In Peru, 20-28% of people has hypersensitivity to allergens; of these 80% are sensible to at least one house dust mite. The immunotherapy is based on the administration of increasing doses of protein extracts or purified proteins of allergens. These treatments seem to be effective in some cases but still we do not have yet an equilibrium between stability, specificity and immunogenicity. This work analyzes in silico models of antigen-antibody of house dust mite allergens of group 1 of Acarus siro, Euroglyphus maynei, Sarcoptes scabiei y Tyrophagus putrescentiae. We obtained structural in silico models using I-tasser. The assymetric unit of 4PP1 is formed by two DerP1:Fab5H8 complexes; to generate interfaces models we replaced chain A by the allergen model in analysis. Then, we minimized the potential energy using the Steepest Descent algorithm and finally we analyzed the interactions in the allergen:IgE interface.

We were able to identify three antibody aminoacids interacting with the four allergens in study (Tyr32, Tyr50, Lys92), one that interacts with SarS1 and TyrP1 and others six that interact only with EurM1 and AcaS1. Our results show the identification of possible regions important in the recognition of group 1 allergens, also we show other aminoacids that could recognize specifically a subgroup of these allergens.

Cyanide is a toxic compund widely used in mining. Naturally some bacterias are capable to degrade this molecules. CynD is a type of prokaryote enzyme able to degrade cyanide and its active form seems to be an oligomer. Several attempts to obtain structural models of CynD by crystallography has not success mainly due the insolubility of the oligomeric state of this protein. In this work we aimed to use in silico tools to identify the aminoacids implied in the oligomerization surfaces. These knowledge could lead us to rationally design CynD variants that are not able to form tights oligomers stabilizing other forms such as dimers or monomers that could be better in purification and crystallization assays. For this, we prepared structural models using SWISS-MODEL, PHYRE2, I-TASSER and ROBETTA. Then, we analyzed chemical parameters of the models using RAMPAGE, PDBsum and ModFold6. Next, we did dimer models using dockings in Hex. The monomer and dimer models were used to perform molecular dynamics simulation in order to determine flexible regions, important aminoacids stabilizing the dimeric interface and the stability of the dimer form. We obtain models with good chemical parameters to perform the dynamics simulation. These assays allow us to identify flexible regions that could be removed to stabilize the dimer or monomer in solution. Finally, the docking showed us which are the probable aminoacids stabilizing the dimer interface. Experimental data is now neccesary to confirm those hypotheses.

JANDHYLA, D.; Berman, M.;Meyeres, P.; Sewell, B.; Willson, R.; Benedik, M. cynD, the Cyanide Dihidratase from Bacillus pumilus: Gene Cloning and Structural Studies. Applied and Environmental Microbiology. Vol 69, No. 8. Aug. 2003. p 4794 – 4805

Crum, M. A. N., Park, J. M., Mulelu, A. E., Sewell, B. T., & Benedik, M. J. (2015). Probing C-terminal interactions of the Pseudomonas stutzeri cyanide-degrading CynD protein. Applied microbiology and biotechnology, 99(7), 3093-3102.

The study of key molecular mechanisms of mitochondrial dysfunctions, which are responsible for neurodegenerative diseases, is a critical step to assist for the diagnosis and therapy success. In this regard, we suggest an alternative of treatment on neurodegenerative disorders-based on Single-Walled Carbon Nanotubes (SWCNT) as potential mito protective -(Phe)-F0-ATPase targeting nanoparticles toward Precision Molecular Nanomedicine against pathological ATP-hydrolysis conditions. Herein, we used ab initio computational simulation to analyze the structural and electronic properties from SWCNT-family with zigzag topologies (n, m - Hamada indices n > 0; m = 0) like: SWCNT-pristine, SWCNT-COOH, SWCNT-OH, SWCNT-monovacancy interacting with the critical (Phe)-residues of the mitochondrial F0-ATPase and using oligomycin A (specific Phe-F0-ATPase inhibitor) as reference control. Then, we show that the SWCNT-family can be potentially used to selectively inhibit the (Phe)-F0-ATPase activity liked to pathological mitochondrial ATP-hydrolysis associated to human neurodegenerative disorders by using DFT-ab initio simulation. The in-silico results suggest the formation of more stable complexes of interaction following the order: SWCNT-COOH/F0-ATPase complex (1.79 eV) > SWCNT-OH/F0-ATPase complex (0.61 eV) > SWCNT/F0-ATPase complex (0.45 eV) > SWCNT-monovacancy/F0-ATPase complex (0.43 eV) based on the strength of the chemisorption interactions. These theoretical evidences open new horizons towards mito-target precision nanomedicine.

Welcome to the MODEC2018 workshop. This is Amazon State University's (UEA) third workshop, devoted to the promotion and application of the Multidisciplinary Sciences to the development of natural products and agro-industrial processes in Ecuadorian Amazon regions. This includes the application of Information and Communications Technologies (ICTs) for data analysis and computational model including the fields of Agro-industrial Engineering, Chemistry, Chemical Engineering, Biotechnology, Veterinary Medicine, and/or Environmental Sciences, etc. We invite you to visit the official web of the workshop: https://sciforum.net/conference/mol2net-04/modec-03

Atomic Weighted Vectors (AWVs) are vectors that contain the codified information of molecular structures, which can apply to a set of Aggregation Operators (AOs) to calculate total and local molecular descriptors (MDs). This article presents an exploratory study of a new tool useful for drug discovery using different datasets, such as DRAGON and Sutherland’s datasets, as well as their comparison with other well-known approaches. In order to evaluate the performance of the tool, several statistics and QSAR/QSPR experiments were performed. Variability analyses are used to quantify the information content of the AWVs obtained from the tool, by the way of an information theory-based algorithm. Principal Components Analysis (PCA) is used to analyze the orthogonality of these descriptors, for which the new MDs from AWVs provide different information from those codified by DRAGON descriptors (0-2D). The QSAR models are obtained for every Sutherland’s dataset, according to the original division into training/test sets, by means of the Multiple Linear Regression with Genetic Algorithm (MLR-GA). These models have been validated and compare favorably to several approaches previously published, using the same benchmark datasets. The obtained results show that this tool should be a useful strategy for the QSAR/QSPR studies, despite its simplicity.

We can combine Perturbation Theory (PT) and Machine Learning (ML) model to seek PTML models useful to explore the effect over drug activity of changes or (perturbations) in multiple parameters or experimental conditions c_j. This include changes in drug chemical structure or assay conditions like c₀ = the biological parameter used (K_i, IC₅₀, etc.), c₁ = drug target, c₂ = organism of assay, c₃ = cell line, etc.

In this work used PTML techniques to explore the Big Data set of >800000 preclinical assays of drugs. These assays reported in CheMBL involved drugs targeting proteins related to G-protein signaling pathways. The data set included 343,738 drugs, 185 experimental parameters, 56 organisms of assay, 52 cellular lines, 592 target proteins. The model predicted correctly 85.4% of control cases (Specificity) and 95.8% of active compounds in training series (Sensitivity). The model also predicted correctly 95.8% and 85.4% cases in external validation series.

It is estimated that in developing countries, 60% or more of waste is lignocellulosic material that can be used in recycling processes. The purpose of this research has been aimed to find enzymatic cocktails from bacteria native to Ecuador that allow the degradation of lignocellulosic material, through the search of microorganisms collected in the Andean, Amazon and Antarctic regions, which can be introduced in a process of enzymatic hydrolysis of bagasse at  industrial scale. For this, qualitative and quantitative assays were carried out to measure the endoglucanase, exoglucanase and filter paper activity of the microorganisms and their enzymatic cocktails, as well as assays of enzymatic hydrolysis of the sugarcane. In addition, the value of the investments for Bacillus sp bacterium enzymatic cocktail production, and the total production cost were calculated.

It was identified that Peniccillium sp., Was the species with the highest activity of filter paper, showing 0.0073 UPF and a glucose yield of 11.968 in 100 grams of bagasse, which opens up the possibility of its use, in industrial processes. From this best strain of microorganism, the equipment was sized on an industrial scale and it was concluded that the investment cost would benefit the country.

The study shows that it is possible to generate a proprietary technology for the production of cellulolytic enzyme crudes in Ecuador.

Arachidonate 5-lipoxygenase (ALOX5) is belongs to lipoxygenase family of enzymes. It metamorphose essential fatty acids substrates into leukotrienes as well as a wide range of other biologically active products. Pancreatic adenocarcinoma remains one of the most fatal animocity. The incidence of pancreatic cancer has steadily increased over the past four decades. Almost 30% of patients with pancreatic cancer present with large, locally advanced tumors in the absence of distant metastases. Because surgical resection is frequently contraindicated by vascular invasion, locally advanced pancreatic cancer has a dismal prognosis with a 6-10-month median survival. The majority of patients present with advanced disease at time of diagnosis resulting in a 5-year survival rate of 7%.Previous studies shown that 5-lipoxygenase (5-LOX) mRNA and protein are expressed in human pancreatic cancer cell lines and that triptolide treatment significantly down regulates 5-LOX expression. Furthermore, LOX inhibitors were found to block proliferation of human pancreatic cancer cells whereas the LOX metabolites 5-HETE and 12-HETE were found to stimulate cancer growth through activation of the p44/42 mitogen-activated protein kinase and PI3/Akt kinase pathways. ALOX5 products, particularly 5-hydroxyeicosatetraenoic acid and 5-oxo-eicosatetraenoic acid, promote the proliferation of these ALOX5 aberrantly expressing tumor cell lines suggesting that ALOX5 acts as a pro-malignancy factor for them and by extension their parent tumors. Thus, for deterrence and treatment of pancreatic cancer induction of 15-LOX-1 expression may be an attractive option for the.5-LOX-derived leukotriene in the pathogenesis of cancer.

The present appraisal is sought to identify a high affinity molecule targeting against ALOX 5 for the treatment of pancreatic cancer through molecular docking studies. 27 established compounds were obtained from various literature studies. The ligand compounds were further prepared using Schrodinger suit software. Protein 3D structure of ALOX5 was obtained from Protein Data Bank(PDB) using PDB ID: 3V92 . Molecular docking studies was performed using flexible docking software, Molegro Virtual Docker. The compound AM-679(Pubchem cid: 71308150), found to be the most effective compound which bound with ALOX5. Further studies can be perform on AM-679 by employ molecular descriptors, Virtual Screening, ADMET, Pharamacophore, Pharmacokinetics studies etc.

Breast cancer is the most common malignancy among women and accounts for second most common cause of the cancer related death. This is majorlyreported as a heterogeneous disease with different subtypes defined by its hormone receptor such as estrogen (ER), progesterone (PR), human epidermal growth factor receptor-2(HER2). Dysregulation in breast cancer most frequent associated with progression of PI3K/AKT/mTOR pathway. The routine activity of our body such as cell survival, cell division, cell proliferation, programmed cell death, protein synthesis, and integration of metabolism controls by this pathway. The mammalian target of rapamycin is a conserved serine/threonine protein kinase, belongs to PI3K-kinase related family, which forms two distinct multi-protein complexes called mTORC1 and mTORC2. The mTOR signaling pathway integrates extracellular signals to intracellular and this signaling is activated in various cancer, directed by mutation in the gene-coding receptor tyrosine kinase, Ras, PI3K, and PTEN that is involved in numerous cellular processes. The aberrant activation of mTOR signaling pathway identified in various malignancy including breast. Hyperactivation of mTOR commonly associated with cellular proliferation, and neogenesis. In variety of cancer, phosphatase and tensin homologue deleted in chromosome 10(PTEN) is mutationally inactivated, leads to increase in overall mTOR activity. This hyper activated mTOR gene produce mRNAs that encode various growth factors, cell death inhibitor, angiogenesis factors, inducer of cell growth which overall support carcinogenesis. Overall features of mTOR signaling pathway have provided a higher level of interest in targeting mTOR as a potential therapeutic agent for effective treatment. Present study aims to identify high affinity compound against mTOR for the treatment of breast cancer. Molecular docking studies was performed with 40 mTOR inhibitor using Schrodinger suite. Out of 40 compounds, compound SF1126 found with the highest affinity with the targeted protein mTOR. This study was asserted with pharmacophore mapping discussed preferable interaction with mTOR. The compound determined in this study can be further used in vivo and in vitro studies to identify ADMET properties.

Eucalyptus nitens Maiden is a fast growing species used principally for pulpwood and solid-wood production, it is preferred over other Eucalyptus species at high elevation, due its cold tolerance. Studies show that the frost tolerance in Eucalyptus spp. is controlled by genetic factor. One tools that has been used in recent years to analyze gene expression is the transcriptomic analysis of sequences obtained by RNA-seq. There are many bioinformatics tools that allow this analysis, however, not all have the same precision. Among the most used in the detection of differentially expressed genes, are DEGseq and edgeR, so the objective was to identify by in silico analysis, genes differentially expressed during the low temperature acclimatization of E. nitens, associating these to tolerance to freezing. Three treatment conditions was used: acclimated before freezing (CABF), cold acclimated after freezing (CAAF), deacclimated (DA) and the control, non- acclimated (NA). The results obtained suggest that it is better to use the package edgeR for the analysis of differential expression, because it detects a smaller amount of false positives, it is when there are a few biological replicates and increases its fidelity when analyzing the biological variability of the samples. The NA-ADH comparison was the one with the most genes detected, while the AAH-DA was the lowest. In all comparisons we found a greater amount of negatively regulated genes than positively regulated genes. Within the differentially expressed genes with significance for the key comparisons we found proteins dehydrins and CBF transcription factors, important in the process of acclimatization at low temperature. Through the analysis of differentially expressed genes and genetic ontology LEA (Late embryogenesis abundant) genes were identified, within which EniDHN1 and EniDHN2, hydrophilic proteins and the CBF (C-repeat binding factor) transcription factor can be highlighted as genes asssociated with tolerance to low temperatures.