Molecular BioSystems

doi: 10.1039/c3mb90026fpmid: N/A

doi: 10.1039/c3mb90027dpmid: N/A

doi: 10.1039/c3mb90029kpmid: N/A

Avadisian, Miriam; Gunning, Patrick T.

doi: 10.1039/c3mb70147fpmid: 23771042

The conjugation of drug or molecular recognition motif to a hydrophobic fatty entity, for purpose of drug–membrane localization, has been a molecular strategy utilized for targeted inhibition of pathways involved in diseased cells. In general, membrane-anchored inhibitor structures have been composed of either a lipid or sterol group coupled via a broad range of inert linkers to either a peptide or small molecule protein recognition agent. Whilst not adhering to the molecular paradigms of modern medicinal chemistry, this approach has afforded peptidic-based therapeutics with improved cellular and in vivo efficacy, leading to more selective targeting of membrane associated protein targets and the effective immobilization of cytosolic signaling proteins through membrane anchorage. The evidence suggests that membrane-anchored peptidic inhibitors are more selective, potent, structurally rigid, and possess enhanced cell permeability profiles as compared to their non-lipidated precursors. This perspectives article will review the application of lipid or sterol conjugation to peptide inhibitors (lipo-molecules) to circumvent the poor cell permeability and metabolic labilities associated with peptidic therapeutics. In addition, the concept of protein–membrane anchorage as a novel drug modality for inhibiting cytosolic signaling protein motility in cells will be reviewed and its merits as an approach to inhibiting protein complexation, protein nuclear translocation and their potential for more effective targeting of membrane associated targets.

Sandefur, Conner I.; Mincheva, Maya; Schnell, Santiago

doi: 10.1039/c3mb70052fpmid: 23857078

Systems biologists increasingly use network representations to investigate biochemical pathways and their dynamic behaviours. In this critical review, we discuss four commonly used network representations of chemical and biochemical pathways. We illustrate how some of these representations reduce network complexity but result in the ambiguous representation of biochemical pathways. We also examine the current theoretical approaches available to investigate the dynamic behaviour of chemical and biochemical networks. Finally, we describe how the critical chemical and biochemical pathways responsible for emergent dynamic behaviour can be identified using network mining and functional mapping approaches.

Kristensen, Anders R.; Foster, Leonard J.

doi: 10.1039/c3mb70135bpmid: 23861068

Most proteins do not exist as isolated molecules in the cell, but instead serve as nodes of protein interaction networks. A number of techniques have been developed in the last two decades to study protein interaction networks at different levels of detail. Here we describe some of the techniques for characterizing protein interactions and protein complexes on a system-wide scale, focusing especially on newly emerging techniques that use co-migration. These newer approaches have the advantage that no genetic manipulation is necessary, thereby allowing investigation of protein complexes at their endogenous levels in the correct cellular context. Finally, we discuss different approaches for measuring large-scale temporal changes to protein interaction networks, an area that we believe will be one of the frontiers in systems biology in the coming years.

Chen, Zhen; Wang, Yanying; Zhai, Ya-Feng; Song, Jiangning; Zhang, Ziding

doi: 10.1039/c3mb70100jpmid: 23861030

As one of the most important trace elements within an organism, zinc has been shown to be involved in numerous biological processes and closely implicated in various diseases. The zinc ion is important for proteins to perform their functional roles. To provide in-depth functional annotation of zinc-binding proteins, an initial but crucial step is the accurate recognition of zinc-binding sites. Motivated by the biological importance of zinc, we propose a new method called ZincExplorer to predict zinc-binding sites from protein sequences. ZincExplorer is a hybrid method that can accurately predict zinc-binding sites from protein sequences. It integrates the outputs of three different types of predictors, namely, SVM-, cluster- and template-based predictors. Four types of zinc-binding amino acids CHEDs (i.e. CYS, HIS, ASP and GLU) could be predicted using ZincExplorer. It achieved a high AURPC (Area Under Recall–Precision Curve) of 0.851, and a precision of 85.6% (specificity = 98.4%, MCC = 0.747) at the 70.0% recall for the CHEDs on the 5-fold cross-validation test. When tested on an independent dataset containing 2023 zinc-binding CHEDs and 14 493 non-zinc-binding CHEDs, it achieved about 3–8% higher AURPC in comparison to two other sequence-based predictors. Moreover, ZincExplorer could also identify the interdependent relationships (IRs) of the predicted zinc-binding sites bound to the same zinc ion, which makes it a useful tool for providing in-depth zinc-binding site annotation.

Sacconnay, Lionel; Smirlis, Despina; Queiroz, Emerson Ferreira; Wolfender, Jean L.; Soares, Milena Botelho Perreira; Carrupt, Pierre-Alain; Nurisso, Alessandra

doi: 10.1039/c3mb70180hpmid: 23799611

Trypanosoma cruzi and Leishmania spp. are protozoan pathogens responsible for Chagas disease and leishmaniasis, respectively. Current therapies rely only on a very small number of drugs, most of them are inadequate because of their severe host toxicity or drug-resistance phenomena. In order to find therapeutic alternatives, the identification of new biotargets is highly desired. In this study, homology modelling, docking and molecular dynamics simulations have been used to generate robust 3D models of NAD+-dependent deacetylases from Trypanosoma and Leishmania spp., known as SIR2rp3, whose structures have never been described before. Molecular docking of known inhibitors revealed strong analogies with the mitochondrial human SIRT5 in terms of binding mode and interaction strength. On the other hand, by extending the analysis to the channel rims, regions of difference between host and parasitic targets, useful for future selective drug design projects, were pointed out.

Bremang, Michael; Cuomo, Alessandro; Agresta, Anna Maria; Stugiewicz, Magdalena; Spadotto, Valeria; Bonaldi, Tiziana

doi: 10.1039/c3mb00009epmid: 23748837

Protein methylation is a post-translational modification (PTM) by which a variable number of methyl groups are transferred to lysine and arginine residues within proteins. Despite increased interest in this modification due to its reversible nature and its emerging role in a diverse set of biological pathways beyond chromatin, global identification of protein methylation has remained an unachieved goal. To characterise sites of lysine and arginine methylation beyond histones, we employed an approach that combines heavy methyl stable isotope labelling by amino acids in cell culture (hmSILAC) with high-resolution mass spectrometry-based proteomics. Through a broad evaluation of immuno-affinity enrichment and the application of two classical protein separation techniques prior to mass spectrometry, to nucleosolic and cytosolic fractions separately, we identified a total of 501 different methylation types, on 397 distinct lysine and arginine sites, present on 139 unique proteins. Our results considerably extend the number of known in vivo methylation sites and indicate their significant presence on several protein complexes involved at all stages of gene expression, from chromatin remodelling and transcription to splicing and translation. In addition, we describe the potential of the hmSILAC approach for accurate relative quantification of methylation levels between distinct functional states.

Mbodj, Abibatou; Junion, Guillaume; Brun, Christine; Furlong, Eileen E. M.; Thieffry, Denis

doi: 10.1039/c3mb70187epmid: 23868318

A limited number of signalling pathways are involved in the specification of cell fate during the development of all animals. Several of these pathways were originally identified in Drosophila. To clarify their roles, and possible cross-talk, we have built a logical model for the nine key signalling pathways recurrently used in metazoan development. In each case, we considered the associated ligands, receptors, signal transducers, modulators, and transcription factors reported in the literature. Implemented using the logical modelling software GINsim, the resulting models qualitatively recapitulate the main characteristics of each pathway, in wild type as well as in various mutant situations (e.g. loss-of-function or gain-of-function). These models constitute pluggable modules that can be used to assemble comprehensive models of complex developmental processes. Moreover, these models of Drosophila pathways could serve as scaffolds for more complicated models of orthologous mammalian pathways. Comprehensive model annotations and GINsim files are provided for each of the nine considered pathways.