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

Computational analysis of the evolutionarily conserved Missing In Metastasis/Metastasis Suppressor 1 gene predicts novel interactions, regulatory regions and transcriptional control

Missing in Metastasis (MIM), or Metastasis Suppressor 1 (MTSS1), is a highly conserved protein, which links the plasma membrane to the actin cytoskeleton. MIM has been implicated in various cancers, however, its modes of action remain largely enigmatic. Here, we performed an extensive in silico characterisation of MIM to gain better understanding of its function. We detected previously unappreciated functional motifs including adaptor protein (AP) complex interaction site and a C-helix, pointing to a role in endocytosis and regulation of actin dynamics, respectively. We also identified new functional regions, characterised with phosphorylation sites or distinct hydrophilic properties. Strong negative selection during evolution, yielding high conservation of MIM, has been combined with positive selection at key sites. Interestingly, our analysis of intra-molecular co-evolution revealed potential regulatory hotspots that coincided with reduced potentially\ua0pathogenic polymorphisms. We explored databases for the mutations and expression levels of MIM in cancer. Experimentally, we focused on chronic lymphocytic leukaemia (CLL), where MIM showed high overall expression, however, downregulation on poor prognosis samples. Finally, we propose strong conservation of MTSS1 also on the transcriptional level and predict novel transcriptional regulators. Our data highlight important targets for future studies on the role of MIM in different tissues and cancers

Linguistic support for revising and editing

Revising and editing are important parts of the writing process. In fact, multiple revision and editing cycles are crucial for the production of high-quality texts. However, revising and editing are also tedious and error-prone, since changes may introduce new errors. Grammar checkers, as offered by some word processors, are not a solution. Besides the fact that they are only available for few languages, and regardless of the questionable quality, their conceptual approach is not suitable for experienced writers, who actively create their texts. Word processors offer few, if any, functions for handling text on the same cognitive level as the author: While the author is thinking in high-level linguistic terms, editors and word processors mostly provide low-level character oriented functions. Mapping the intended outcome to these low-level operations is distracting for the author, who now has to focus for a long time on small parts of the text. This results in a loss of global overview of the text and in typical revision errors (duplicate verbs, extraneous conjunctions, etc.) We therefore propose functions for text processors that work on the conceptual level of writers. These functions operate on linguistic elements, not on lines and characters. We describe how these functions can be implemented by making use of NLP methods and linguistic resources

Recognition of sorting signals by clathrin adaptors

Sorting of membrane proteins is generally mediated by cytosolic coats, which create a scaffold to form coated buds and vesicles and to selectively concentrate cargo by interacting with cytosolic signals. The classical paradigm is the interaction between clathrin coats and associated adaptor proteins, which cluster receptors with characteristic tyrosine and dileucine motifs during endocytosis. Clathrin in association with different sets of adaptors is found in addition at the trans-Golgi network and endosomes. Sequences similar to internalization signals also direct lysosomal and basolateral sorting, which implicates related clathrinadaptor coats in the respective sorting pathways. This review concentrates on the recognition of sorting signals by clathrin-associated adaptor proteins, an area of significant recent progress due to new methodological and conceptual approaches

Functional human iPSC-derived alveolar-like cells cultured in a miniaturized 96‑Transwell air-liquid interface model

In order to circumvent the limited access and donor variability of human primary alveolar cells, directed differentiation of human pluripotent stem cells (hiPSCs) into alveolar-like cells, provides a promising tool for respiratory disease modeling and drug discovery assays. In this work, a unique, miniaturized 96-Transwell microplate system is described where hiPSC-derived alveolar-like cells were cultured at an air-liquid interface (ALI). To this end, hiPSCs were differentiated into lung epithelial progenitor cells (LPCs) and subsequently matured into a functional alveolar type 2 (AT2)-like epithelium with monolayer-like morphology. AT2-like cells cultured at the physiological ALI conditions displayed characteristics of AT2 cells with classical alveolar surfactant protein expressions and lamellar-body like structures. The integrity of the epithelial barriers between the AT2-like cells was confirmed by applying a custom-made device for 96-parallelized transepithelial electric resistance (TEER) measurements. In order to generate an IPF disease-like phenotype in vitro, the functional AT2-like cells were stimulated with cytokines and growth factors present in the alveolar tissue of IPF patients. The cytokines stimulated the secretion of pro-fibrotic biomarker proteins both on the mRNA (messenger ribonucleic acid) and protein level. Thus, the hiPSC-derived and cellular model system enables the recapitulation of certain IPF hallmarks, while paving the route towards a miniaturized medium throughput approach of pharmaceutical drug discovery.publishe