Design,synthesis and evaluation of novel dehydroabietic acid-dithiocarbamate hybrids as potential multi-targeted compounds for tumor cytotoxicity

In the present study, novel representatives of the important group of biologically-active, dehydroabietic acid-bearing dithiocarbamate moiety, were synthesized and characterized by ¹H NMR, ¹³C NMR, HR-MS. The in vitro antiproliferative activity evaluation (MTT) indicated that these compounds exhibited potent inhibitory activities in various cancer cell lines (HepG-2, MCF-7, HeLa, T-24, MGC-803). Particularly, compound III-b possessed extraordinary cytotoxicity with low micromolar IC₅₀ values ranging from 4.07 to 38.84 µM against tested cancer cell lines, while displayed weak cytotoxicity on two normal cell lines (LO-2 and HEK 293 T). Subsequently, the potential mechanisms of representative compound III-b were elementarily investigated by Transwell experiment, which showed III-b can inhibit cancer cells migration. Annexin-V/PI dual staining showed that the compound can induce HepG-2 cells apoptosis in a dose-dependent manner. Meanwhile this apoptosis may be related to the upregulated protein expression of cleaved-caspase 3, cleaved-caspase 9, Bax and downregulated of Bcl-2 indicated by Western Blot. Later study further confirmed that ROS levels in HepG-2 cells increased significantly with the rise of concentrations. In addition, through the network pharmacology data analyzing, the core targets and signaling pathways of compound III-b for treatment of liver neoplasms were forecasted. Molecular docking model showed that compound III-b had high affinity with hub targets (CASP3, EGFR, HSP90AA1, MAPK1, ERBB2, MDM2), suggesting that compound III-b might target the hub protein to modulate signaling activity. Taken together, these data indicated that dehydroabietic acid structural modification following the “Molecular hybridization” principle is a feasible way to discover the potential multi-targeted antitumor compounds.     

Ultrasound-assisted immersion freezing reduces the structure and gel property deterioration of myofibrillar protein from chicken breast

The effects of air freezing (AF), immersion freezing (IF) and ultrasound-assisted immersion freezing (UF) at different power levels (125, 165, 205 and 245 W) on the structure and gel properties of the myofibrillar protein (MP) of chicken breast were investigated. UF at 165 W (UF-165) had no obvious negative impact on the primary structure of the MP and effectively reduced the change in the secondary and tertiary structure. In addition, UF-165 significantly reduced the losses in the elastic modulus (G′), gel strength, and gel water holding capacity (P < 0.05). According to low field nuclear magnetic resonance analysis, the T₂₁ and T₂₂ of the UF-165 MP gels were shorter than those of the AF and IF samples, which meant that the UF-165 reduced the mobility of the immobilized water and free water in MP gel. A scanning electron microscopy analysis showed that the appropriate ultrasonic power promoted the formation of a compact and homogeneous protein gel network. These results suggested that the appropriate ultrasonic power maintained the MP structure and reduced the loss of gel quality.     

A benchmark of optimally folded protein structures using integer programming and the 3D-HP-SC model

The Protein Structure Prediction (PSP) problem comprises, among other issues, forecasting the three-dimensional native structure of proteins using only their primary structure information. Most computational studies in this area use synthetic data instead of real biological data. However, the closer to the real-world, the more the impact of results and their applicability. This work presents 17 real protein sequences extracted from the Protein Data Bank for a benchmark to the PSP problem using the tri-dimensional Hydrophobic-Polar with Side-Chains model (3D-HP-SC). The native structure of these proteins was found by maximizing the number of hydrophobic contacts between the side-chains of amino acids. The problem was treated as an optimization problem and solved by means of an Integer Programming approach. Although the method optimally solves the problem, the processing time has an exponential trend. Therefore, due to computational limitations, the method is a proof-of-concept and it is not applicable to large sequences. For unknown sequences, an upper bound of the number of hydrophobic contacts (using this model) can be found, due to a linear relationship with the number of hydrophobic residues. The comparison between the predicted and the biological structures showed that the highest similarity between them was found with distance thresholds around 5.2–8.2 Å. Both the dataset and the programs developed will be freely available to foster further research in the area.     

Sensitive targeted multiple protein quantification based on elemental detection of Quantum Dots

A generic strategy based on the use of CdSe/ZnS Quantum Dots (QDs) as elemental labels for protein quantification, using immunoassays with elemental mass spectrometry (ICP-MS), detection is presented. In this strategy, streptavidin modified QDs (QDs-SA) are bioconjugated to a biotinylated secondary antibody (b-Ab₂). After a multi-technique characterization of the synthesized generic platform (QDs-SA-b-Ab₂) it was applied to the sequential quantification of five proteins (transferrin, complement C3, apolipoprotein A1, transthyretin and apolipoprotein A4) at different concentration levels in human serum samples. It is shown how this generic strategy does only require the appropriate unlabeled primary antibody for each protein to be detected. Therefore, it introduces a way out to the need for the cumbersome and specific bioconjugation of the QDs to the corresponding specific recognition antibody for every target analyte (protein). Results obtained were validated with those obtained using UV–vis spectrophotometry and commercial ELISA Kits.     

Conformational Studies of Oligosaccharides

The conformation of a molecule strongly affects its function, as demonstrated for peptides and nucleic acids. This correlation is much less established for carbohydrates, the most abundant organic materials in nature. Recent advances in synthetic and analytical techniques have enabled the study of carbohydrates at the molecular level. Recurrent structural features were identified as responsible for particular biological activities or material properties. In this Minireview, recent achievements in the structural characterization of carbohydrates, enabled by systematic studies of chemically defined oligosaccharides, are discussed. These findings can guide the development of more potent glycomimetics. Synthetic carbohydrate materials by design can be envisioned.     

Tridentate Schiff base and 4,4′-bipyridine coordinated di/polynuclear Cu (II) complexes: Synthesis,crystal structure,DNA/protein binding and catecholase activity

4,4′-bipyridine bridged two Cu (II) complexes, [Cu₂L¹₂(4,4′-bipy)(H₂O)₂](ClO₄)₂ ( 1 ) and [Cu₂L²₂(4,4′-bipy)]_n·(2H₂O)_n ( 2 ) (where, HL¹ = 2-[(3-methylamino-propylimino)-methyl]-phenol, H₂L² = 3-[(2-hydroxy-3-methoxy-benzylidene)-amino]-propionic acid, and 4,4′-bipy = 4,4′-bipyridine) have been synthesized and characterized by single crystal structure determination, mass spectrometry, FT-IR, electronic absorption, and emission spectroscopy. Complex 1 is dinuclear cationic compound and counter balanced by perchlorate anion, whereas complex 2 possesses 1D poly-nuclear structure. Both the complexes crystallize in monoclinic system with P2₁/c space group and the copper centers possess square pyramidal geometry. H-bonding, C-H···π, π···π interactions results the formation of two dimentional supramolecular structure for both the complexes. Interactions of complexes with bovine serum albumins (BSA) and human serum albumins (HSA) have been studied by using electronic absorption and emission spectroscopic technique. The calculated values of binding constants (K_b) are (9.22 ± 0.26) × 10⁵ L mol⁻¹ ( 1 -BSA), (7.19 ± 0.16) × 10⁵ L mol⁻¹ ( 1 -HSA), (5.05 ± 0.20) × 10⁵ L mol⁻¹ ( 2 -BSA) and (3.56 ± 0.25) × 10⁵ L mol⁻¹ ( 2 -HSA). The mechanism of serum albumins-complex interactions have been investigated by fluorescence lifetime measurement. Fluorescence spectroscopic studies indicate that both the complexes interact with calf thymas-DNA. Catecholase activity of the complexes has been studied in methanol using 3,5-di-tert-butylcatechol (3,5-DTBC) as substrate and the result show that both the complexes are active for catalytic oxidation of 3,5-DTBC to 3,5-di-tert-butylquinone (3,5-DTBQ) in presence of molecular oxygen. Calculated values of turnover numbers are 71.81 ± 1.04 h⁻¹ and 69.45 ± 0.74 h⁻¹ for 1 and 2 , respectively.     

The Polymer Physics of Multiscale Charge Transport in Conjugated Systems

Conjugated polymers are promising candidates for next‐generation low‐cost flexible electronics. Field‐effect transistors comprising conjugated polymers have witnessed significant improvements in device performance, notably the field‐effect mobility, in the last three decades. However, to truly make these materials commercially competitive, a better understanding of charge‐transport mechanisms in these structurally heterogeneous systems is needed for providing systematic guides for further improvements. This review assesses the key microstructural features of conjugated polymers across multiple length scales that can influence charge transport, with special attention given to the underlying polymer physics. The mechanistic understanding from collective experimental and theoretical studies point to the importance of interconnected ordered domains given the macromolecular nature of the polymeric semiconductors. Based on the criterion, optimization to improve charge transport can be broadly characterized by efforts to (a) promote intrachain transport, (b) establish intercrystallite connectivity, and (c) enhance interchain coupling. © 2019 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2019 , 57, 1559–1571     

Integrating Rigidity Analysis into the Exploration of Protein Conformational Pathways Using RRT* and MC

To understand how proteins function on a cellular level, it is of paramount importance to understand their structures and dynamics, including the conformational changes they undergo to carry out their function. For the aforementioned reasons, the study of large conformational changes in proteins has been an interest to researchers for years. However, since some proteins experience rapid and transient conformational changes, it is hard to experimentally capture the intermediate structures. Additionally, computational brute force methods are computationally intractable, which makes it impossible to find these pathways which require a search in a high-dimensional, complex space. In our previous work, we implemented a hybrid algorithm that combines Monte-Carlo (MC) sampling and RRT*, a version of the Rapidly Exploring Random Trees (RRT) robotics-based method, to make the conformational exploration more accurate and efficient, and produce smooth conformational pathways. In this work, we integrated the rigidity analysis of proteins into our algorithm to guide the search to explore flexible regions. We demonstrate that rigidity analysis dramatically reduces the run time and accelerates convergence.     

Impact of ultrasound processing on alternative protein systems: Protein extraction,nutritional effects and associated challenges

Proteins from alternative sources including terrestrial and aquatic plants, microbes and insects are being increasingly explored to combat the dietary, environmental and ethical challenges linked primarily to conventional sources of protein, mainly meat and dairy proteins. Ultrasound (US) technologies have emerged as a clean, green and efficient methods for the extraction of proteins from alternative sources compared to conventional methods. However, the application of US can also lead to modifications of the proteins extracted from alternative sources, including changes in their nutritional quality (protein content, amino acid composition, protein digestibility, anti-nutritional factors) and allergenicity, as well as damage of the compounds associated with an increased degradation resulting from extreme US processing conditions. This work aims to summarise the main advances in US equipment currently available to date, including the main US parameters and their effects on the extraction of protein from alternative sources, as well as the studies available on the effects of US processing on the nutritional value, allergenicity and degradation damage of these alternative protein ingredients. The main research gaps identified in this work and future challenges associated to the widespread application of US and their scale-up to industry operations are also covered in detail.     

Exploring the relationship between hub proteins and drug targets based on GO and intrinsic disorder

Protein–protein interactions (PPIs) play essential roles in many biological processes. In protein–protein interaction networks, hubs involve in numbers of PPIs and may constitute an important source of drug targets. The intrinsic disorder proteins (IDPs) with unstable structures can promote the promiscuity of hubs and also involve in many disease pathways, so they also could serve as potential drug targets. Moreover, proteins with similar functions measured by semantic similarity of gene ontology (GO) terms tend to interact with each other. Here, the relationship between hub proteins and drug targets based on GO terms and intrinsic disorder was explored. The semantic similarities of GO terms and genes between two proteins, and the rate of intrinsic disorder residues of each protein were extracted as features to characterize the functional similarity between two interacting proteins. Only using 8 feature variables, prediction models by support vector machine (SVM) were constructed to predict PPIs. The accuracy of the model on the PPI data from human hub proteins is as high as 83.72%, which is very promising compared with other PPI prediction models with hundreds or even thousands of features. Then, 118 of 142 PPIs between hubs are correctly predicted that the two interacting proteins are targets of the same drugs. The results indicate that only 8 functional features are fully efficient for representing PPIs. In order to identify new targets from IDP dataset, the PPIs between hubs and IDPs are predicted by the SVM model and the model yields a prediction accuracy of 75.84%. Further research proves that 3 of 5 PPIs between hubs and IDPs are correctly predicted that the two interacting proteins are targets of the same drugs. All results demonstrate that the model with only 8-dimensional features from GO terms and intrinsic disorder still gives a good performance in predicting PPIs and further identifying drug targets.