Physiologically relevant fluorescent assay for identification of 17β-hydroxysteroid dehydrogenase type 10 inhibitors

Mitochondrial enzyme 17β-hydroxysteroid dehydrogenase type 10 (HSD10) is a potential molecular target for treatment of mitochondrial-related disorders such as Alzheimer's disease (AD). Its over-expression in AD brains is one of the critical factors disturbing the homeostasis of neuroprotective steroids and exacerbating amyloid beta (Aβ)-mediated mitochondrial toxicity and neuronal stress. This study was focused on revalidation of the most potent HSD10 inhibitors derived from benzothiazolyl urea scaffold using fluorescent-based enzymatic assay with physiologically relevant substrates of 17β-oestradiol and allopregnanolone. The oestradiol-based assay led to the identification of two nanomolar inhibitors (IC50 70 and 346 nM) differing from HSD10 hits revealed from the formerly used assay. Both identified inhibitors were found to be effective also in allopregnanolone-based assay with non-competitive or uncompetitive mode of action. In addition, both inhibitors were confirmed to penetrate the HEK293 cells and they were able to inhibit the HSD10 enzyme in the cellular environment. Both molecules seem to be potential lead structures for further research and development of HDS10 inhibitors.

RNase T1 Refolding Assay for Determining Mitochondrial Cyclophilin D Activity: A Novel In Vitro Method Applicable in Drug Research and Discovery

Human cyclophilin D is a mitochondrial peptidyl-prolyl isomerase that plays a role in regulating the opening of the mitochondrial permeability transition pore. It is considered a viable and promising molecular target for the treatment of diseases for which disease development is associated with pore opening, e.g., Alzheimer's disease or ischemia/reperfusion injury. Currently available and widely used in vitro methods based on Kofron's assay for determining cyclophilin D activity suffer from serious drawbacks and limitations. In this study, a completely novel approach for an in vitro assay of cyclophilin D activity using RNase T1 refolding is introduced. The method is simple and is more in line with the presumed physiological role of cyclophilin D in protein folding than Kofron's assay, which relies on a peptide substrate. The method is applicable for identifying novel inhibitors of cyclophilin D as potential drugs for the treatment of the diseases mentioned above. Moreover, the description of CypD activity in the in vitro RNase T1 refolding assay reveals new possibilities for investigating the role of cyclophilin D in protein folding in cells and may lead to a better understanding of its pathological and physiological roles.

Benzothiazolyl Ureas are Low Micromolar and Uncompetitive Inhibitors of 17β-HSD10 with Implications to Alzheimer's Disease Treatment

Human 17β-hydroxysteroid dehydrogenase type 10 is a multifunctional protein involved in many enzymatic and structural processes within mitochondria. This enzyme was suggested to be involved in several neurological diseases, e.g., mental retardation, Parkinson's disease, or Alzheimer's disease, in which it was shown to interact with the amyloid-beta peptide. We prepared approximately 60 new compounds based on a benzothiazolyl scaffold and evaluated their inhibitory ability and mechanism of action. The most potent inhibitors contained 3-chloro and 4-hydroxy substitution on the phenyl ring moiety, a small substituent at position 6 on the benzothiazole moiety, and the two moieties were connected via a urea linker (4at, 4bb, and 4bg). These compounds exhibited IC₅₀ values of 1-2 μM and showed an uncompetitive mechanism of action with respect to the substrate, acetoacetyl-CoA. These uncompetitive benzothiazolyl inhibitors of 17β-hydroxysteroid dehydrogenase type 10 are promising compounds for potential drugs for neurodegenerative diseases that warrant further research and development.

Flavones Inhibit the Activity of AKR1B10, a Promising Therapeutic Target for Cancer Treatment

AKR1B10 is an NADPH-dependent reductase that plays an important function in several physiological reactions such as the conversion of retinal to retinol, reduction of isoprenyl aldehydes, and biotransformation of procarcinogens and drugs. A growing body of evidence points to the important role of the enzyme in the development of several types of cancer (e.g., breast, hepatocellular), in which it is highly overexpressed. AKR1B10 is regarded as a therapeutic target for the treatment of these diseases, and potent and specific inhibitors may be promising therapeutic agents. Several inhibitors of AKR1B10 have been described, but the area of natural plant products has been investigated sparingly. In the present study almost 40 diverse phenolic compounds and alkaloids were examined for their ability to inhibit the recombinant AKR1B10 enzyme. The most potent inhibitors-apigenin, luteolin, and 7-hydroxyflavone-were further characterized in terms of IC50, selectivity, and mode of action. Molecular docking studies were also conducted, which identified putative binding residues important for the interaction. In addition, cellular studies demonstrated a significant inhibition of the AKR1B10-mediated reduction of daunorubicin in intact cells by these inhibitors without a considerable cytotoxic effect. Although these compounds are moderately potent and selective inhibitors of AKR1B10, they constitute a new structural type of AKR1B10 inhibitor and may serve as a template for the development of better inhibitors.

Estimation of the time-varying cortical connectivity patterns by the adaptive multivariate estimators in high resolution EEG studies

The Directed Transfer Function (DTF) and the Partial Directed Coherence (PDC) are frequency-domain estimators, based on the multivariate autoregressive modelling (MVAR) of time series, that are able to describe interactions between cortical areas in terms of the concept of Granger causality. However, the classical estimation of these methods requires the stationary of the signals. In this way, transient pathways of information transfer remains hidden. The objective of this study is to test a time-varying multivariate method for the estimation of rapidly changing connectivity relationships between cortical areas of the human brain, based on DTF/PDC and on the use of adaptive MVAR modelling (AMVAR). This approach will allow the observation of transient influences between the cortical areas during the execution of a task. Time-varying DTF and PDC were obtained by the adaptive recursive fit of an MVAR model with time-dependent parameters, by means of a generalized recursive least-square (RLS) algorithm, taking into consideration a set of EEG epochs. Simulations were performed under different levels of Signal to Noise Ratio (SNR), number of trials (TRIALS) and frequency bands (BAND), and of different values of the RLS adaptation factor adopted (factor C). The results indicated that time-varying DTF and PDC are able to estimate correctly the imposed connectivity patterns under reasonable operative conditions of SNR ad number of trials. Moreover, the capability of follow the rapid changes in connectivity is highly increased by the number of trials at disposal, and by the right choice of the value adopted for the adaptation factor C. The results of the simulation study indicate that DTF and PDC computed on adaptive MVAR can be effectively used to estimate time-varying patterns of functional connectivity between cortical activations, under general conditions met in practical EEG recordings.