Protein–Protein Interaction Network and Subcellular Localization of the Arabidopsis Thaliana ESCRT Machinery

The endosomal sorting complex required for transport (ESCRT) consists of several multi-protein subcomplexes which assemble sequentially at the endosomal surface and function in multivesicular body (MVB) biogenesis. While ESCRT has been relatively well characterized in yeasts and mammals, comparably little is known about ESCRT in plants. Here we explored the yeast two-hybrid protein interaction network and subcellular localization of the Arabidopsis thaliana ESCRT machinery. We show that the Arabidopsis ESCRT interactome possesses a number of protein–protein interactions that are either conserved in yeasts and mammals or distinct to plants. We show also that most of the Arabidopsis ESCRT proteins examined at least partially localize to MVBs in plant cells when ectopically expressed on their own or co-expressed with other interacting ESCRT proteins, and some also induce abnormal MVB phenotypes, consistent with their proposed functional role(s) as part of the ESCRT machinery in Arabidopsis. Overall, our results help define the plant ESCRT machinery by highlighting both conserved and unique features when compared to ESCRT in other evolutionarily diverse organisms, providing a foundation for further exploration of ESCRT in plants

A global view of drug-therapy interactions

Network science is already making an impact on the study of complex systems and offers a promising variety of tools to understand their formation and evolution (1-4) in many disparate fields from large communication networks (5,6), transportation infrastructures (7) and social communities (8,9) to biological systems (1,10,11). Even though new highthroughput technologies have rapidly been generating large amounts of genomic data, drug design has not followed the same development, and it is still complicated and expensive to develop new single-target drugs. Nevertheless, recent approaches suggest that multi-target drug design combined with a network-dependent approach and large-scale systems-oriented strategies (12-14) create a promising framework to combat complex multigenetic disorders like cancer or diabetes. Here, we investigate the human network corresponding to the interactions between all US approved drugs and human therapies, defined by known drug-therapy relationships. Our results show that the key paths in this network are shorter than three steps, indicating that distant therapies are separated by a surprisingly low number of chemical compounds. We also identify a sub-network composed by drugs with high centrality measures (15), which represent the structural back-bone of the drug-therapy system and act as hubs routing information between distant parts of the network. These findings provide for the first time a global map of the largescale organization of all known drugs and associated therapies, bringing new insights on possible strategies for future drug development. Special attention should be given to drugs which combine the two properties of (a) having a high centrality value and (b) acting on multiple targets.Comment: 16 pages, 4 figures. It was submitted to peer review on August 15, 200

Sensory ways to indigenous multimodal literacies : Hands and feet tell the story

This chapter reports original research that asks the question: What are the ways of knowing, being, and communicating that are valued and practiced in Indigenous communities? Literacy curricula, internationally and nationally, typically do not take into account the multi-sensorial dimensions of non-Western forms of representation that go beyond narrow conceptions of print. For example, literacies are often conceived as drawing on print, visual, spatial, gestural, and audio modes, but the role of haptics and locomotion has typically received little attention. This chapter highlights examples of the multi-sensoriality of Indigenous literacies observed in participatory community research with an Indigenous school. It extends recent theories of sensory studies in the history and cultural anthropology of the senses, applying these principles to literacy education. Sensory literacies is a theoretical perspective that gives priority to the sensorial dimensions of the body and its role in communication in literacy practice, because without a sensing body, we cannot know about or communicate with the world. The data demonstrates how the forgotten role of the hands and feet in dominant theories of communication is central to Indigenous identity and literacies. Written by a white academic with an Indigenous researcher, the chapter problematises the privileging of narrow, logocentric, and Western forms of literacy and its implications for rethinking the role of the whole body in literacy and the literacy curriculum for Indigenous students

Using Multiple Microenvironments to Find Similar Ligand-Binding Sites: Application to Kinase Inhibitor Binding

The recognition of cryptic small-molecular binding sites in protein structures is important for understanding off-target side effects and for recognizing potential new indications for existing drugs. Current methods focus on the geometry and detailed chemical interactions within putative binding pockets, but may not recognize distant similarities where dynamics or modified interactions allow one ligand to bind apparently divergent binding pockets. In this paper, we introduce an algorithm that seeks similar microenvironments within two binding sites, and assesses overall binding site similarity by the presence of multiple shared microenvironments. The method has relatively weak geometric requirements (to allow for conformational change or dynamics in both the ligand and the pocket) and uses multiple biophysical and biochemical measures to characterize the microenvironments (to allow for diverse modes of ligand binding). We term the algorithm PocketFEATURE, since it focuses on pockets using the FEATURE system for characterizing microenvironments. We validate PocketFEATURE first by showing that it can better discriminate sites that bind similar ligands from those that do not, and by showing that we can recognize FAD-binding sites on a proteome scale with Area Under the Curve (AUC) of 92%. We then apply PocketFEATURE to evolutionarily distant kinases, for which the method recognizes several proven distant relationships, and predicts unexpected shared ligand binding. Using experimental data from ChEMBL and Ambit, we show that at high significance level, 40 kinase pairs are predicted to share ligands. Some of these pairs offer new opportunities for inhibiting two proteins in a single pathway

Epigenetic polypharmacology: from combination therapy to multitargeted drugs

The modern drug discovery process has largely focused its attention in the so-called magic bullets, single chemical entities that exhibit high selectivity and potency for a particular target. This approach was based on the assumption that the deregulation of a protein was causally linked to a disease state, and the pharmacological intervention through inhibition of the deregulated target was able to restore normal cell function. However, the use of cocktails or multicomponent drugs to address several targets simultaneously is also popular to treat multifactorial diseases such as cancer and neurological disorders. We review the state of the art with such combinations that have an epigenetic target as one of their mechanisms of action. Epigenetic drug discovery is a rapidly advancing field, and drugs targeting epigenetic enzymes are in the clinic for the treatment of hematological cancers. Approved and experimental epigenetic drugs are undergoing clinical trials in combination with other therapeutic agents via fused or linked pharmacophores in order to benefit from synergistic effects of polypharmacology. In addition, ligands are being discovered which, as single chemical entities, are able to modulate multiple epigenetic targets simultaneously (multitarget epigenetic drugs). These multiple ligands should in principle have a lower risk of drug-drug interactions and drug resistance compared to cocktails or multicomponent drugs. This new generation may rival the so-called magic bullets in the treatment of diseases that arise as a consequence of the deregulation of multiple signaling pathways provided the challenge of optimization of the activities shown by the pharmacophores with the different targets is addressed

On the Matter of Time

Drawing on several disciplinary areas, this article considers diverse cultural concepts of time, space, and materiality. It explores historical shifts in ideas about time, observing that these have gone full circle, from visions in which time and space were conflated, through increasingly divergent linear understandings of the relationship between them, to their reunion in contemporary notions of space-time. Making use of long-term ethnographic research and explorations of the topic of Time at Durham University’s Institute of Advanced Study (2012–13), the article considers Aboriginal Australian ideas about relationality and the movement of matter through space and time. It asks why these earliest explanations of the cosmos, though couched in a wholly different idiom, seem to have more in common with the theories proposed by contemporary physicists than with the ideas that dominated the period between the Holocene and the Anthropocene. The analysis suggests that such unexpected resonance between these oldest and newest ideas about time and space may spring from the fact that they share an intense observational focus on material events. Comparing these vastly different but intriguingly compatible worldviews meets interdisciplinary aims in providing a fresh perspective on both of them

A theoretical entropy score as a single value to express inhibitor selectivity

<p>Abstract</p> <p>Background</p> <p>Designing maximally selective ligands that act on individual targets is the dominant paradigm in drug discovery. Poor selectivity can underlie toxicity and side effects in the clinic, and for this reason compound selectivity is increasingly monitored from very early on in the drug discovery process. To make sense of large amounts of profiling data, and to determine when a compound is sufficiently selective, there is a need for a proper quantitative measure of selectivity.</p> <p>Results</p> <p>Here we propose a new theoretical entropy score that can be calculated from a set of IC₅₀data. In contrast to previous measures such as the 'selectivity score', Gini score, or partition index, the entropy score is non-arbitary, fully exploits IC₅₀data, and is not dependent on a reference enzyme. In addition, the entropy score gives the most robust values with data from different sources, because it is less sensitive to errors. We apply the new score to kinase and nuclear receptor profiling data, and to high-throughput screening data. In addition, through analyzing profiles of clinical compounds, we show quantitatively that a more selective kinase inhibitor is not necessarily more drug-like.</p> <p>Conclusions</p> <p>For quantifying selectivity from panel profiling, a theoretical entropy score is the best method. It is valuable for studying the molecular mechanisms of selectivity, and to steer compound progression in drug discovery programs.</p