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This work reports the design and synthesis of novel oxadiazole-decorated azobenzenes, structural analysis of the resulting compounds and behavior under light irradiation. The synthetic strategy involved constructing amino functionalized heterocyclic key intermediates which were used either to yield electrophilic diazonium salts able to react with phenol moieties or as nucleophilic partners in Bayer-Mills reaction with nitroso-substituted derivatives. The amino-derived oxadiazole intermediates were investigated by absorption and emission spectroscopy providing blue and green emitted light. The target oxadiazole-decorated azobenzenes were structurally characterized, including solid-state structures, and subsequently used in irradiation experiments in order to take advantage of the azo group known to provide photoswitching abilities. We noticed quenching of the emissive properties in presence of the azo group; however, all compounds were very stable to repeated cycles of light irradiation. In addition, according to structural diversification we could obtain half-lives of the meta stable isomers within hours to hundreds of hours range. The experimental results were very well correlated with DFT calculations.

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Synthetic chemical probes are powerful tools for investigating biological processes. They are particularly useful for proteomic studies such as activity-based protein profiling (ABPP). These chemical methods initially used mimics of natural substrates. As the techniques gained prominence, more and more elaborate chemical probes with increased specificity towards given enzyme/protein families and amenability to various reaction conditions were used. Among the chemical probes, peptidyl-epoxysuccinates represent one of the first types of compounds used to investigate the activity of the cysteine protease papain-like family of enzymes. Structurally derived from the natural substrate, a wide body of inhibitors and activity- or affinity-based probes bearing the electrophilic oxirane unit for covalent labeling of active enzymes now exists. Herein, we review the literature regarding the synthetic approaches to epoxysuccinate-based chemical probes together with their reported applications, from biological chemistry and inhibition studies to supramolecular chemistry and the formation of protein arrays.

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Arylazopyrazoles stand out among the azoheteroarene photoswitches due to their excellent properties in terms of stability of the least stable isomer and conversion between isomers, leading to their use in several interesting applications. We report herein the synthesis of arylazo-trifluoromethyl-substituted pyrazoles and their switching behavior under light irradiation. UV-vis and NMR experiments showed that arylazo-1H-3,5-bis(trifluoromethyl)pyrazoles displayed very long half-lives in DMSO (days), along with reasonable values of other parameters that characterize a photoswitch. Inclusion of naphthyl moieties as aryl counterparts of the arylazopyrazoles is beneficial only in combination with trifluoromethyl groups, while extending the conjugation by grafting the pyrazole moiety with electron-donating or -withdrawing substituents positively affects the photoswitching behavior, in terms of isomerization yield and half-lives of the least stable isomer. The experimental values were correlated with theoretical calculations indicating the valuable influence of the trifluoromethyl groups onto the photoswitching behavior.

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Starting from dansyl-chloride, in reaction with 1,1-diphenylhydrazine and methoxyamine, two new fluorescent derivatives 1 and 2 were obtained and characterized by NMR, IR, UV-Vis, HR-MS, and fluorescence spectroscopy. The single-crystal X-ray structure was obtained for compound 2. Both compounds generate free radicals by oxidation, as demonstrated by ESR spectroscopy. Compound 1 generates the corresponding hydrazyl-persistent free radical, evidenced directly by ESR spectroscopy, while compound 2 generates in the first instance the methoxyaminyl short-lived free radical, which decomposes rapidly with the formation of the methoxy radical, evidenced by the ESR spin-trapping technique. By oxidation of compounds 1 and 2, their fluorescence is quenched.

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We describe the synthesis of a novel polyamino polycarboxylic ligand, its ability to coordinate metal-ions and attachment to a solid support designed for protein purification through Immobilised Metal-ion Affinity Chromatography (IMAC). The resin was found to be highly efficient for purification of His-tagged HCV E2 glycoproteins expressed in 293T mammalian cells.

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In this study we describe the synthesis and characterisation of a new hydrazone-based fluorescent compound that is able to selectively label the endoplasmic reticulum (ER) in yeast and mammalian living cells. The fluorescence properties of the compound depended on the DMSO/water ratio and on the pH. NMR experiments allowed determination of the conformation adopted in various environments. Apart from the convenient synthetic procedure, our compound displays low cell toxicity and blue emission compatible with filters routinely used in fluorescence microscopy.

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Starting from Kryptofix 22 two different branches were covalently attached through the nitrogen atoms, one containing a fluorescent moiety and the other the stable free radical TEMPO. The novel derivative exhibits fluorescence and paramagnetic properties, while the diaza-crown part ensures the affinity for alkaline metal-ions.

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A variety of biological networks can be modeled as logical or Boolean networks. However, a simplification of the reality to binary states of the nodes does not ease the difficulty of analyzing the dynamics of large, complex networks, such as signal transduction networks, due to the exponential dependence of the state space on the number of nodes. This paper considers a recently introduced method for finding a fairly small subnetwork, representing a collection of nodes that determine the states of most other nodes with a reasonable level of entropy. The subnetwork contains the most determinative nodes that yield the highest information gain. One of the goals of this paper is to propose an algorithm for finding a suitable subnetwork size. The information gain is quantified by the so-called determinative power of the nodes, which is obtained via the mutual information, a concept originating in information theory. We find the most determinative nodes for 36 network models available in the online database Cell Collective (http://cellcollective.org). We provide statistical information that indicates a weak correlation between the subnetwork size and other variables, such as network size, or maximum and average determinative power of nodes. We observe that the proportion represented by the subnetwork in comparison to the whole network shows a weak tendency to decrease for larger networks. The determinative power of nodes is weakly correlated to the number of outputs of a node, and it appears to be independent of other topological measures such as closeness or betweenness centrality. Once the subnetwork of the most determinative nodes is identified, we generate a biological function analysis of its nodes for some of the 36 networks. The analysis shows that a large fraction of the most determinative nodes are essential and involved in crucial biological functions. The biological pathway analysis of the most determinative nodes shows that they are involved in important disease pathways.

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Long-lived states of nuclear spin order were used for the first time to probe interactions between molecules and diamagnetic metal ions. Proton spin states with lifetimes twice as long as the spin-lattice relaxation time constants of the same nuclei were promoted on the methoxyphenyl and tolyl substituents of a 1,3,4-oxadiazole derivative. The transient interaction of this oxadiazole derivative with silver(I) ions significantly speeds up the relaxation rate constants of proton long-lived states. The interactions between silver and organic compounds lead to the formation of coordination polymers that can be used for the preparation of bio-compatible materials.

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Boolean networks have been widely used as models for gene regulatory networks, signal transduction networks, or neural networks, among many others. One of the main difficulties in analyzing the dynamics of a Boolean network and its sensitivity to perturbations or mutations is the fact that it grows exponentially with the number of nodes. Therefore, various approaches for simplifying the computations and reducing the network to a subset of relevant nodes have been proposed in the past few years. We consider a recently introduced method for reducing a Boolean network to its most determinative nodes that yield the highest information gain. The determinative power of a node is obtained by a summation of all mutual information quantities over all nodes having the chosen node as a common input, thus representing a measure of information gain obtained by the knowledge of the node under consideration. The determinative power of nodes has been considered in the literature under the assumption that the inputs are independent in which case one can use the Bahadur orthonormal basis. In this article, we relax that assumption and use a standard orthonormal basis instead. We use techniques of Hilbert space operators and harmonic analysis to generate formulas for the sensitivity to perturbations of nodes, quantified by the notions of influence, average sensitivity, and strength. Since we work on finite-dimensional spaces, our formulas and estimates can be and are formulated in plain matrix algebra terminology. We analyze the determinative power of nodes for a Boolean model of a signal transduction network of a generic fibroblast cell. We also show the similarities and differences induced by the alternative complete orthonormal basis used. Among the similarities, we mention the fact that the knowledge of the states of the most determinative nodes reduces the entropy or uncertainty of the overall network significantly. In a special case, we obtain a stronger result than in previous works, showing that a large information gain from a set of input nodes generates increased sensitivity to perturbations of those inputs.

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This paper studies the spread of perturbations through networks composed of Boolean functions with special canalyzing properties. Canalyzing functions have the property that at least for one value of one of the inputs the output is fixed, irrespective of the values of the other inputs. In this paper the focus is on partially nested canalyzing functions, in which multiple, but not all inputs have this property in a cascading fashion. They naturally describe many relationships in real networks. For example, in a gene regulatory network, the statement "if gene A is expressed, then gene B is not expressed regardless of the states of other genes" implies that A is canalyzing. On the other hand, the additional statement "if gene A is not expressed, and gene C is expressed, then gene B is automatically expressed; otherwise gene B's state is determined by some other type of rule" implies that gene B is expressed by a partially nested canalyzing function with more than two variables, but with two canalyzing variables. In this paper a difference equation model of the probability that a network node's value is affected by an initial perturbation over time is developed, analyzed, and validated numerically. It is shown that the effect of a perturbation decreases towards zero over time if the Boolean functions are canalyzing in sufficiently many variables. The maximum dynamical impact of a perturbation is shown to be comparable to the average impact for a wide range of values of the average sensitivity of the network. Percolation limits are also explored; these are parameter values which generate a transition of the expected perturbation effect to zero as other parameters are varied, so that the initial perturbation does not scale up with the parameters once the percolation limits are reached.

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BACKGROUND: An algebraic method for information fusion based on nonadditive set functions is used to assess the joint contribution of Boolean network attributes to the sensitivity of the network to individual node mutations. The node attributes or characteristics under consideration are: in-degree, out-degree, minimum and average path lengths, bias, average sensitivity of Boolean functions, and canalizing degrees. The impact of node mutations is assessed using as target measure the average Hamming distance between a non-mutated/wild-type network and a mutated network. RESULTS: We find that for a biochemical signal transduction network consisting of several main signaling pathways whose nodes represent signaling molecules (mainly proteins), the algebraic method provides a robust classification of attribute contributions. This method indicates that for the biochemical network, the most significant impact is generated mainly by the combined effects of two attributes: out-degree, and average sensitivity of nodes. CONCLUSIONS: The results support the idea that both topological and dynamical properties of the nodes need to be under consideration. The algebraic method is robust against the choice of initial conditions and partition of data sets in training and testing sets for estimation of the nonadditive set functions of the information fusion procedure.

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Up till 20 years ago, in order to endow molecules with function there were two mainstream lines of thought. One was to rationally design the positioning of chemical functionalities within candidate molecules, followed by an iterative synthesis-optimization process. The second was the use of a "brutal force" approach of combinatorial chemistry coupled with advanced screening for function. Although both methods provided important results, "rational design" often resulted in time-consuming efforts of modeling and synthesis only to find that the candidate molecule was not performing the designed job. "Combinatorial chemistry" suffered from a fundamental limitation related to the focusing of the libraries employed, often using lead compounds that limit its scope. Dynamic constitutional chemistry has developed as a combination of the two approaches above. Through the rational use of reversible chemical bonds together with a large plethora of precursor libraries, one is now able to build functional structures, ranging from quite simple molecules up to large polymeric structures. Thus, by introduction of the dynamic component within the molecular recognition processes, a new perspective of deciphering the world of the molecular events has aroused together with a new field of chemistry. Since its birth dynamic constitutional chemistry has continuously gained attention, in particular due to its ability to easily create from scratch outstanding molecular structures as well as the addition of adaptive features. The fundamental concepts defining the dynamic constitutional chemistry have been continuously extended to currently place it at the intersection between the supramolecular chemistry and newly defined adaptive chemistry, a pivotal feature towards evolutive chemistry.

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Development of lanthanide-based luminescent "switch-on" systems via azide-alkyne [3+2] cycloaddition is described. We used these for non-specific protein labeling and as tags for specific and selective activity-based protein labeling.

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Reaction between ortho-phthalaldehyde and various aroylhydrazines unexpectedly yields N-(1-(2-aryl-hydrazono)isoindolin-2-yl)benzamides as major products along with the predictable 1,2-bis-aroylhydrazones. NMR investigation of the major reaction products indicate the presence of a mixture of geometrical isomers, in various ratios. Single crystal X-ray diffraction confirms the proposed structure and indicates a Z configuration of the C═N double bond substitutents. Optimization of the condensation reaction conditions enabled quantitative isolation of the cyclic isomer. Oxidation of the isomers with bis(trifluoroacetoxy)iodobenzene (PIFA) leads to rapid formation of new highly fluorescent 1,2-bis(5-aryl-1,3,4-oxadiazol-2-yl)benzenes.

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We present here a new, general, solid phase strategy for the synthesis of sequence independent peptidyl-fluoromethyl ketones using standard Fmoc peptide chemistry. Our method is based on the synthesis of bifunctional linkers which allows the incorporation of amino acid fluoromethyl ketone unit at the C-terminal end of peptide sequences. Application of this approach for the synthesis of activity based probes for SENPs is also described.

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In this paper we provide a mean-field Boolean network model for a signal transduction network of a generic fibroblast cell. The network consists of several main signaling pathways, including the receptor tyrosine kinase, the G-protein coupled receptor, and the Integrin signaling pathway. The network consists of 130 nodes, each representing a signaling molecule (mainly proteins). Nodes are governed by Boolean dynamics including canalizing functions as well as totalistic Boolean functions that depend only on the overall fraction of active nodes. We categorize the Boolean functions into several different classes. Using a mean-field approach we generate a mathematical formula for the probability of a node becoming active at any time step. The model is shown to be a good match for the actual network. This is done by iterating both the actual network and the model and comparing the results numerically. Using the Boolean model it is shown that the system is stable under a variety of parameter combinations. It is also shown that this model is suitable for assessing the dynamics of the network under protein mutations. Analytical results support the numerical observations that in the long-run at most half of the nodes of the network are active.

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We report here the synthesis and biochemical properties of a new peptidyl activity-based probe 1 for SUMO proteases, SENPs. The activity-based probe has at its C terminus a glycine-derived fluoromethylketone moiety as a reactive group designed to target the active-site cysteine of SENPs. Based on a study of the interactions between SENPs and SUMOs, we introduced further design elements that allow the activity-based probe to selectively target SENPs at low micromolar to high nanomolar concentrations. Moreover, 1 out-competes SUMO1 from the reversible SUMO1-SENP1 complex, thus suggesting that 1 and SUMO1 share a common binding site on SENP1.

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Self-assembled inorganic-protein arrays with well-defined and controllable size and structure were obtained through the Fe(II) complexation of protein-conjugated terpyridine units (ligand). The atom-level control of the ligand is obtained through residue-specific conjugation between the complexing unit (terpy) containing an activity-based probe and a corresponding active enzyme (papain). The Fe(II)-based self-assembly performed on this unique building block (ligand) leads to chemical species of unprecedented constitution. The first example presented herein opens the way to a shape and size regime usually reserved to polymers.

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Herein we describe the design and synthesis of the first series of di-functional ligands for the directed construction of inorganic-protein frameworks. The synthesized ligands are composed of a metal-ion binding moiety (terpyridine-based) conjugated to an epoxysuccinyl peptide, known to covalently bind active cysteine proteases through the active-site cysteine. We explore and optimize two different conjugation chemistries between the di-functionalized metal-ion ligand and the epoxysuccinyl-containing peptide moiety: peptide-bond formation (with limited success) and Cu(I)-catalysed click chemistry (with good results). Further, the complexation of the synthesized ligands with Fe(II) and Ni(II) ions is investigated: the di-functional ligands are confirmed to behave similarly to the parent terpyridine. As designed, the peptidic moiety does not interfere with the complexation reaction, in spite of the presence of two triazole rings that result from the click reaction. ES-MS together with NMR and UV/Vis studies establish the structure, the stoichiometry of the complexation reactions, as well as the conditions under which chemically sensitive peptide-containing polypyridine ligands can undergo the self-assembly process. These results establish the versatility of our approach and open the way to the synthesis of di-functional ligands containing more elaborated polypyridine ligands as well as affinity labels for different enzyme families. As such, this paper is the first step towards the construction of robust supramolecular species that cover a size-regime and organization level previously unexplored.

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