Abstract: Based on in vitro assays, we performed a High Throughput Screening (HTS) to identify kinase inhibitors among 10,000 small chemical compounds. In this didactic paper, we describe step-by-step the approach to validate the hits as well as the major pitfalls encountered in the development of active molecules. We propose a decision tree that could be adapted to most in vitro HTS.
Abstract: McArdle disease (glycogen storage disease Type V; MD) is a metabolic myopathy caused by a deficiency in muscle glycogen phosphorylase. Since muscle glycogen is an important fuel for muscle during exercise, this inborn error of metabolism provides a model for understanding the role of glycogen in muscle function and the compensatory adaptations that occur in response to impaired glycogenolysis. Patients with MD have exercise intolerance with symptoms including premature fatigue, myalgia, and/or muscle cramps. Despite this, MD patients are able to perform prolonged exercise as a result of the “second wind” phenomenon, owing to the improved delivery of extra-muscular fuels during exercise. The present review will cover what this disease can teach us about exercise physiology, and particularly focuses on the compensatory pathways for energy delivery to muscle in the absence of glycogenolysis.
Abstract: A nano-flow high-resolution screening platform, featuring a parallel chip-based microfluidic bioassay and mass spectrometry coupled to nano-liquid chromatography, was applied to screen animal venoms for nicotinic acetylcholine receptor like (nAChR) affinity by using the acetylcholine binding protein, a mimic of the nAChR. The potential of this microfluidic platform is demonstrated by profiling the Conus textile venom proteome, consisting of over 1,000 peptides. Within one analysis (<90 min, 500 ng venom injected), ligands are detected and identified. To show applicability for non-peptides, small molecular ligands such as steroidal ligands were identified in skin secretions from two toad species (Bufo alvarius and Bufo marinus). Bioactives from the toad samples were subsequently isolated by MS-guided fractionation. The fractions analyzed by NMR and a radioligand binding assay with α7-nAChR confirmed the identity and bioactivity of several new ligands.
Abstract: Hsp90 has become the target of intensive investigation, as inhibition of its function has the ability to simultaneously incapacitate proteins that function in pathways that represent the six hallmarks of cancer. While a number of Hsp90 inhibitors have made it into clinical trials, a number of short-comings have been noted, such that the search continues for novel Hsp90 inhibitors with superior pharmacological properties. To identify new potential Hsp90 inhibitors, we have utilized a high-throughput assay based on measuring Hsp90-dependent refolding of thermally denatured luciferase to screen natural compound libraries. Over 4,000 compounds were screen with over 100 hits. Data mining of the literature indicated that 51 compounds had physiological effects that Hsp90 inhibitors also exhibit, and/or the ability to downregulate the expression levels of Hsp90-dependent proteins. Of these 51 compounds, seven were previously characterized as Hsp90 inhibitors. Four compounds, anthothecol, garcinol, piplartine, and rottlerin, were further characterized, and the ability of these compounds to inhibit the refolding of luciferase, and reduce the rate of growth of MCF7 breast cancer cells, correlated with their ability to suppress the Hsp90-dependent maturation of the heme-regulated eIF2α kinase, and deplete cultured cells of Hsp90-dependent client proteins. Thus, this screen has identified an additional 44 compounds with known beneficial pharmacological properties, but with unknown mechanisms of action as possible new inhibitors of the Hsp90 chaperone machine.
Abstract: Putting new findings into the context of available literature knowledge is one approach to deal with the surge of high-throughput data results. Furthermore, prior knowledge can increase the performance and stability of bioinformatic algorithms, for example, methods for network reconstruction. In this review, we examine software packages for the statistical computing framework R, which enable the integration of pathway data for further bioinformatic analyses. Different approaches to integrate and visualize pathway data are identified and packages are stratified concerning their features according to a number of different aspects: data import strategies, the extent of available data, dependencies on external tools, integration with further analysis steps and visualization options are considered. A total of 12 packages integrating pathway data are reviewed in this manuscript. These are supplemented by five R-specific packages for visualization and six connector packages, which provide access to external tools.