ABSTRACT
Human-ether-a-go-go-related channel (hERG1) is the pore-forming domain of the delayed rectifier K+ channel in the heart which underlies the IKr current. The channel has been extensively studied due to its propensity to bind chemically diverse group of drugs. The subsequent hERG1 block can lead to a prolongation of the QT interval potentially leading to an abnormal cardiac electrical activity. The recently solved cryo-EM structure featured a striking non-swapped topology of the Voltage-Sensor Domain (VSD) which is packed against the pore-domain as well as a small and hydrophobic intra-cavity space. The small size and hydrophobicity of the cavity was unexpected and challenges the already-established hypothesis of drugs binding to the wide cavity. Recently, we showed that an amphipathic drug, ivabradine, may favorably bind the channel from the lipid-facing surface and we discovered a mutant (M651T) on the lipid facing domain between the VSD and the PD which inhibited the blocking capacity of the drug. Using multi-microseconds Molecular Dynamics (MD) simulations of wild-type and M651T mutant hERG1, we suggested the block of the channel through the lipid mediated pathway, the opening of which is facilitated by the flexible phenylalanine ring (F656). In this study, we characterize the dynamic interaction of the methionine-aromatic cassette in the S5-S6 helices by combining data from electrophysiological experiments with MD simulations and molecular docking to elucidate the complex allosteric coupling between drug binding to lipid-facing and intra-cavity sites and aromatic cassette dynamics. We investigated two well-established hERG1 blockers (ivabradine and dofetilide) for M651 sensitivity through electrophysiology and mutagenesis techniques. Our electrophysiology data reveal insensitivity of dofetilide to the mutations at site M651 on the lipid facing side of the channel, mirroring our results obtained from docking experiments. Moreover, we show that the dofetilide-induced block of hERG1 occurs through the intracellular space, whereas little to no block of ivabradine is observed during the intracellular application of the drug. The dynamic conformational rearrangement of the F656 appears to regulate the translocation of ivabradine into the central cavity. M651T mutation appears to disrupt this entry pathway by altering the molecular conformation of F656.
ABSTRACT
BACKGROUND: Multispectral image analysis is an emerging tool that utilizes both spatial and spectral image information to classify images that can be used for the differentiation between benign versus malignant cells. The aim of the current study was to analyze the ability of this tool in differentiating subtle cytologic differences that cannot be appreciated by the human eye. Herein, the authors used fine-needle aspirations (FNAs) of follicular adenoma (FA) and parathyroid adenoma (PA) as a test case. METHODS: The Nuance platform was used to collect image stacks that were subsequently analyzed with CRI-MLS software, a neural network-based artificial intelligence system that can classify images using automatically "learned" spatial-spectral features. CRI-MLS was trained on random, well-preserved FA cells and PA cells from the training set (n = 45 cells each). An algorithmic solution was developed and then validated on an independent series comprised of 1904 FA cells from 5 FA cases and 690 PA cells from 5 PA cases. RESULTS: The solution from the CRI-MLS classifier showed 1876 FA cells (98.5%) as true FA and 28 FA cells (1.5%) as false PA, whereas 663 PA cells (96%) were true PA and 27 PA cells (4%) were false FA. The summary result of this solution was a sensitivity of 98.5%, a specificity of 96.1%, and a positive predictive value of 98.6%. CONCLUSIONS: The best spatial-spectral imaging solution was able to correctly classify 2534 of 2594 cells (98%) and misclassified only 55 of 2594 cells (2%). These data suggest that this technology may be valuable in a clinical setting to help differentiate and classify morphologically similar lesions.
