Benzohydroxamate and nitrobenzohydroxamate affect membrane order: Correlations between spectroscopic and molecular dynamics to approach tuberculosis.

This work correlates the effects of benzohydroxamate (BH) and nitrobenzohydroxamate (NBH) anions in two membrane models which may be used for anti-tuberculosis (anti-TB) spectroscopic studies and/or computational studies. Firstly, the BH and NBH influence in the physico-chemical properties of soy asolectin (ASO)-based large multilamellar vesicles (MLVs) were evaluated by spectroscopic and calorimetric studies. In parallel, the BH and NBH interaction with a Mycobacterium tuberculosis (Mtb) inner membrane model, composed of phosphatidyl-myo-inositol-dimannoside (PIM), was investigated by molecular dynamics (MD) simulations.

Phylogenetic analysis, computer modeling and catalytic prediction of an Amazonian soil β-glucosidase against a soybean saponin.

Saponins are amphipathic glycosides with detergent properties present in vegetables. These compounds, when ingested, can cause difficulties in absorbing nutrients from food and even induce inflammatory processes in the intestine. There is already some evidence that saponins can be degraded by β-glucosidases of the GH3 family.

Phosphoproteomics data-driven signalling network inference: Does it work?

The advent of global phosphoproteome profiling has led to wide phosphosite coverage and therefore the opportunity to predict kinase-substrate associations from these datasets. However, the regulatory kinase is unknown for most substrates, due to biased and incomplete database annotations. In this study we compare the performance of six pairwise measures to predict kinase-substrate associations using a data driven approach on publicly available time resolved and perturbation mass spectrometry-based phosphoproteome data.

Chemoprotection mediated by açaí berry (Euterpe oleracea) in white shrimp Litopenaeus vannamei exposed to the cyanotoxin saxitoxin analyzed by in vivo assays and docking modeling.

Saxitoxin (STX) is a neurotoxic cyanotoxin that also generate reactive oxygen species, leading to a situation of oxidative stress and altered metabolism. The Amazonian fruit açaí Euterpe oleracea possesses a high concentration of antioxidant molecules, a fact that prompted us to evaluate its chemoprotection activity against STX toxicity (obtained from samples of Trichodesmium sp. collected in the environment) in the shrimp Litopenaeus vannamei.

E-Volve: understanding the impact of mutations in SARS-CoV-2 variants spike protein on antibodies and ACE2 affinity through patterns of chemical interactions at protein interfaces.

Background: The SARS-CoV-2 pandemic reverberated, posing health and social hygiene obstacles throughout the globe. Mutant lineages of the virus have concerned scientists because of convergent amino acid alterations, mainly on the viral spike protein. Studies have shown that mutants have diminished activity of neutralizing antibodies and enhanced affinity with its human cell receptor, the ACE2 protein.

A higher flexibility at the SARS-CoV-2 main protease active site compared to SARS-CoV and its potentialities for new inhibitor virtual screening targeting multi-conformers.

The main-protease (M) catalyzes a crucial step for the SARS-CoV-2 life cycle. The recent SARS-CoV-2 presents the main protease (M) with 12 mutations compared to SARS-CoV (M). Recent studies point out that these subtle differences lead to mobility variances at the active site loops with functional implications.

Mefloquine synergism with anti-tuberculosis drugs and correlation to membrane effects: Biologic, spectroscopic and molecular dynamics simulations studies.

Studies displaying the combination of mefloquine (MFL) with anti-tuberculosis (TB) substances are limited in the literature. In this work, the effect of MFL-association with two first-line anti-TB drugs and six fluoroquinolones was evaluated against Mycobacterium tuberculosis drug resistant strains. MFL showed synergistic interaction with isoniazid, pyrazinamide, and several fluoroquinolones, reaching fractional inhibitory concentration indexes (FICIs) ranging from 0.

Long-chain fatty dihydropyridines: Docking calcium channel studies and antihypertensive activity.

Aims: From the synthesis of 43 lipophilic dihydropyridines, the aim of this study was to verify whether the new dihydropyridines have calcium channel affinity using coupling studies and to determine antihypertensive and antioxidant properties, as well as toxicology and toxicity nifedipine and three new compounds, were chosen from the previous results.

Materials And Methods: The animals were treated for 56 days, 28 days with N (ω) -nitro-L-arginine methyl ester to induce hypertension, and then treated for another 28 days with the new di- hydropyridine and the standard drug nifedipine. Throughout the treatment the animals had their blood pressure measured and their heart rate checked by pletysmography.

Graphene oxide and GST-omega enzyme: An interaction that affects arsenic metabolism in the shrimp Litopenaeus vannamei.

Arsenic (As) is one of the most widespread contaminants; it is found in almost every environment. Its toxic effects on living organisms have been studied for decades, but the interaction of this metalloid with other contaminants is still relatively unknown, mainly whether this interaction occurs with emerging contaminants such as nanomaterials. To examine this relationship, the marine shrimp Litopenaeus vannamei was exposed for 48 h to As, graphene oxide (GO; two different concentrations) or a combination of both, and gills, hepatopancreas and muscle tissues were sampled.

A comparison of classifiers for predicting the class color of fluorescent proteins.

Fluorescent proteins have been applied in a wide variety of fields ranging from basic science to industrial applications. Apart from the naturally occurring fluorescent proteins, there is a growing interest in genetically modified variants that emit light in a specific wavelength. Genetically modifying a protein is not an easy task, especially because the exchange of one residue by other has to achieve the desired property while maintaining protein stability.

Computational MitoTarget Scanning Based on Topological Vacancies of Single-Walled Carbon Nanotubes with the Human Mitochondrial Voltage-Dependent Anion Channel (hVDAC1).

We present an in silico approach for modeling the noncovalent interactions between the human mitochondrial voltage-dependent anion channel (hVDAC1) and a family of single-walled carbon nanotubes (SWCNTs) with a defined pattern of topological vacancies ( v = 1-16), obtained by removing atoms from the SWCNT surface. The general results showed more stable docking interaction complexes (SWCNT-hVDAC1), with more negative Gibbs free energy of binding affinity values, and a strong dependence on the vacancy number ( R = 0.93) and vacancy formation energy ( R = 0.

Systems biology approach identifies key regulators and the interplay between miRNAs and transcription factors for pathological cardiac hypertrophy.

Pathological cardiac hypertrophy (CH) is associated with increased heart failure risk and sudden cardiac death. Several transcription factors (TFs) and miRNAs were implicated in CH, and their high combinatorial action in gene expression regulation is becoming more clear. We adopted a systems biology approach to construct a comprehensive TF-miRNA co-regulatory network in CH and systematically characterize its structure, from node- to systems-level properties.

Silencing the OCT4-PG1 pseudogene reduces OCT-4 protein levels and changes characteristics of the multidrug resistance phenotype in chronic myeloid leukemia.

Cancer stem cells show epigenetic plasticity and intrinsic resistance to anti-cancer therapy, rendering capable of initiating cancer relapse and progression. Transcription factor OCT-4 regulates various pathways in stem cells, but its expression can be regulated by pseudogenes. This work evaluated how OCT4-PG1 pseudogene can affect OCT-4 expression and mechanisms related to the multidrug resistance (MDR) phenotype in FEPS cells.

A Computational Method to Propose Mutations in Enzymes Based on Structural Signature Variation (SSV).

With the use of genetic engineering, modified and sometimes more efficient enzymes can be created for different purposes, including industrial applications. However, building modified enzymes depends on several in vitro experiments, which may result in the process being expensive and time-consuming. Therefore, computational approaches could reduce costs and accelerate the discovery of new technological products.

Molecular modelling and competitive inhibition of a Mycobacterium tuberculosis multidrug-resistance efflux pump.

Tuberculosis is a major cause of mortality and morbidity in developing countries, and the emergency of multidrug and extensive drug resistance cases is an utmost issue on the control of the disease. Despite the efforts on the development of new antibiotics, eventually there will be strains resistant to them as well. Efflux plays an important role in the evolution of resistance in Mycobacterium tuberculosis.

Cytoprotection of lipoic acid against toxicity induced by saxitoxin in hippocampal cell line HT-22 through in silico modeling and in vitro assays.

Saxitoxins (STXs) are potent neurotoxins that block voltage-gated channels in neurons and induce cytotoxicity. These toxins not only can generate reactive oxygen species but also can alter antioxidant levels, promoting oxidative stress. Under this pro-oxidant situation, the use of the antioxidant lipoic acid (LA) can represent a chemoprotective alternative to minimize the deleterious effects induced by neurotoxins as STXs.

Decrypting Strong and Weak Single-Walled Carbon Nanotubes Interactions with Mitochondrial Voltage-Dependent Anion Channels Using Molecular Docking and Perturbation Theory.

The current molecular docking study provided the Free Energy of Binding (FEB) for the interaction (nanotoxicity) between VDAC mitochondrial channels of three species (VDAC1-Mus musculus, VDAC1-Homo sapiens, VDAC2-Danio rerio) with SWCNT-H, SWCNT-OH, SWCNT-COOH carbon nanotubes. The general results showed that the FEB values were statistically more negative (p < 0.05) in the following order: (SWCNT-VDAC2-Danio rerio) > (SWCNT-VDAC1-Mus musculus) > (SWCNT-VDAC1-Homo sapiens) > (ATP-VDAC).

Inference of regulatory networks with a convergence improved MCMC sampler.

Background: One of the goals of the Systems Biology community is to have a detailed map of all biological interactions in an organism. One small yet important step in this direction is the creation of biological networks from post-genomic data. Bayesian networks are a very promising model for the inference of regulatory networks in Systems Biology.

An infrastructure to mine molecular descriptors for ligand selection on virtual screening.

The receptor-ligand interaction evaluation is one important step in rational drug design. The databases that provide the structures of the ligands are growing on a daily basis. This makes it impossible to test all the ligands for a target receptor.

Comparing the reconstruction of regulatory pathways with distinct Bayesian networks inference methods.

Background: Inference of biological networks has become an important tool in Systems Biology. Nowadays it is becoming clearer that the complexity of organisms is more related with the organization of its components in networks rather than with the individual behaviour of the components. Among various approaches for inferring networks, Bayesian Networks are very attractive due to their probabilistic nature and flexibility to incorporate interventions and extra sources of information.

Gene regulatory network reconstruction by Bayesian integration of prior knowledge and/or different experimental conditions.

There have been various attempts to improve the reconstruction of gene regulatory networks from microarray data by the systematic integration of biological prior knowledge. Our approach is based on pioneering work by Imoto et al. where the prior knowledge is expressed in terms of energy functions, from which a prior distribution over network structures is obtained in the form of a Gibbs distribution.

Bayesian integration of biological prior knowledge into the reconstruction of gene regulatory networks with Bayesian networks.

There have been various attempts to improve the reconstruction of gene regulatory networks from microarray data by the systematic integration of biological prior knowledge. Our approach is based on pioneering work by Imoto et al., where the prior knowledge is expressed in terms of energy functions, from which a prior distribution over network structures is obtained in the form of a Gibbs distribution.

Reconstructing gene regulatory networks with bayesian networks by combining expression data with multiple sources of prior knowledge.

There have been various attempts to reconstruct gene regulatory networks from microarray expression data in the past. However, owing to the limited amount of independent experimental conditions and noise inherent in the measurements, the results have been rather modest so far. For this reason it seems advisable to include biological prior knowledge, related, for instance, to transcription factor binding locations in promoter regions or partially known signalling pathways from the literature.