Bioimpacts最新文献

Introduction: The present study attempts to identify potential targets of H. pylori for novel inhibitors from therapeutic herb, mango ginger (Curcuma amada Roxb.). Methods: Crystal structure of all the selected drug targets obtained from Protein Data Bank (PDB) were subjected to molecular docking against a total of 130 compounds (found to have biological activity against H. pylori ) were retrieved from public databases. Compounds with good binding affinity were selected for Prime MM-GBSA rescoring and molecular dynamics (MD) simulation. Final list of compounds were taken for ADMET predictions. Results: Based on binding affinity denoted by glide score and ligand efficiency, mango ginger compounds were found selective to shikimate kinase and type II dehydroquinase through hydrogen bonding and salt bridge interactions. Stability of the interactions and free energy calculations by Prime MM-GBSA results confirmed the affinity of mango ginger compounds towards both shikimate kinase and type II dehydroquinase. From the above results, 15 compounds were calculated for ADMET parameters, Lipinski's rule of five, and the results were found promising without any limitations. MD simulations identified gentisic acid as hit compound for shikimate kinase of H. pylori. Conclusion: Current study could identify the in silico potential of mango ginger compounds against shikimate kinase and type II dehydroquinase targets for H. pylori infections and are suitable for in vitro and in vivo evaluation.

Introduction: Histone modifying enzymes include several classes of enzymes that are responsible for various post-translational modifications of histones such as methylation and acetylation. They are important epigenetic factors, which may involve several diseases and so their assay, as well as screening of their inhibitors, are of great importance. Herein, a bioassay based on terbium-to-quantum dot (Tb-to-QD) time-resolved Förster resonance energy transfer (TR-FRET) was developed for monitoring the activity of G9a, the euchromatic histone-lysine N-methyltransferase 2. Overexpression of G9a has been reported in some cancers such as ovarian carcinoma, lung cancer, multiple myeloma and brain cancer. Thus, inhibition of this enzyme is important for therapeutic purposes. Methods: In this assay, a biotinylated peptide was used as a G9a substrate in conjugation with streptavidin-coated ZnS/CdSe QD as FRET acceptor, and an anti-mark antibody labeled with Tb as a donor. Time-resolved fluorescence was used for measuring FRET ratios. Results: We examined three QDs, with emission wavelengths of 605, 655 and 705 nm, as FRET acceptors and investigated FRET efficiency between the Tb complex and each of them. Since the maximum FRET efficiency was obtained for Tb to QD705 (more than 50%), this pair was exploited for designing the enzyme assay. We showed that the method has excellent sensitivity and selectivity for the determination of G9a at concentrations as low as 20 pM. Furthermore, the designed assay was applied for screening of an enzyme inhibitor, S-(5'-Adenosyl)-L-homocysteine (SAH). Conclusion: It was shown that Tb-to-QD FRET is an outstanding platform for developing a homogenous assay for the G9a enzyme and its inhibitors. The obtained results confirmed that this assay was quite sensitive and could be used in the field of inhibitor screening.

This biography highlights the scientific trajectory of Professor Mohammad A. Rafi, Ph.D., who, in particular, has greatly advanced the field of neurodegenerative disorders during his long and successful tenure at Jefferson Medical College, Thomas Jefferson University. This Editorial recognizes, above all, Professor Rafi's significant contributions to the study of lysosomal storage disorders as they relate to Krabbe Disease.

Introduction: Inflammation is the primary response caused due to harmful stimuli which are followed by the increased draining of plasma and immune cells from the body into the site of the injured tissue. A signaling cascade of growth factors and cytokines propagates and eventually matures in the inflammatory site involving the blood vessels and immune markers within the injured tissue in order to promote the renewal of the degenerated tissue. During a chronic disorder like diabetic foot ulcer, there is an obstinate inflammation which may act as a prime factor for limb amputation and upon persistent prevalence may even lead to death. Methods: This study focuses on the mode of action of ALK-F (alkaloid fraction) isolated from Adhatoda vasica in attenuating the nitric oxide production which was estimated by Griess assay, tumor necrosis factor-α (TNF-α), and interleukin-6 (IL-6) expression was analyzed by ELISA and expression of COX-2 and iNOS by RT-PCR and western blotting in LPS stimulated RAW 264.7 macrophages. Total intracellular ROS was analyzed by DCFH-DA probing and the presence of quinazoline alkaloid (vasicine) in the ALK-F was evidenced by high performance liquid chromatography (HPLC). Results: The ALK-F of A. vasica exhibited a significant inhibitory effect on LPS elicited nitrite production (13.2 ± 1.06 µM), iNOS, and COX-2 (2.6 and 3.3 fold) in a dose-dependent manner. There was a significant decrease in the generation of these pro-inflammatory cytokines TNF-α (1102 ± 1.02 pg/mL) and IL-6 (18 ± 0.87 ng/mL) and total intracellular ROS in the highest tested concentrations (1 µg and 10 µg) of ALK-F of A. vasica. HPLC analysis by the gradient elution method revealed the presence of 12% of quinazoline alkaloid vasicine in the crude alkaloid fraction. Conclusion: Thus this study communally suggests that attenuation of nitric oxide and the dysregulation of genes responsible for inflammation which deliberates A. vasica to conflict against inflammation and provide remedial benefits in diabetic wound care.

Introduction: The genus Morus is well known for its medicinal benefits from time immemorial. The present work reported the health-promoting properties of the biologically active molecules present in different species of the genus Morus. Methods: Different solvent extracts of the three plant species of Morus were investigated initially for their antioxidant effects, followed by in vitro anticancer studies against MCF7 and 3T3 cell lines along with their bioactive isolates viz. cathafuran-B, moracin-M, and Ursolic acid. Further, in silico docking studies were performed for the isolated compounds to predict their probable mode of interaction with P38Map Kinase. Results: The results indicated that all three species under study possessed remarkable antioxidant effects which are supported by a linear and positive correlation between different antioxidant activities. The in vitro cell antiproliferative test indicated that the cell survivability decreased with an increase in the concentration of extracts and compounds. Among the extracts, M. laevigata methanol extract showed 21.57, 6.27% of cell survival against MCF7 and 3T3 cell lines at 800 µg/mL concentration while among the isolated compounds, ursolic acid showed 8.46, 17.58% of cell survival at 200 µg/mL concentration. Among the three compounds docked, ursolic acid showed greater binding affinity towards the target protein in terms of its binding energy (-9.97 kJ/mol) compared to Cathafuran B (-8.35 kJ/mol) and Moracin M (-6.91 kJ/mol). Conclusion: The study generated interesting results in terms of health benefits of Morus species by documenting their antioxidant and anticancer activities, thereby validating the folk claims of therapeutic benefits of mulberry.

Introduction: In recent decades, the growing rate of cancer incidence is a big concern for most societies. Due to the genetic origins of cancer disease, its internal structure is necessary for the study of this disease. Methods: In this research, cancer data are analyzed based on DNA sequences. The transition probability of occurring two pairs of nucleotides in DNA sequences has Markovian property. This property inspires the idea of feature dimension reduction of DNA sequence for overcoming the high computational overhead of genes analysis. This idea is utilized in this research based on the Markovian property of DNA sequences. This mapping decreases feature dimensions and conserves basic properties for discrimination of cancerous and non-cancerous genes. Results: The results showed that a non-linear support vector machine (SVM) classifier with RBF and polynomial kernel functions can discriminate selected cancerous samples from non-cancerous ones. Experimental results based on the 10-fold cross-validation and accuracy metrics verified that the proposed method has low computational overhead and high accuracy. Conclusion: The proposed algorithm was successfully tested on related research case studies. In general, a combination of proposed Markovian-based feature reduction and non-linear SVM classifier can be considered as one of the best methods for discrimination of cancerous and non-cancerous genes.

Introduction: Riboswitches are short regulatory elements generally found in the untranslated regions of prokaryotes' mRNAs and classified into several families. Due to the binding possibility between riboswitches and antibiotics, their usage as engineered regulatory elements and also their evolutionary contribution, the need for bioinformatics tools of riboswitch detection is increasing. We have previously introduced an alignment independent algorithm for the identification of frequent sequential blocks in the families of riboswitches. Herein, we report the application of block location-based feature extraction strategy (BLBFE), which uses the locations of detected blocks on riboswitch sequences as features for classification of seed sequences. Besides, mono- and dinucleotide frequencies, k-mer, DAC, DCC, DACC, PC-PseDNC-General and SC-PseDNC-General methods as some feature extraction strategies were investigated. Methods: The classifiers of the Decision tree, KNN, LDA, and Naïve Bayes, as well as k-fold cross-validation, were employed for all methods of feature extraction to compare their performances based on the criteria of accuracy, sensitivity, specificity, and f-score performance measures. Results: The outcome of the study showed that the BLBFE strategy classified the riboswitches indicating 87.65% average correct classification rate (CCR). Moreover, the performance of the proposed feature extraction method was confirmed with average values of 94.31%, 85.01%, 95.45% and 85.38% for accuracy, sensitivity, specificity, and f-score, respectively. Conclusion: Our result approved the performance of the BLBFE strategy in the classification and discrimination of the riboswitch groups showing remarkable higher values of CCR, accuracy, sensitivity, specificity and f-score relative to previously studied feature extraction methods.

Introduction: The serum metabolomics approach has been used to identify metabolite biomarkers that can diagnose colorectal cancer (CRC) accurately and specifically. However, the biomarkers identified differ between studies suggesting that more studies need to be performed to understand the influence of genetic and environmental factors. Therefore, this study aimed to identify biomarkers and affected metabolic pathways in Malaysian CRC patients. Methods: Serum from 50 healthy controls and 50 CRC patients were collected at UKM Medical Centre. The samples were deproteinized with acetonitrile and untargeted metabolomics profile determined using liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-QTOFMS, Agilent USA). The data were analysed using Mass Profiler Professional (Agilent, USA) software. The panel of biomarkers determined were then used to identify CRC from a new set of 20 matched samples. Results: Eleven differential metabolites were identified whose levels were significantly different between CRC patients compared to normal controls. Based on the analysis of the area under the curve, 7 of these metabolites showed high sensitivity and specificity as biomarkers. The use of the 11 metabolites on a new set of samples was able to differentiate CRC from normal samples with 80% accuracy. These metabolites were hypoxanthine, acetylcarnitine, xanthine, uric acid, tyrosine, methionine, lysoPC, lysoPE, citric acid, 5-oxoproline, and pipercolic acid. The data also showed that the most perturbed pathways in CRC were purine, catecholamine, and amino acid metabolisms. Conclusion: Serum metabolomics profiling can be used to identify distinguishing biomarkers for CRC as well as to further our knowledge of its pathophysiological mechanisms.