Intracellular Loop in the Brain Isoforms of Anoctamin 2 Channels Regulates Calcium-dependent Activation

Anoctamin 2 (ANO2 or TMEM16B), a calcium-activated chloride channel (CaCC), performs diverse roles in neurons throughout the central nervous system. In hippocampal neurons, ANO2 narrows action potential width and reduces postsynaptic depolarization with high sensitivity to Ca2+ at relatively fast kinetics. In other brain regions, including the thalamus, ANO2 mediates activity-dependent spike frequency adaptations with low sensitivity to Ca2+ at relatively slow kinetics. How this same channel can respond to a wide range of Ca2+ levels remains unclear. We hypothesized that splice variants of ANO2 may contribute to its distinct Ca2+ sensitivity, and thus its diverse neuronal functions. We identified two ANO2 isoforms expressed in mouse brains and examined their electrophysiological properties: isoform 1 (encoded by splice variants with exons 1a, 2, 4, and 14) was expressed in the hippocampus, while isoform 2 (encoded by splice variants with exons 1a, 2, and 4) was broadly expressed throughout the brain, including in the cortex and thalamus, and had a slower calcium-dependent activation current than isoform 1. Computational modeling revealed that the secondary structure of the first intracellular loop of isoform 1 forms an entrance cavity to the calcium-binding site from the cytosol that is relatively larger than that in isoform 2. This difference provides structural evidence that isoform 2 is involved in accommodating spike frequency, while isoform 1 is involved in shaping the duration of an action potential and decreasing postsynaptic depolarization. Our study highlights the roles and molecular mechanisms of specific ANO2 splice variants in modulating neuronal functions.

BMD42-2910, a Novel Benzoxazole Derivative, Shows a Potent Anti-prion Activity and Prolongs the Mean Survival in an Animal Model of Prion Disease

Prion diseases are a group of neurodegenerative and fatal central nervous system disorders. The pathogenic mechanism involves the conversion of cellular prion protein (PrPC) to an altered scrapie isoform (PrPSc), which accumulates in amyloid deposits in the brain. However, no therapeutic drugs have demonstrated efficacy in clinical trials. We previously reported that BMD42-29, a synthetic compound discovered in silico , is a novel anti-prion compound that inhibits the conversion of PrPC to protease K (PK)-resistant PrPSc fragments (PrPres). In the present study, 14 derivatives of BMD42-29 were obtained from BMD42-29 by modifying in the side chain by in silico feedback, with the aim to determine whether they improve anti-prion activity. These derivatives were assessed in a PrPSc-infected cell model and some derivatives were further tested using real timequaking induced conversion (RT-QuIC). Among them, BMD42-2910 showed high anti-prion activity at low concentrations in vitro and also no toxic effects in a mouse model. Interestingly, abundant PrPres was reduced in brains of mice infected with prion strain when treated with BMD42- 2910, and the mice survived longer than control mice and even that treated with BMD42-29. Finally, high binding affinity was predicted in the virtual binding sites (Asn159, Gln 160, Lys194, and Glu196) when PrPC was combined with BMD-42-2910. Our findings showed that BMD42-2910 sufficiently reduces PrPres generation in vitro and in vivo and may be a promising novel anti-prion compound.

Assessment of quantitative structure-activity relationship of toxicity prediction models for Korean chemical substance control legislation

OBJECTIVES: For successful adoption of legislation controlling registration and assessment of chemical substances, it is important to obtain sufficient toxicological experimental evidence and other related information. It is also essential to obtain a sufficient number of predicted risk and toxicity results. Particularly, methods used in predicting toxicities of chemical substances during acquisition of required data, ultimately become an economic method for future dealings with new substances. Although the need for such methods is gradually increasing, the-required information about reliability and applicability range has not been systematically provided. METHODS: There are various representative environmental and human toxicity models based on quantitative structure-activity relationships (QSAR). Here, we secured the 10 representative QSAR-based prediction models and its information that can make predictions about substances that are expected to be regulated. We used models that predict and confirm usability of the information expected to be collected and submitted according to the legislation. After collecting and evaluating each predictive model and relevant data, we prepared methods quantifying the scientific validity and reliability, which are essential conditions for using predictive models. RESULTS: We calculated predicted values for the models. Furthermore, we deduced and compared adequacies of the models using the Alternative non-testing method assessed for Registration, Evaluation, Authorization, and Restriction of Chemicals Substances scoring system, and deduced the applicability domains for each model. Additionally, we calculated and compared inclusion rates of substances expected to be regulated, to confirm the applicability. CONCLUSIONS: We evaluated and compared the data, adequacy, and applicability of our selected QSAR-based toxicity prediction models, and included them in a database. Based on this data, we aimed to construct a system that can be used with predicted toxicity results. Furthermore, by presenting the suitability of individual predicted results, we aimed to provide a foundation that could be used in actual assessments and regulations.