A Comprehensive Spectroscopic and Computational Investigation to Probe the Interaction of Antineoplastic Drug Nordihydroguaiaretic Acid with Serum Albumins

Exogenous drugs that are used as antidote against chemotheray, inflammation or viral infection, gets absorbed and interacts reversibly to the major serum transport protein i.e. albumins, upon entering the circulatory system. To have a structural guideline in the rational drug designing and in the synthesis of drugs with greater efficacy, the binding mechanism of an antineoplastic and anti-inflammatory drug Nordihydroguaiaretic acid (NDGA) with human and bovine serum albumins (HSA & BSA) were examined by spectroscopic and computational methods. NDGA binds to site II of HSA with binding constant (K_b) ~10⁵ M^-1 and free energy (ΔG) ~ -7.5 kcal.mol^-1. It also binds at site II of BSA but with lesser binding affinity (K_b) ~10⁵ M^-1 and ΔG ~ -6.5 kcal.mol^-1. The negative value of ΔG, ΔH and ΔS for both the albumins at three different temperatures confirmed that the complex formation process between albumins and NDGA is spontaneous and exothermic. Furthermore, hydrogen bonds and hydrophobic interactions are the main forces involved in complex formation of NDGA with both the albumins as evaluated from fluorescence and molecular docking results. Binding of NDGA to both the albumins alter the conformation and causes minor change in the secondary structure of proteins as indicated by the CD spectra.     

The Chemical Fractionation of Rabbit and Swine Thymus

A chemical fractionation procedure, previously found applicable to bovine thymus and bovine and ovine palatine tonsils, was used to fractionate rabbit and hog thymus. With respect to the chemical fractionation steps, yields of fractions, and optical and electrophoretic properties, extracts from hog and rabbit thymus were indistinguishable from similar extracts prepared from calf thymus. The study provides composition and yield data applicable to the thymus of a small mammal readily available in most laboratories.     

Surfactant-mediated amyloidogenesis behavior of stem bromelain; a biophysical insight

Neurodegenerative disorders are mainly associated with amyloid fibril formation of different proteins. Stem bromelain (SB), a cysteine protease, is known to exist as a molten globule state at pH 10.0. It passes through the identical surrounding (pH 10.0) in the gut epithelium of intestine upon oral administration. Protein–surfactant complexes are widely employed as drug carriers, so the nature of surfactant toward protein is of great interest. The present work describes the effect of cationic surfactants (CTAB & DTAB) and their hydrophobic behavior toward amyloidogenesis behavior of SB at pH 10.0. Multiple approaches including light scattering, far UV-CD, turbidity measurements, and dye binding assay (ThT, Congo red and ANS) were performed to measure the aggregation propensity of SB. Further, we monitored the hydrodynamic radii of aggregates formed using dynamic light scattering technique. Structure of fibrils was also visualized through fluorescence microscopy as well as TEM. At pH 10.0, low concentration of CTAB (0–200 μM) induced amyloid formation in SB as evident from a prominent increase in turbidity and light scattering, gain in β-sheet content, and enhanced ThT fluorescence intensity. However, further increase in CTAB concentration suppressed the fibrillation phenomenon. In contrast, DTAB did not induce fibril formation at any concentration used (0–500 μM) due to lower hydrophobicity. Net negative charge developed on protein at high pH (10.0) might have facilitated amyloid formation at low concentration of cationic surfactant (CTAB) due to electrostatic and hydrophobic interactions.     

The biology and chemistry of antifungal agents: A review

In recent years their has been an increased use of antifungal agents and has resulted in the development of resistance to drugs. Currently, use of standard antifungal therapies can be limited because of toxicity, low efficacy rates. Different types of mechanisms contribute to the development of resistance to antifungals. This has given raise to search for a new heterocycle with distinct action or multitargeted combination therapy. This review addresses the areas such as the underlying mechanisms, eight different targets such as ergosterol synthesis, chitin synthesis, ergosterol disruptors, glucan synthesis, squalene epoxidase, nucleic acid synthesis, protein synthesis, microtubules synthesis. The clinically employed drugs along with the current research work going on worldwide on different heterocycles are discussed. In recent advances various heterocycles including imidazole, benzimidazole etc., twenty three scaffolds and their lead identification are discussed.     

Regulation of tight junction assembly and epithelial morphogenesis by the heat shock protein Apg-2

Background  

Tight junctions are required for epithelial barrier formation and participate in the regulation of signalling mechanisms that control proliferation and differentiation. ZO-1 is a tight junction-associated adaptor protein that regulates gene expression, junction assembly and epithelial morphogenesis. We have previously demonstrated that the heat shock protein Apg-2 binds ZO-1 and thereby regulates its role in cell proliferation. Here, we addressed the question whether Apg-2 is also important for junction formation and epithelial morphogenesis.     

Abundance-based Classifier for the Prediction of Mass Spectrometric Peptide Detectability Upon Enrichment (PPA)

The function of a large percentage of proteins is modulated by post-translational modifications (PTMs). Currently, mass spectrometry (MS) is the only proteome-wide technology that can identify PTMs. Unfortunately, the inability to detect a PTM by MS is not proof that the modification is not present. The detectability of peptides varies significantly making MS potentially blind to a large fraction of peptides. Learning from published algorithms that generally focus on predicting the most detectable peptides we developed a tool that incorporates protein abundance into the peptide prediction algorithm with the aim to determine the detectability of every peptide within a protein. We tested our tool, “Peptide Prediction with Abundance” (PPA), on in-house acquired as well as published data sets from other groups acquired on different instrument platforms. Incorporation of protein abundance into the prediction allows us to assess not only the detectability of all peptides but also whether a peptide of interest is likely to become detectable upon enrichment. We validated the ability of our tool to predict changes in protein detectability with a dilution series of 31 purified proteins at several different concentrations. PPA predicted the concentration dependent peptide detectability in 78% of the cases correctly, demonstrating its utility for predicting the protein enrichment needed to observe a peptide of interest in targeted experiments. This is especially important in the analysis of PTMs. PPA is available as a web-based or executable package that can work with generally applicable defaults or retrained from a pilot MS data set.Post-translational modification (PTM)¹ of proteins is a key regulatory mechanism in the vast majority of biological processes. Historically, to follow PTMs, site-specific antibodies had to be generated in a time-consuming and laborious process associated with high failure rates. Mass spectrometry (MS) holds enormous promise in PTM analysis as it is currently the only technique that has the ability to both discover, localize, and quantify proteome-wide modifications (1). Recent advances in instrumentation and method optimization makes it possible to detect the complete yeast proteome within one hour (2), an ever increasing proportion of the human proteome (3–6), and more than 10,000 phosphorylation sites in a single MS experiment (7, 8). As a result one of the major publicly available databases (www.phosphosite.org (9)) has curated >200,000 phosphorylation sites.Although the number of proteins and PTMs that can be identified is impressive, many modifications have still not been identified in any MS-based experiment. The identification and quantification of biologically relevant modifications is challenging for three reasons: (1) many proteins of interest are of very low abundance rendering them difficult to detect and quantify; (2) many modifications sites are present at substoichiometric quantities, further reducing their detectability; and (3) as large scale proteomics is based on the detection of peptides after a proteolytic digest, and the detectability of a peptide is determined by its physiochemical properties (10), many peptides from highly abundant proteins are never detected. This is particularly important, as there is a shift in the use of MS-based proteomics from large scale, unbiased, discovery-focused experiments toward directed experiments for accurate and precise quantification of biologically relevant PTMs. Protein and peptide enrichment strategies and/or targeted MS experiments like single reaction monitoring (SRM) (11) have increased the number of detectable peptides; however, both of these methods are laborious, and often not successful, that is, the peptide carrying the modification of interest is still not observed as it is fundamentally very difficult to detect.Protein enrichment is the method choice for most experimentalists, but there is no current way to determine whether this is likely to succeed prior to engaging in lengthy biochemical and/or analytical experiments. In an effort to gauge the chances of success for detecting a particular peptide we sought to develop an algorithm that can predict both the chances of detecting a particular peptide and, more importantly, what enrichment it would take to detect a particular peptide that is not easily detected. Here we present such a tool that predicts the detectability and estimates an enrichment factor, i.e. an increase in signal over the background that is necessary to actually detect a particular peptide. Our algorithm development was motivated by two premises: (1) In silico methods have been developed that focus on the prediction of easily detectable “proteotypic” peptides (peptides that are likely to provide the best detection sensitivity) with good accuracy (12–15). (2) Comprehensive proteome studies have shown that the number of detected peptides per protein, and thus the sequence coverage, varies with protein abundance (which is the basis for spectral counting-based protein quantification (16, 17)). We find that incorporation of protein abundance in a peptide classification tool improves the accuracy of the prediction of peptide detectability allowing us to predict the detectability of all peptides within a protein as well as the amount of enrichment needed to detect a peptide of interest.We used a set of 120 purified in vitro expressed proteins as a training set to develop a prediction tool. We deliver this in the form of a web-based interface that provides information about: (1) the probability of detecting the different tryptic peptides of a protein, and (2) the fold enrichment that would be required to bring a peptide of interest into the detectable range. This tool will help guide researchers in their efforts to monitor particular peptides and their modified cognates by MS, specifically, in prioritizing their efforts toward enriching proteins where they would be likely to be able to detect a peptide or modification of interest.     

1,3,4-Oxadiazole-2(3H)-thione and its analogues: A new class of non-competitive nucleotide pyrophosphatases/phosphodiesterases 1 inhibitors

A series of 1,3,4-oxadiazole-2 (3H)-thiones and 1,3,4-thiadiazole-2 (3H)-thiones were synthesized and evaluated for their inhibitory activities against the two nucleotide pyrophosphatase phosphodiesterase 1 enzymes. Dixon, as well as Lineweaver–Burk plots, and their secondary replots have indicated that the inhibition was of pure non-competitive type, against both snake venom and pure human recombinant enzymes as the V_max values decreases without affecting the K_m values. 5-[4-(t-Butyldimethylsilyloxy)-phenyl]-1,3,4-thiadiazole-2 (3H)-thione (17) and [4-(t-butyldimethylsilyloxy)-phenyl]-1,3,4-oxadiazole-2 (3H)-thione (1) were found to be the most active compounds with IC₅₀ values 66.47 and 368 μM, respectively. The K_i values were 100 μM and 360 μM against the snake venom and human recombinant NPP1 enzyme, respectively. Most active compounds were found to be non-toxic in neutrophil viability assay.