Histone deacetylase (HDAC) inhibitors have shown promise in treating various forms of cancer. However, many HDAC inhibitors from diverse structural classes have been associated with QT prolongation in humans. Inhibition of the human ether a-go-go related gene (hERG) channel has been associated with QT prolongation and fatal arrhythmias. To determine if the observed cardiac effects of HDAC inhibitors in humans is due to hERG blockade, a highly potent HDAC inhibitor devoid of hERG activity was required. Starting with dacinostat (LAQ824), a highly potent HDAC inhibitor, we explored the SAR to determine the pharmacophores required for HDAC and hERG inhibition. We disclose here the results of these efforts where a high degree of pharmacophore homology between these two targets was discovered. This similarity prevented traditional strategies for mitigating hERG binding/modulation from being successful and novel approaches for reducing hERG inhibition were required. Using a hERG homology model, two compounds, 11r and 25i, were discovered to be highly efficacious with weak affinity for the hERG and other ion channels.

The smooth pursuit gain (SPG) is defined as the ratio of the angular velocity of the eye to that of the moving target. Being evaluated at a certain frequency of harmonic visual stimuli, it has been widely used in medicine as a measure of oculomotor system performance. In this study, the smooth pursuit system (SPS) is modeled as a dynamical system whose output signal is the angular velocity of the eye and the input is the angular velocity of a moving stimulus. Then, by means of system identification, the entire dynamics of SPS can be estimated, provided the visual stimuli are properly designed. This technique is referred to as the dynamic SPG (DSPG). Systems appearing equivalent in terms of SPG, can therefore be distinguished between using DSPG. Modern eye tracking techniques register gaze direction over time, but do not measure gaze velocity. Hence, to estimate the SPG/DSPG, differentiation must be applied to the output of the eye tracker. Four approaches to differentiation of eye-tracking data are evaluated in this paper with respect to the estimation of DSPG, out of which the method based on Laguerre functions stands out as the most reliable technique for this particular application.

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