Discovery of Potent, Selective, and Brain-Penetrant Apoptosis Signal-Regulating Kinase 1 (ASK1) Inhibitors that Modulate Brain Inflammation In Vivo.

Apoptosis signal-regulating kinase 1 (ASK1) is one of the key mediators of the cellular stress response that regulates inflammation and apoptosis. To probe the therapeutic value of modulating this pathway in preclinical models of neurological disease, we further optimized the profile of our previously reported inhibitor 3. This effort led to the discovery of 32, a potent (cell IC50 = 25 nM) and selective ASK1 inhibitor with suitable pharmacokinetic and brain penetration (rat Cl/Clu = 1.6/56 L/h/kg and Kp,uu = 0.46) for proof-of-pharmacology studies. Specifically, the ability of 32 to inhibit ASK1 in the central nervous system (CNS) was evaluated in a human tau transgenic (Tg4510) mouse model exhibiting elevated brain inflammation. In this study, transgenic animals treated with 32 (at 3, 10, and 30 mg/kg, BID/PO for 4 days) showed a robust reduction of inflammatory markers (e.g., IL-1ß) in the cortex, thus confirming inhibition of ASK1 in the CNS.

Acute inhibition of the CNS-specific kinase TTBK1 significantly lowers tau phosphorylation at several disease relevant sites.

Hyperphosphorylated tau protein is a pathological hallmark of numerous neurodegenerative diseases and the level of tau pathology is correlated with the degree of cognitive impairment. Tau hyper-phosphorylation is thought to be an early initiating event in the cascade leading to tau toxicity and neuronal death. Inhibition of tau phosphorylation therefore represents an attractive therapeutic strategy. However, the widespread expression of most kinases and promiscuity of their substrates, along with poor selectivity of most kinase inhibitors, have resulted in systemic toxicities that have limited the advancement of tau kinase inhibitors into the clinic. We therefore focused on the CNS-specific tau kinase, TTBK1, and investigated whether selective inhibition of this kinase could represent a viable approach to targeting tau phosphorylation in disease. In the current study, we demonstrate that TTBK1 regulates tau phosphorylation using overexpression or knockdown of this kinase in heterologous cells and primary neurons. Importantly, we find that TTBK1-specific phosphorylation of tau leads to a loss of normal protein function including a decrease in tau-tubulin binding and deficits in tubulin polymerization. We then describe the use of a novel, selective small molecule antagonist, BIIB-TTBK1i, to study the acute effects of TTBK1 inhibition on tau phosphorylation in vivo. We demonstrate substantial lowering of tau phosphorylation at multiple sites implicated in disease, suggesting that TTBK1 inhibitors may represent an exciting new approach in the search for neurodegenerative disease therapies.

Small-molecule bioanalytical sample preparation method development starting from the BASICS.

AIM: To develop a robust small-molecule bioanalytical sample preparation method, systematic investigations of the bioanalytical handling conditions of analytes and IS of interest are preferred. So far, such investigations are done manually and are labor-intensive and error-prone. RESULT: An automation-assisted system has been developed to facilitate such systematic investigations. The system takes experimental design and automates the majority of the wet laboratory work. In addition, the system also automates the data extraction, recovery/loss computation, graphing and reporting. CONCLUSION: The automation-assisted system greatly reduces errors and labor involved in the systematic investigation of analytes and IS both for wet chemistry experiments and for data extraction and processing, enhances data processing efficiency and overall sample preparation method development productivity.

Online and automated sample extraction.

Online and automated sample extraction is widely used to increase the throughput and improve the quality of LC-MS/MS analysis. In this article, we review the most commonly used online sample extraction methodologies including online SPE, turbulent flow chromatography, online DBS extraction and online immunoaffinity extraction. We also review the offline automated sample extraction platforms, including custom robot scripts for the automation of individual steps during sample extraction, the robot scripts for the automation of individual assays, and the platform for integrated multiple sample extraction. The most recent developments and future trends in this area are also discussed.

ICECAP: an integrated, general-purpose, automation-assisted IC50/EC50 assay platform.

BACKGROUND: IC50 and EC50 values are commonly used to evaluate drug potency. Mass spectrometry (MS)-centric bioanalytical and biomarker labs are now conducting IC50/EC50 assays, which, if done manually, are tedious and error-prone. Existing bioanalytical sample preparation automation systems cannot meet IC50/EC50 assay throughput demand. RESULT: A general-purpose, automation-assisted IC50/EC50 assay platform was developed to automate the calculations of spiking solutions and the matrix solutions preparation scheme, the actual spiking and matrix solutions preparations, as well as the flexible sample extraction procedures after incubation. In addition, the platform also automates the data extraction, nonlinear regression curve fitting, computation of IC50/EC50 values, graphing, and reporting. CONCLUSION: The automation-assisted IC50/EC50 assay platform can process the whole class of assays of varying assay conditions. In each run, the system can handle up to 32 compounds and up to 10 concentration levels per compound, and it greatly improves IC50/EC50 assay experimental productivity and data processing efficiency.

ASPECTS: an automation-assisted SPE method development system.

BACKGROUND: A typical conventional SPE method development (MD) process usually involves deciding the chemistry of the sorbent and eluent based on information about the analyte; experimentally preparing and trying out various combinations of adsorption chemistry and elution conditions; quantitatively evaluating the various conditions; and comparing quantitative results from all combination of conditions to select the best condition for method qualification. The second and fourth steps have mostly been performed manually until now. RESULTS: We developed an automation-assisted system that expedites the conventional SPE MD process by automating 99% of the second step, and expedites the fourth step by automatically processing the results data and presenting it to the analyst in a user-friendly format. CONCLUSION: The automation-assisted SPE MD system greatly saves the manual labor in SPE MD work, prevents analyst errors from causing misinterpretation of quantitative results, and shortens data analysis and interpretation time.