Pierce into the Native Structure of Ata,a Trimeric Autotransporter of Acinetobacter baumannii ATCC 17978

International Journal of Peptide Research and Therapeutics - Acinetobacter baumannii is an important pathogen responsible for nosocomial infections worldwide. Trimeric autotransporters, the...     

Designing a Novel Multi-epitope Peptide Vaccine Against Pathogenic Shigella spp. Based Immunoinformatics Approaches

International Journal of Peptide Research and Therapeutics - Shigella spp. causes severe diarrhea and dysenteric disease, which known as shigellosis. Until now, no licensed vaccine is available for...     

Exploring dengue proteome to design an effective epitope-based vaccine against dengue virus

Dengue, a mosquito-borne disease, is caused by four known dengue serotypes. This infection causes a range of symptoms from a mild fever to a sever homorganic fever and death. It is a serious public health problem in subtropical and tropical countries. There is no specific vaccine currently available for clinical use and study on this issue is ongoing. In this study, bioinformatics approaches were used to predict antigenic, immunogenic, non-allergenic, and conserved B and T-cell epitopes as promising targets to design an effective peptide-based vaccine against dengue virus. Molecular docking analysis indicated the deep binding of the identified epitopes in the binding groove of the most popular human MHC I allele (human leukocyte antigens [HLA] A*0201). The final vaccine construct was created by conjugating the B and T-cell identified epitopes using proper linkers and adding an appropriate adjuvant at the N-terminal. The characteristics of the new subunit vaccine demonstrated that the epitope-based vaccine was antigenic, non-toxic, stable, and soluble. Other physicochemical properties of the new designed construct including isoelectric point value, aliphatic index, and grand average of hydropathicity were biologically considerable. Molecular docking of the engineered vaccine with Toll-like receptor 2 (TLR2) model revealed the hydrophobic interaction between the adjuvant and the ligand binding regions in the hydrophobic channel of TLR2. The study results indicated the high potential capability of the new multi-epitope vaccine to induce cellular and humoral immune responses against the dengue virus. Further experimental tests are required to investigate the immune protection capacity of the new vaccine construct in animal models.

Communicated by Ramaswamy H. Sarma     

Telmisartan anti‐cancer activities mechanism through targeting N‐cadherin by mimicking ADH‐1 function

This study aimed to investigate if Telmisartan as a novel N‐cadherin antagonist, can overcome cell migration of cancer cells. We investigated the mechanism and influence of Docetaxel and Telmisartan (as an analogous to ADH‐1, which is a well‐known N‐cadherin antagonist) on cancer cells. The effect of ADH‐1 and Telmisartan on cell attachment in PC3, DU145, MDA‐MB‐468 cell lines using recombinant human N‐cadherin was studied. Cell viability assay was performed to examine the anti‐proliferative effects of Telmisartan, ADH‐1 and Docetaxel. Migration was examined via wound healing assay, and apoptosis was determined by flow cytometry. The expression of AKT‐1 as a downstream gene of N‐cadherin signalling pathway was assayed by real‐time PCR. Treatment of PC3, MDA‐MB‐468 and DU145 cells with Telmisartan (0.1 µM) and ADH‐1 (40 µM) resulted in 50%, 58% and approximately 20% reduction in cell attachment to N‐cadherin coated plate respectively. It shows reduction of cell attachment in PC3 and MDA‐MB‐468 cell lines appeared to be more sensitive than that of DU145 cells to the Telmisartan and ADH‐1 treatments. Telmisartan (0.1 µM) and Docetaxel (0.01 nM) significantly reduced cell migration in PC3 and MDA‐MB‐468 cell lines compared with the control group. Using Real‐time PCR, we found that Telmisartan, Docetaxel and ADH‐1 had significant influence on the AKT‐1 mRNA level. The results of the current study for the first time suggest that, Telmisartan, exerts anti‐proliferation and anti‐migration effects by targeting antagonistically N‐cadherin. Also, these data suggest that Telmisartan as a less expensive alternative to ADH‐1 could potentiate Docetaxel anticancer effects.     

In Silico Sub-unit Hexavalent Peptide Vaccine Against an <Emphasis Type="Italic">Staphylococcus aureus</Emphasis> Biofilm-Related Infection

Staphylococcus aureus is responsible for significant and increasing number of hospital-and community-acquired infections worldwide. A pool of pathogenesis factors helps the bacterium to cause the range of mild to severe infections leading the high mortality and morbidity. Staphylococcus aureus and Candida albicans can be co-isolated from all human mucosal sites and are responsible for diverse infections. Vaccine design for related polymicrobial infections should consider the consortia of microorganisms responsible for the disease. In this study we considered biofilm mode of growth and polymicrobial nature of the infections caused by S. aureus. In the first phase of study the prediction of putative antigenic targets of S. aureus and C. albicans was conducted based on data mining and bioinformatic characterization of their proteins. Various properties of proteins were evaluated such as subcellular localization, hydrophilicity, repeat containing modules, beta turns, surface accessibility and number of antigenic determinants. The second phase includes various immunoinformatics analyses on six proteins include ALS, ClfA, FtmB, SdrE, Spa and Bap leading to design a novel sub-unit hexavalent vaccine. Several potential T cell and B-cell epitopes are present in our vaccine. Also the vaccine is expected to strongly induce IFN-gamma production. The amino acid sequence introduced here is expected to enhance cell-mediated and humoral responses against S. aureus biofilm-related infections to clear biofilm communities of S. aureus and intracellular colonies of pathogen as well as planktonic cells and thus reduces colonization and persistence.     

Characterization of Respiratory and Cardiac Motion from Electro-Anatomical Mapping Data for Improved Fusion of MRI to Left Ventricular Electrograms

Accurate fusion of late gadolinium enhancement magnetic resonance imaging (MRI) and electro-anatomical voltage mapping (EAM) is required to evaluate the potential of MRI to identify the substrate of ventricular tachycardia. However, both datasets are not acquired at the same cardiac phase and EAM data is corrupted with respiratory motion limiting the accuracy of current rigid fusion techniques. Knowledge of cardiac and respiratory motion during EAM is thus required to enhance the fusion process. In this study, we propose a novel approach to characterize both cardiac and respiratory motion from EAM data using the temporal evolution of the 3D catheter location recorded from clinical EAM systems. Cardiac and respiratory motion components are extracted from the recorded catheter location using multi-band filters. Filters are calibrated for each EAM point using estimates of heart rate and respiratory rate. The method was first evaluated in numerical simulations using 3D models of cardiac and respiratory motions of the heart generated from real time MRI data acquired in 5 healthy subjects. An accuracy of 0.6–0.7 mm was found for both cardiac and respiratory motion estimates in numerical simulations. Cardiac and respiratory motions were then characterized in 27 patients who underwent LV mapping for treatment of ventricular tachycardia. Mean maximum amplitude of cardiac and respiratory motion was 10.2±2.7 mm (min = 5.5, max = 16.9) and 8.8±2.3 mm (min = 4.3, max = 14.8), respectively. 3D Cardiac and respiratory motions could be estimated from the recorded catheter location and the method does not rely on additional imaging modality such as X-ray fluoroscopy and can be used in conventional electrophysiology laboratory setting.     

Experimental Analysis of E2BB (LTIIb) Signal Peptide in Secretory Production of Reteplase in Escherichia coli

International Journal of Peptide Research and Therapeutics - Recombinant reteplase is the truncated form of tissue plasminogen activator. Signal peptides play a pivotal role in the secretion of...     

In Silico Designing a Candidate Vaccine Against Breast Cancer

International Journal of Peptide Research and Therapeutics - Breast cancer (BC) is the most common type of women’s cancer with a prevalence of about 25%, although it is rare in men...     

Experimental Evaluation of In Silico Selected Signal Peptides for Secretory Expression of Erwinia Asparaginase in Escherichia coli

International Journal of Peptide Research and Therapeutics - Erwinia chrysanthemi asparaginase is an important drug used in cancer treatment, especially in acute lymphoblastic leukemia (ALL)....     

An Augmented Lagrangian Based Compressed Sensing Reconstruction for Non-Cartesian Magnetic Resonance Imaging without Gridding and Regridding at Every Iteration

Background

Non-Cartesian trajectories are used in a variety of fast imaging applications, due to the incoherent image domain artifacts they create when undersampled. While the gridding technique is commonly utilized for reconstruction, the incoherent artifacts may be further removed using compressed sensing (CS). CS reconstruction is typically done using conjugate-gradient (CG) type algorithms, which require gridding and regridding to be performed at every iteration. This leads to a large computational overhead that hinders its applicability.

Methods

We sought to develop an alternative method for CS reconstruction that only requires two gridding and one regridding operation in total, irrespective of the number of iterations. This proposed technique is evaluated on phantom images and whole-heart coronary MRI acquired using 3D radial trajectories, and compared to conventional CS reconstruction using CG algorithms in terms of quantitative vessel sharpness, vessel length, computation time, and convergence rate.

Results

Both CS reconstructions result in similar vessel length (P = 0.30) and vessel sharpness (P = 0.62). The per-iteration complexity of the proposed technique is approximately 3-fold lower than the conventional CS reconstruction (17.55 vs. 52.48 seconds in C++). Furthermore, for in-vivo datasets, the convergence rate of the proposed technique is faster (60±13 vs. 455±320 iterations) leading to a ∼23-fold reduction in reconstruction time.

Conclusions

The proposed reconstruction provides images of similar quality to the conventional CS technique in terms of removing artifacts, but at a much lower computational complexity.