Corrigendum to “A systematic strategy for estimating hERG block potency and its implications in a new cardiac safety paradigm” [Toxicology and Applied Pharmacology volume 394C (2020) 114961]

© 2020 The Author(s) The authors regret that one affiliation address is mistaken in the published paper. Matthew Bridgland-Taylor's affiliation was incorrectly listed as Clinical Pharmacology & Safety Sciences, R&D, AstraZeneca, Cambridge, United Kingdom. The correct affiliation is Clinical Pharmacology & Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, United Kingdom. The authors would like to apologise for any inconvenience caused

A systematic strategy for estimating hERG block potency and its implications in a new cardiac safety paradigm

© 2020 Introduction: hERG block potency is widely used to calculate a drug's safety margin against its torsadogenic potential. Previous studies are confounded by use of different patch clamp electrophysiology protocols and a lack of statistical quantification of experimental variability. Since the new cardiac safety paradigm being discussed by the International Council for Harmonisation promotes a tighter integration of nonclinical and clinical data for torsadogenic risk assessment, a more systematic approach to estimate the hERG block potency and safety margin is needed. Methods: A cross-industry study was performed to collect hERG data on 28 drugs with known torsadogenic risk using a standardized experimental protocol. A Bayesian hierarchical modeling (BHM) approach was used to assess the hERG block potency of these drugs by quantifying both the inter-site and intra-site variability. A modeling and simulation study was also done to evaluate protocol-dependent changes in hERG potency estimates. Results: A systematic approach to estimate hERG block potency is established. The impact of choosing a safety margin threshold on torsadogenic risk evaluation is explored based on the posterior distributions of hERG potency estimated by this method. The modeling and simulation results suggest any potency estimate is specific to the protocol used. Discussion: This methodology can estimate hERG block potency specific to a given voltage protocol. The relationship between safety margin thresholds and torsadogenic risk predictivity suggests the threshold should be tailored to each specific context of use, and safety margin evaluation may need to be integrated with other information to form a more comprehensive risk assessment

Arrhenius And Absolute Reaction Rate Models for Thermodynamic Characterization of Linamarase (Β-Glucosidase) using Linamarin Substrate

Thermodynamic characterization of linamarase (β-glucosidase)influenced by linamarin substrate purification, pH and temperature were investigated. In the study, recombinant Saccharomyces cerevisiae cells at the stationary phase of growth were recovered, homogenized and centrifuged to obtain crude extracts designated as GELIN0. Carboxy methyl cellulose, diethyl amino-ethyl-sephadex and diethyl amino-ethyl-cellulose were used to purify the crude extracts resulting in GELIN1, GELIN2 and GELIN3, respectively. Commercial native linamarase (CNLIN) was purchased and used as control. The ability of the GELIN extracts(β-glucosidase) and the commercial native linamarase (CNLIN) to hydrolyse cyanogenic glucosides was challenged using linamarin extracted from cassava as substrates. Degradation of linamarin was evaluated at optimum pH 6.8 using a 4 × 6 × 8 between and within factorial design comprising of 4 enzyme types (GELIN0, GELIN1, GELIN2 and GELIN3), and 6 temperatures (25, 27, 29, 31, 33, 35 oC, respectively) and 8 time intervals (0, 10, 20, 30, 40, 50, 60 and 70 min.). Data obtained from residual hydrocyanic acid with time were fitted with zero, first and second order kinetics, respectively, to determine the best fit order (based on r2 and linearity). Arrhenius and absolute reaction rate models were applied to obtain activation energies (Ea), frequency factor (K0) and enthalpy (ΔH#), entropy (ΔS#), respectively, that characterized the reactions. The results indicated that the degradation of linamarin by GELIN at the optimum pH 6.8 was best described by first order kinetics, Arrhenius and absolute reaction rate models showing high coefficient of linear regression (r2>0.996) with reaction rate constant increasing from 0.0252 -0.0923 min-1 with enzyme purification ranging for GELIN0 – GELIN3. Frequency factor (Ko), Ea, ΔH# and ΔS# values decreased with enzyme purification. Activation energy (Ea) values for the degradation of linamarin (GELIN0 – GELIN3) ranged from 60.9 to 91.7 kJ/mol. Enthalpy values varied from 58 to 89 kJ/mol while ΔS# values varied from -92.8 to 4.1 J/mol. deg.) indicating spontaneous and irreversible degradation reactions which suggest a possible use of the purified linamarase (β-glucosidase) in detoxification process for foods containing linamarin.Keywords: purified linamarase, rate models, linamarin, Saccharomyces cerevisiae, cassav

Insights into the structure and regulation of glucokinase from a novel mutation (V62M), which causes maturity-onset diabetes of the young.

Abstract Glucokinase (GCK) serves as the pancreatic glucose sensor. Heterozygous inactivating GCK mutations cause hyperglycemia, whereas activating mutations cause hypoglycemia. We studied the GCK V62M mutation identified in two families and co-segregating with hyperglycemia to understand how this mutation resulted in reduced function. Structural modeling locates the mutation close to five naturally occurring activating mutations in the allosteric activator site of the enzyme. Recombinant glutathionyl S-transferase-V62M GCK is paradoxically activated rather than inactivated due to a decreased S0.5 for glucose compared with wild type (4.88 versus 7.55 mM). The recently described pharmacological activator (RO0281675) interacts with GCK at this site. V62M GCK does not respond to RO0281675, nor does it respond to the hepatic glucokinase regulatory protein (GKRP). The enzyme is also thermally unstable, but this lability is apparently less pronounced than in the proven instability mutant E300K. Functional and structural analysis of seven amino acid substitutions at residue Val62 has identified a non-linear relationship between activation by the pharmacological activator and the van der Waals interactions energies. Smaller energies allow a hydrophobic interaction between the activator and glucokinase, whereas larger energies prohibit the ligand from fitting into the binding pocket. We conclude that V62M may cause hyperglycemia by a complex defect of GCK regulation involving instability in combination with loss of control by a putative endogenous activator and/or GKRP. This study illustrates that mutations that cause hyperglycemia are not necessarily kinetically inactivating but may exert their effects by other complex mechanisms. Elucidating such mechanisms leads to a deeper understanding of the GCK glucose sensor and the biochemistry of \u3b2-cells and hepatocytes