Evaluation of a diospyrin derivative as antileishmanial agent and potential modulator of ornithine decarboxylase of Leishmania donovani

World health organization has called for academic research and development of new chemotherapeutic strategies to overcome the emerging resistance and side effects exhibited by the drugs currently used against leishmaniasis. Diospyrin, a bis-naphthoquinone isolated from Diospyros montana Roxb., and its semi-synthetic derivatives, were reported for inhibitory activity against protozoan parasites including Leishmania. Presently, we have investigated the antileishmanial effect of a di-epoxide derivative of diospyrin (D17), both in vitro and in vivo. Further, the safety profile of D17 was established by testing its toxicity against normal macrophage cells (IC₅₀ ∼ 20.7 μM), and also against normal BALB/c mice in vivo. The compound showed enhanced activity (IC₅₀ ∼ 7.2 μM) as compared to diospyrin (IC₅₀ ∼ 12.6 μM) against Leishmania donovani promastigotes. Again, D17 was tested on L. donovani BHU1216 isolated from a sodium stibogluconate-unresponsive patient, and exhibited selective inhibition of the intracellular amastigotes (IC₅₀ ∼ 0.18 μM). Also, treatment of infected BALB/c mice with D17 at 2 mg/kg/day reduced the hepatic parasite load by about 38%. Subsequently, computational docking studies were undertaken on selected enzymes of trypanothione metabolism, viz. trypanothione reductase (TryR) and ornithine decarboxylase (ODC), followed by the enzyme kinetics, where D17 demonstrated non-competitive inhibition of the L. donovani ODC, but could not inhibit TryR.     

Overexpression of WsSGTL1 Gene of Withania somnifera Enhances Salt Tolerance,Heat Tolerance and Cold Acclimation Ability in Transgenic Arabidopsis Plants

Background

Sterol glycosyltrnasferases (SGT) are enzymes that glycosylate sterols which play important role in plant adaptation to stress and are medicinally important in plants like Withania somnifera. The present study aims to find the role of WsSGTL1 which is a sterol glycosyltransferase from W. somnifera, in plant’s adaptation to abiotic stress.

Methodology

The WsSGTL1 gene was transformed in Arabidopsis thaliana through Agrobacterium mediated transformation, using the binary vector pBI121, by floral dip method. The phenotypic and physiological parameters like germination, root length, shoot weight, relative electrolyte conductivity, MDA content, SOD levels, relative electrolyte leakage and chlorophyll measurements were compared between transgenic and wild type Arabidopsis plants under different abiotic stresses - salt, heat and cold. Biochemical analysis was done by HPLC-TLC and radiolabelled enzyme assay. The promoter of the WsSGTL1 gene was cloned by using Genome Walker kit (Clontech, USA) and the 3D structures were predicted by using Discovery Studio Ver. 2.5.

Results

The WsSGTL1 transgenic plants were confirmed to be single copy by Southern and homozygous by segregation analysis. As compared to WT, the transgenic plants showed better germination, salt tolerance, heat and cold tolerance. The level of the transgene WsSGTL1 was elevated in heat, cold and salt stress along with other marker genes such as HSP70, HSP90, RD29, SOS3 and LEA4-5. Biochemical analysis showed the formation of sterol glycosides and increase in enzyme activity. When the promoter of WsSGTL1 gene was cloned from W. somnifera and sequenced, it contained stress responsive elements. Bioinformatics analysis of the 3D structure of the WsSGTL1 protein showed functional similarity with sterol glycosyltransferase AtSGT of A. thaliana.

Conclusions

Transformation of WsSGTL1 gene in A. thaliana conferred abiotic stress tolerance. The promoter of the gene in W.somnifera was found to have stress responsive elements. The 3D structure showed functional similarity with sterol glycosyltransferases.     

A high‐throughput capillary isoelectric focusing immunoassay for fingerprinting protein sialylation

The serum half‐life, biological activity, and solubility of many recombinant glycoproteins depend on their sialylation. Monitoring glycoprotein sialylation during cell culture manufacturing is, therefore, critical to ensure product efficacy and safety. Here a high‐throughput method for semi‐quantitative fingerprinting of glycoprotein sialylation using capillary isoelectric focusing immunoassay on NanoPro (Protein Simple) platform was developed. The method was specific, sensitive, precise, and robust. It could analyze 2 μL of crude cell culture samples without protein purification, and could automatically analyze from 8 samples in 4 h to 96 samples in 14 h without analyst supervision. Furthermore, its capability to detect various changes in sialylation fingerprints during cell culture manufacturing process was indispensable to ensure process robustness and consistency. Moreover, the changes in the sialylation fingerprints analyzed by this method showed strong correlations with intact mass analysis using liquid chromatography and mass spectrometry. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 32:235–241, 2016     

Invariant TAD Boundaries Constrain Cell-Type-Specific Looping Interactions between Promoters and Distal Elements around the CFTR Locus

Three-dimensional genome structure plays an important role in gene regulation. Globally, chromosomes are organized into active and inactive compartments while, at the gene level, looping interactions connect promoters to regulatory elements. Topologically associating domains (TADs), typically several hundred kilobases in size, form an intermediate level of organization. Major questions include how TADs are formed and how they are related to looping interactions between genes and regulatory elements. Here we performed a focused 5C analysis of a 2.8 Mb chromosome 7 region surrounding CFTR in a panel of cell types. We find that the same TAD boundaries are present in all cell types, indicating that TADs represent a universal chromosome architecture. Furthermore, we find that these TAD boundaries are present irrespective of the expression and looping of genes located between them. In contrast, looping interactions between promoters and regulatory elements are cell-type specific and occur mostly within TADs. This is exemplified by the CFTR promoter that in different cell types interacts with distinct sets of distal cell-type-specific regulatory elements that are all located within the same TAD. Finally, we find that long-range associations between loci located in different TADs are also detected, but these display much lower interaction frequencies than looping interactions within TADs. Interestingly, interactions between TADs are also highly cell-type-specific and often involve loci clustered around TAD boundaries. These data point to key roles of invariant TAD boundaries in constraining as well as mediating cell-type-specific long-range interactions and gene regulation.     

Coupling dynamics and evolutionary information with structure to identify protein regulatory and functional binding sites

Binding sites in proteins can be either specifically functional binding sites (active sites) that bind specific substrates with high affinity or regulatory binding sites (allosteric sites), that modulate the activity of functional binding sites through effector molecules. Owing to their significance in determining protein function, the identification of protein functional and regulatory binding sites is widely acknowledged as an important biological problem. In this work, we present a novel binding site prediction method, Active and Regulatory site Prediction (AR-Pred), which supplements protein geometry, evolutionary, and physicochemical features with information about protein dynamics to predict putative active and allosteric site residues. As the intrinsic dynamics of globular proteins plays an essential role in controlling binding events, we find it to be an important feature for the identification of protein binding sites. We train and validate our predictive models on multiple balanced training and validation sets with random forest machine learning and obtain an ensemble of discrete models for each prediction type. Our models for active site prediction yield a median area under the curve (AUC) of 91% and Matthews correlation coefficient (MCC) of 0.68, whereas the less well-defined allosteric sites are predicted at a lower level with a median AUC of 80% and MCC of 0.48. When tested on an independent set of proteins, our models for active site prediction show comparable performance to two existing methods and gains compared to two others, while the allosteric site models show gains when tested against three existing prediction methods. AR-Pred is available as a free downloadable package at https://github.com/sambitmishra0628/AR-PRED_source .