = 0.02). The DMFT was only associated with age (OR = 2.12; 95% CI, 1.11-4.08, p = 0.023). In the present population, crack/cocaine addiction was associated with a greater decayed teeth index and a lower filled and missing teeth index. Programs aimed to encourage self-esteem and encourage individuals to seek dental care are required for this population. Further studies using a larger sample size and studies with women are required to confirm the results.

Extracellular alpha-galactosidase from Debaryomyces hansenii UFV-1 and its use in the hydrolysis of raffinose oligosaccharides.

Raffinose oligosaccharides (RO) are the factors primarily responsible for flatulence upon ingestion of soybean-derived products. ROs are hydrolyzed by alpha-galactosidases that cleave alpha-1,6-linkages of alpha-galactoside residues. The objectives of this study were the purification and characterization of extracellular alpha-galactosidase from Debaryomyces hansenii UFV-1. The enzyme purified by gel filtration and anion exchange chromatographies presented an Mr value of 60 kDa and the N-terminal amino acid sequence YENGLNLVPQMGWN. The Km values for hydrolysis of pNP alphaGal, melibiose, stachyose, and raffinose were 0.30, 2.01, 9.66, and 16 mM, respectively. The alpha-galactosidase presented absolute specificity for galactose in the alpha-position, hydrolyzing pNPGal, stachyose, raffinose, melibiose, and polymers. The enzyme was noncompetitively inhibited by galactose (Ki = 2.7 mM) and melibiose (Ki = 1.2 mM). Enzyme treatments of soy milk for 4 h at 60 degrees C reduced the amounts of stachyose and raffinose by 100%.