HERG potassium channel regulation by the N-terminal eag domain

Human ether-á-go-go related gene (hERG, K(v)11.1) potassium channels play a significant role in cardiac excitability. Like other K(v) channels, hERG is activated by membrane voltage; however, distinct from other K(v) channels, hERG channels have unusually slow kinetics of closing (deactivation). The mechanism for slow deactivation involves an N-terminal "eag domain" which comprises a PAS (Per-Arnt-Sim) domain and a short Cap domain. Here we review recent advances in understanding how the eag domain regulates deactivation, including several new Nuclear Magnetic Resonance (NMR) solution structures of the eag domain, and evidence showing that the eag domain makes a direct interaction with the C-terminal C-linker and Cyclic Nucleotide-Binding Homology Domain.     

Evaluation of a high-throughput fluorescence assay method for HERG potassium channel inhibition

The number of projects in drug development that fail in late phases because of cardiac side effects such as QT prolongation can impede drug discovery and development of projects. The molecular target responsible for QT prolongation by a wide range of pharmaceutical agents is the myocardial hERG potassium channel. It is therefore desirable to screen for compound interactions with the hERG channel at an early stage of drug development. Here, the authors report a cell-based fluorescence assay using membrane potential-sensitive fluorescent dyes and stably transfected hERG channels from CHO cells. The assay allows semiautomated screening of compounds for hERG activity on 384-well plates and is sufficiently rapid for testing a large number of compounds. The assay is robust as indicated by a Z' factor larger than 0.6. The throughput is in the range of 10,000 data points per day, which is significantly higher than any other method presently available for hERG. The data obtained with the fluorescence assay were in qualitative agreement with those from patch-clamp electrophysiological analysis. There were no false-positive hits, and the rate of false-negative compounds is currently 12% but might be further reduced by testing compounds at higher concentration. Quantitative differences between fluorescence and electrophysiological methods may be due to the use- or voltage-dependent activity of the antagonists.     

A model for identifying HERG K+ channel blockers

Acquired long QT syndrome (LQTS) occurs frequently as a side effect of blockade of cardiac HERG K(+) channels by commonly used medications. A large number of structurally diverse compounds have been shown to inhibit K(+) current through HERG. There is considerable interest in developing in silico tools to filter out potential HERG blockers early in the drug discovery process. We describe a binary classification model that combines a 2D topological similarity filter with a 3D pharmacophore ensemble procedure to discriminate between HERG actives and inactives with an overall accuracy of 82%, with false negative and false positive rates of 29% and 15%, respectively. This model should be generally applicable in virtual library counterscreening against HERG.     

Improved method for predicting beta-turn using support vector machine

MOTIVATION: Numerous methods for predicting beta-turns in proteins have been developed based on various computational schemes. Here, we introduce a new method of beta-turn prediction that uses the support vector machine (SVM) algorithm together with predicted secondary structure information. Various parameters from the SVM have been adjusted to achieve optimal prediction performance. RESULTS: The SVM method achieved excellent performance as measured by the Matthews correlation coefficient (MCC = 0.45) using a 7-fold cross validation on a database of 426 non-homologous protein chains. To our best knowledge, this MCC value is the highest achieved so far for predicting beta-turn. The overall prediction accuracy Qtotal was 77.3%, which is the best among the existing prediction methods. Among its unique attractive features, the present SVM method avoids overtraining and compresses information and provides a predicted reliability index.     

复杂疾病驱使的融合SDA-SVM集成基因挖掘方法

提出了一种新颖的复杂疾病驱使的融合SDA-SVM(Stepwise Discriminant Analysis-Support Vector Machine,SDA-SVM)技术的集成基因挖掘方法。该集成方法融合逐步判别分析和支持向量机的优点,能够有效地进行复杂疾病相关基因的深度挖掘,使得挖掘出的基因能够较好地识别疾病类型和亚型。通过将该方法应用于一套弥散性大B细胞淋巴瘤DNA表达谱数据,并与其它基因挖掘方法对比,结果表明该方法挖掘出的基因具有较高的疾病相关性和较强的疾病类型识别能力。     

Coupled K+-water flux through the HERG potassium channel measured by an osmotic pulse method

The streaming potential (V(stream)) is a signature feature of ion channels in which permeating ions and water molecules move in a single file. V(stream) provides a quantitative measure of the ion and water flux (the water-ion coupling ratio), the knowledge of which is a prerequisite for elucidating the mechanisms of ion permeation. We have developed a method to measure V(stream) with the whole-cell patch-clamp configuration. A HEK293 cell stably expressing the HERG potassium channel was voltage clamped and exposed to hyperosmotic solutions for short periods of time (<1 s) by an ultrafast solution switching system (the osmotic pulse [quick jump-and-away] method). The reversal potentials were monitored by a series of voltage ramps before, during, and after the osmotic pulse. The shifts of the reversal potentials immediately after the osmotic jump gave V(stream). In symmetrical K+ solutions (10 mM), the V(stream)s measured at different osmolalities showed a linear relationship with a slope of -0.7 mV/DeltaOsm, from which the water-ion coupling ratio (n, the ratio of the flux of water to the flux of cations; Levitt, D.G., S.R. Elias, and J.M. Hautman. 1978. Biochim. Biophys. Acta. 512:436-451) was calculated to be 1.4. In symmetrical 100 mM K+ solutions, the coupling ratio was decreased significantly (n = 0.9), indicating that the permeation process through states with increased ion occupancy became significant. We presented a diagrammatic representation linking the water-ion coupling ratio to the mode of ion permeation and suggested that the coupling ratio of one may represent the least hydrated ion flux in the single-file pore.     

Ecological footprint model using the support vector machine technique

The per capita ecological footprint (EF) is one of the most widely recognized measures of environmental sustainability. It aims to quantify the Earth's biological resources required to support human activity. In this paper, we summarize relevant previous literature, and present five factors that influence per capita EF. These factors are: National gross domestic product (GDP), urbanization (independent of economic development), distribution of income (measured by the Gini coefficient), export dependence (measured by the percentage of exports to total GDP), and service intensity (measured by the percentage of service to total GDP). A new ecological footprint model based on a support vector machine (SVM), which is a machine-learning method based on the structural risk minimization principle from statistical learning theory was conducted to calculate the per capita EF of 24 nations using data from 123 nations. The calculation accuracy was measured by average absolute error and average relative error. They were 0.004883 and 0.351078% respectively. Our results demonstrate that the EF model based on SVM has good calculation performance.     

Local sequence information-based support vector machine to classify voltage-gated potassium channels

In our previous work,we developed a computational tool,PreK-ClassK-ClassKv,to predictand classify potassium (K~ ) channels.For K channel prediction (PreK) and classification at family level(ClassK),this method performs well.However,it does not perform so well in classifying voltage-gatedpotassium (Kv) channels (ClassKv).In this paper,a new method based on the local sequence information ofKv channels is introduced to classify Kv channels.Six transmembrane domains of a Kv channel protein areused to define a protein,and the dipeptide composition technique is used to transform an amino acid sequenceto a numerical sequence.A Kv channel protein is represented by a vector with 2000 elements,and a supportvector machine algorithm is applied to classify Kv channels.This method shows good performance withaverages of total accuracy (Acc),sensitivity (SE),specificity (SP),reliability (R) and Matthews correlationcoefficient (MCC) of 98.0%,89.9%,100%,0.95 and 0.94 respectively.The results indicate that the localsequence information-based method is better than the global sequence information-based method to classifyKv channels.     

Trapping of a methanesulfonanilide by closure of the HERG potassium channel activation gate

Deactivation of voltage-gated potassium (K(+)) channels can slow or prevent the recovery from block by charged organic compounds, a phenomenon attributed to trapping of the compound within the inner vestibule by closure of the activation gate. Unbinding and exit from the channel vestibule of a positively charged organic compound should be favored by membrane hyperpolarization if not impeded by the closed gate. MK-499, a methanesulfonanilide compound, is a potent blocker (IC(50) = 32 nM) of HERG K(+) channels. This bulky compound (7 x 20 A) is positively charged at physiological pH. Recovery from block of HERG channels by MK-499 and other methanesulfonanilides is extremely slow (Carmeliet 1992; Ficker et al. 1998), suggesting a trapping mechanism. We used a mutant HERG (D540K) channel expressed in Xenopus oocytes to test the trapping hypothesis. D540K HERG has the unusual property of opening in response to hyperpolarization, in addition to relatively normal gating and channel opening in response to depolarization (Sanguinetti and Xu 1999). The hyperpolarization-activated state of HERG was characterized by long bursts of single channel reopening. Channel reopening allowed recovery from block by 2 microM MK-499 to occur with time constants of 10.5 and 52.7 s at -160 mV. In contrast, wild-type HERG channels opened only briefly after membrane hyperpolarization, and thus did not permit recovery from block by MK-499. These findings provide direct evidence that the mechanism of slow recovery from HERG channel block by methanesulfonanilides is due to trapping of the compound in the inner vestibule by closure of the activation gate. The ability of HERG channels to trap MK-499, despite its large size, suggests that the vestibule of this channel is larger than the well studied Shaker K(+) channel.     

The regulation of the cardiac potassium channel (HERG) by caveolin-1

Protein-protein interaction plays a key role in the regulation of biological processes. The human potassium (HERG) channel is encoded by the ether-à-go-go-related gene (herg), and its activity may be regulated by association with other cellular proteins. To identify cellular proteins that might play a role in the regulation of the HERG channel, we screened a human heart cDNA library with the N terminus of HERG using a yeast 2-hybrid system, and identified caveolin-1 as a potential HERG partner. The interaction between these 2 proteins was confirmed by coimmunoprecipitation assay, and their overlapping subcellular localization was demonstrated by fluorescence immunocytochemistry. The physiologic implication of the protein-protein interaction was studied in whole-cell patch-clamp electrophysiology experiments. A significant increase in HERG current amplitude and a faster deactivation of tail current were observed in HEK293/HERG cells in a membrane lipid rafts disruption model and caveolin-1 knocked down cells by RNA interference. Alternatively, when caveolin-1 was overexpressed, the HERG current amplitude was significantly reduced and the tail current was deactivated more slowly. Taken together, these data indicate that HERG channels interact with caveolin-1 and are negatively regulated by this interaction. The finding from this study clearly demonstrates the regulatory role of caveolin-1 on HERG channels, and may help to understand biochemical events leading to arrhythmogenesis in the long QT syndrome in cardiac patients.     

Inhibition of HERG potassium channel current by the class 1a antiarrhythmic agent disopyramide

The Class 1a antiarrhythmic drug disopyramide (DISO) is associated with 'acquired' prolongation of the QT interval of the electrocardiogram (ECG). This potentially proarrhythmic effect is likely to reflect drug actions on ion channels involved in ventricular action potential repolarisation. In this study, we examined the effects of DISO on potassium channels encoded by HERG, as this K channel type has been implicated in both congenital and acquired long-QT syndromes (LQTS). Chinese hamster ovary cells were transiently transfected with HERG cDNA for subsequent whole cell patch clamp recording. HERG tail currents recorded at -40 mV following test pulses to +30 mV were inhibited in a dose-dependent fashion by DISO concentrations within the clinical range (IC50 = 7.23 +/- 0.72 microM; mean +/- SEM). Experiments with 10 microM DISO indicated that the degree of HERG blockade showed some voltage dependence. Further data obtained using an 'envelope of tails' protocol (pulse potential +40 mV) were consistent with a significant role for open-channel blockade at lower drug concentrations. At higher concentrations it is possible that blockade may have involved drug binding to both resting and open channels. Inhibition of the inactivation-deficient mutant HERG-S631A was comparable to that seen for wild-type HERG. Therefore, channel inactivation was not obligatory for DISO to exert its effect. Native delayed rectifier tail currents from rabbit isolated ventricular myocytes were also inhibited by DISO. We conclude (a) that DISO inhibits HERG encoded potassium channels at clinically relevant concentrations and (b) that this action may constitute the molecular basis for acquired LQTS associated with this drug.     

Deletion of protein kinase A phosphorylation sites in the HERG potassium channel inhibits activation shift by protein kinase A.

We investigated the role of protein kinase A (PKA) in regulation of the human ether-a-go-go-related gene (HERG) potassium channel activation. HERG clones with single mutations destroying one of four consensus PKA phosphorylation sites (S283A, S890A, T895A, S1137A), as well as one clone carrying all mutations with no PKA phosphorylation sites (HERG 4M) were constructed. These clones were expressed heterologously in Xenopus oocytes, and HERG potassium currents were measured with the two microelectrode voltage clamp technique. Application of the cAMP-specific phosphodiesterase (PDE IV) inhibitor Ro-20-1724 (100 microM), which results in an increased cAMP level and PKA stimulation, induced a reduction of HERG wild type outward currents by 19.1% due to a shift in the activation curve of 12.4 mV. When 100 microM Ro-20-1724 was applied to the HERG 4M channel, missing all PKA sites, there was no significant shift in the activation curve, and the current amplitude was not reduced. Furthermore, the adenylate cyclase activator forskolin that leads to PKA activation (400 microM, 60 min), shifted HERG wild type channel activation by 14.1 mV and reduced currents by 39.9%, whereas HERG 4M channels showed only a small shift of 4.3 mV and a weaker current reduction of 22.3%. We conclude that PKA regulates HERG channel activation, and direct phosphorylation of the HERG channel protein has a functional role that may be important in regulation of cardiac repolarization.     

Prediction of biological activity of Aurora-A kinase inhibitors by multilinear regression analysis and support vector machine

Several QSAR (quantitative structure-activity relationships) models for predicting the inhibitory activity of 117 Aurora-A kinase inhibitors were developed. The whole dataset was split into a training set and a test set based on two different methods, (1) by a random selection; and (2) on the basis of a Kohonen’s self-organizing map (SOM). Then the inhibitory activity of 117 Aurora-A kinase inhibitors was predicted using multilinear regression (MLR) analysis and support vector machine (SVM) methods, respectively. For the two MLR models and the two SVM models, for the test sets, the correlation coefficients of over 0.92 were achieved.     

A selective filter model of the potassium channel

A model based on analogy between filter and crown-ether molecule in a two-phase system organic solvent-water is proposed for potassium channel selective filter. The selectivity of K+-channel can be quantitatively described by this model.     

Pruning and model-selecting algorithms in the RBF frameworks constructed by support vector learning

This paper presents the pruning and model-selecting algorithms to the support vector learning for sample classification and function regression. When constructing RBF network by support vector learning we occasionally obtain redundant support vectors which do not significantly affect the final classification and function approximation results. The pruning algorithms primarily based on the sensitivity measure and the penalty term. The kernel function parameters and the position of each support vector are updated in order to have minimal increase in error, and this makes the structure of SVM network more flexible. We illustrate this approach with synthetic data simulation and face detection problem in order to demonstrate the pruning effectiveness.