Safety, pharmacokinetics, pharmacogenomics and QT concentration-effect modelling of the SirT1 inhibitor selisistat in healthy volunteers.

AIM: Selisistat (SEN0014196), a first-in-class SirT1 inhibitor, is being developed as a disease-modifying therapy for Huntington's disease. This first-in-human study investigated the safety, pharmacokinetics and pharmacogenomics of single and multiple doses of selisistat in healthy male and female subjects. METHOD: In this double-blind, randomized, placebo-controlled study, seven cohorts of eight subjects received a single dose of selisistat at dose levels of 5, 25, 75, 150, 300 and 600 mg and four cohorts of eight subjects were administered 100, 200 and 300 mg once daily for 7 days. Blood sampling and safety assessments were conducted throughout the study. RESULTS: Selisistat was rapidly absorbed and systemic exposure increased in proportion to dose in the 5-300 mg range. Steady-state plasma concentrations were achieved within 4 days of repeated dosing. The incidence of drug related adverse events showed no correlation with dose level or number of doses received and was comparable with the placebo group. No serious adverse events were reported and no subjects were withdrawn due to adverse events. There were no trends in clinical laboratory parameters or vital signs. No trends in heart rate or ECG parameters, including the QTc interval and T-wave morphology, were observed. There were no findings in physical or neurological examinations or postural control. Transcriptional alteration was observed in peripheral blood. CONCLUSION: Selisistat was safe and well tolerated by healthy male and female subjects after single doses up to 600 mg and multiple doses up to 300 mg day(-1).

An exploratory double-blind, randomized clinical trial with selisistat, a SirT1 inhibitor, in patients with Huntington's disease.

AIMS: Selisistat, a selective SirT1 inhibitor is being developed as a potentially disease-modifying therapeutic for Huntington's disease (HD). This was the first study of selisistat in HD patients and was primarily aimed at development of pharmacodynamic biomarkers. METHODS: This was a randomized, double-blind, placebo-controlled, multicentre exploratory study. Fifty-five male and female patients in early stage HD were randomized to receive 10 mg or 100 mg of selisistat or placebo once daily for 14 days. Blood sampling, clinical and safety assessments were conducted throughout the study. Candidate pharmacodynamic markers included circulating soluble huntingtin and innate immune markers. RESULTS: Selisistat was found to be safe and well tolerated, and systemic exposure parameters showed that the average steady-state plasma concentration achieved at the 10 mg dose level (125 nm) was comparable with the IC50 for SirT1 inhibition. No adverse effects on motor, cognitive or functional readouts were recorded. While circulating levels of soluble huntingtin were not affected by selisistat in this study, the biological samples collected have allowed development of assay technology for use in future studies. No effects on innate immune markers were seen. CONCLUSIONS: Selisistat was found to be safe and well tolerated in early stage HD patients at plasma concentrations within the anticipated therapeutic concentration range.

Robust MS quantification method for phospho-peptides using 18O/16O labeling.

BACKGROUND: Quantitative measurements of specific protein phosphorylation sites, as presented here, can be used to investigate signal transduction pathways, which is an important aspect of cell dynamics. The presented method quantitatively compares peptide abundances from experiments using 18O/16O labeling starting from elaborated MS spectra. It was originally developed to study signaling cascades activated by amyloid-beta treatment of neurons used as a cellular model system with relevance to Alzheimer's disease, but is generally applicable. RESULTS: The presented method assesses, in complete cell lysates, the degree of phosphorylation of specific peptide residues from MS spectra using 18O/16O labeling. The abundance of each observed phospho-peptide from two cell states was estimated from three overlapping isotope contours. The influence of peptide-specific labeling efficiency was removed by performing a label swapped experiment and assuming that the labeling efficiency was unchanged upon label swapping. Different degrees of phosphorylation were reported using the fold change measure which was extended with a confidence interval found to reflect the quality of the underlying spectra. Furthermore a new way of method assessment using simulated data is presented. Using simulated data generated in a manner mimicking real data it was possible to show the method's robustness both with increasing noise levels and with decreasing labeling efficiency. CONCLUSION: The fold change error assessable on simulated data was on average 0.16 (median 0.10) with an error-to-signal ratio and labeling efficiency distributions similar to the ones found in the experimentally observed spectra. Applied to experimentally observed spectra a very good match was found to the model (<10% error for 85% of spectra) with a high degree of robustness, as assessed by data removal. This new method can thus be used for quantitative signal cascade analysis of total cell extracts in a high throughput mode.

Application of Modeling Approaches to Explore Vaccine Adjuvant Mode-of-Action.

Novel adjuvant technologies have a key role in the development of next-generation vaccines, due to their capacity to modulate the duration, strength and quality of the immune response. The AS01 adjuvant is used in the malaria vaccine RTS,S/AS01 and in the licensed herpes-zoster vaccine (Shingrix) where the vaccine has proven its ability to generate protective responses with both robust humoral and T-cell responses. For many years, animal models have provided insights into adjuvant mode-of-action (MoA), generally through investigating individual genes or proteins. Furthermore, modeling and simulation techniques can be utilized to integrate a variety of different data types; ranging from serum biomarkers to large scale "omics" datasets. In this perspective we present a framework to create a holistic integration of pre-clinical datasets and immunological literature in order to develop an evidence-based hypothesis of AS01 adjuvant MoA, creating a unified view of multiple experiments. Furthermore, we highlight how holistic systems-knowledge can serve as a basis for the construction of models and simulations supporting exploration of key questions surrounding adjuvant MoA. Using the Systems-Biology-Graphical-Notation, a tool for graphical representation of biological processes, we have captured high-level cellular behaviors and interactions, and cytokine dynamics during the early immune response, which are substantiated by a series of diagrams detailing cellular dynamics. Through explicitly describing AS01 MoA we have built a consensus of understanding across multiple experiments, and so we present a framework to integrate modeling approaches into exploring adjuvant MoA, in order to guide experimental design, interpret results and inform rational design of vaccines.

Increased expression of the oligopeptidase THOP1 is a neuroprotective response to Abeta toxicity.

In a comprehensive proteomics study aiming at the identification of proteins associated with amyloid-beta (Abeta)-mediated toxicity in cultured cortical neurons, we have identified Thimet oligopeptidase (THOP1). Functional modulation of THOP1 levels in primary cortical neurons demonstrated that its overexpression was neuroprotective against Abeta toxicity, while RNAi knockdown made neurons more vulnerable to amyloid peptide. In the TgCRND8 transgenic mouse model of amyloid plaque deposition, an age-dependent increase of THOP1 expression was found in brain tissue, where it co-localized with Abeta plaques. In accordance with these findings, THOP1 expression was significantly increased in human AD brain tissue as compared to non-demented controls. These results provide compelling evidence for a neuroprotective role of THOP1 against toxic effects of Abeta in the early stages of AD pathology, and suggest that the observed increase in THOP1 expression might be part of a compensatory defense mechanism of the brain against an increased Abeta load.

DSSPcont: Continuous secondary structure assignments for proteins.

The DSSP program automatically assigns the secondary structure for each residue from the three-dimensional co-ordinates of a protein structure to one of eight states. However, discrete assignments are incomplete in that they cannot capture the continuum of thermal fluctuations. Therefore, DSSPcont (http://cubic.bioc.columbia.edu/services/DSSPcont) introduces a continuous assignment of secondary structure that replaces 'static' by 'dynamic' states. Technically, the continuum results from calculating weighted averages over 10 discrete DSSP assignments with different hydrogen bond thresholds. A DSSPcont assignment for a particular residue is a percentage likelihood of eight secondary structure states, derived from a weighted average of the ten DSSP assignments. The continuous assignments have two important features: (i) they reflect the structural variations due to thermal fluctuations as detected by NMR spectroscopy; and (ii) they reproduce the structural variation between many NMR models from one single model. Therefore, functionally important variation can be extracted from a single X-ray structure using the continuous assignment procedure.

Continuum secondary structure captures protein flexibility.

The DSSP program assigns protein secondary structure to one of eight states. This discrete assignment cannot describe the continuum of thermal fluctuations. Hence, a continuous assignment is proposed. Technically, the continuum results from averaging over ten discrete DSSP assignments with different hydrogen bond thresholds. The final continuous assignment for a single NMR model successfully reflected the structural variations observed between all NMR models in the ensemble. The structural variations between NMR models were verified to correlate with thermal motion; these variations were captured by the continuous assignments. Because the continuous assignment reproduces the structural variation between many NMR models from one single model, functionally important variation can be extracted from a single X-ray structure. Thus, continuous assignments of secondary structure may affect future protein structure analysis, comparison, and prediction.

Brain penetration assessment in vivo: a reliable and simple method in anesthetized rats at steady state.

BACKGROUND: For CNS drugs, brain disposition is of critical importance during drug discovery. In vitro methods are used early followed by more predictive in vivo methods later on in the drug discovery process. Current in vivo methods are costly, have long turnover times or do not measure brain disposition at steady state. NEW METHOD: A new method to evaluate drug brain disposition in vivo was developed in anaesthetized rats. Seven reference compounds were administered as an initial IV bolus (loading dose) followed by IV infusion for 4.5 h in order to obtain a steady state plasma concentration before brain sampling. The loading dose was estimated from a preliminary single dose IV pharmacokinetic study and was found to successfully bring plasma concentrations to steady state for compounds exhibiting either mono- or bi-compartmental pharmacokinetics. RESULTS: Using this method, a steady state lasting at least 2h was obtained, thus making the in vivo method robust with respect to differences in the pharmacokinetics and/or blood-to-brain equilibration rate of the compounds tested. The method produced highly reproducible results, with substantial advantages in terms of cost, turnaround time and animal welfare. COMPARISON WITH EXISTING METHODS: The results agreed with those reported in other, more elaborate preclinical models and in humans, enabling brain disposition to be assessed in a simple, efficient and robust in vivo model for new chemical entities. CONCLUSIONS: Introducing the presented method in drug discovery allows brain disposition to be assessed earlier in the drug discovery pipeline and thus facilitate the selection of potent and penetrant CNS drugs.