Toward a consensus model of the HERG potassium channel

In silico prediction of hERG blockers using machine learning and deep learning approaches

The human ether-à-go-go-related gene (hERG) is associated with drug cardiotoxicity. If the hERG channel is blocked, it will lead to prolonged QT interval and cause sudden death in severe cases. Therefore, it is important to evaluate the hERG-blocking property of compounds in early drug discovery. In this study, a dataset containing 4556 compounds with IC50 values determined by patch clamp techniques on mammalian lineage cells was collected, and hERG blockers and non-blockers were distinguished according to three single thresholds and two binary thresholds. Four machine learning (ML) algorithms combining four molecular fingerprints and molecular descriptors as well as graph convolutional neural networks (GCNs) were used to construct a series of binary classification models. The results showed that the best models varied for different thresholds. The ML models implemented by support vector machine and random forest performed well based on Morgan fingerprints and molecular descriptors, with AUCs ranging from 0.884 to 0.950. GCN showed superior prediction performance with AUCs above 0.952, which might be related to its direct extraction of molecular features from the original input. Meanwhile, the classification of binary threshold was better than that of single threshold, which could provide us with a more accurate prediction of hERG blockers. At last, the applicability domain for the model was defined, and seven structural alerts that might generate hERG blockage were identified by information gain and substructure frequency analysis. Our work would be beneficial for identifying hERG blockers in chemicals.

Inhibition of the hERG Potassium Channel by a Methanesulphonate-Free E-4031 Analogue

hERG (human Ether-à-go-go Related Gene)-encoded potassium channels underlie the cardiac rapid delayed rectifier (IKr) potassium current, which is a major target for antiarrhythmic agents and diverse non-cardiac drugs linked to the drug-induced form of long QT syndrome. E-4031 is a high potency hERG channel inhibitor from the methanesulphonanilide drug family. This study utilized a methanesulphonate-lacking E-4031 analogue, "E-4031-17", to evaluate the role of the methanesulphonamide group in E-4031 inhibition of hERG. Whole-cell patch-clamp measurements of the hERG current (IhERG) were made at physiological temperature from HEK 293 cells expressing wild-type (WT) and mutant hERG constructs. For E-4031, WT IhERG was inhibited by a half-maximal inhibitory concentration (IC50) of 15.8 nM, whilst the comparable value for E-4031-17 was 40.3 nM. Both compounds exhibited voltage- and time-dependent inhibition, but they differed in their response to successive applications of a long (10 s) depolarisation protocol, consistent with greater dissociation of E-4031-17 than the parent compound between applied commands. Voltage-dependent inactivation was left-ward voltage shifted for E-4031 but not for E-4031-17; however, inhibition by both compounds was strongly reduced by attenuated-inactivation mutations. Mutations of S6 and S5 aromatic residues (F656V, Y652A, F557L) greatly attenuated actions of both drugs. The S624A mutation also reduced IhERG inhibition by both molecules. Overall, these results demonstrate that the lack of a methanesulphonate in E-4031-17 is not an impediment to high potency inhibition of IhERG.

Molecular dynamics of hERG channel: insights into understanding the binding of small molecules for detuning cardiotoxicity

Evaluation of cardiotoxicity potential of new chemical entities (NCEs) has lately become one of the stringent filters in the drug discovery and development process. Cardiotoxicity is caused mainly by the inhibition of human ether-a-go-go related gene (hERG) channel protein. Inhibition of the hERG channel leads to a life-threatening condition known as cardiac arrhythmia. Knowledge of the structural behaviour of the hERG would aid greatly in the design of new drug molecules that do not interact with the protein and add to the safety index. In this study, a computational model for the active-state of hERG was developed. This model was equilibrated by performing the molecular dynamics simulations for 100 ns followed by clustering and selection of a representative structure based on the largest populated cluster. To study the changes in the protein structure on inhibition, three inhibitory ligands, namely, dofetilide, cisapride and terfenadine were docked, followed by molecular dynamics simulations of 200 ns for the apo and each ligand-bound structure. It was observed that docking and simulation studies of the hERG model exhibited noticeable conformational changes in the protein upon ligand-binding. A significant change in the kink of the S6-transmembrane helix was observed. Inter-chain distances between the crucial residues Y652 and F656 (present below the ion-selectivity filter), their side-chain orientation and hydrogen bonding indicated a probable collapse of the pore. These changes may infer the initiation in transition of hERG from an open to an inactive state. Hence, these findings would help in designing compounds devoid of hERG inhibition with reduced cardiotoxicity.Communicated by Ramaswamy H. Sarma.

Refinement of a cryo-EM structure of hERG: Bridging structure and function

The human-ether-a-go-go-related gene (hERG) encodes the voltage-gated potassium channel (KCNH2 or Kv11.1, commonly known as hERG). This channel plays a pivotal role in the stability of phase 3 repolarization of the cardiac action potential. Although a high-resolution cryo-EM structure is available for its depolarized (open) state, the structure surprisingly did not feature many functionally important interactions established by previous biochemical and electrophysiology experiments. Using molecular dynamics flexible fitting (MDFF), we refined the structure and recovered the missing functionally relevant salt bridges in hERG in its depolarized state. We also performed electrophysiology experiments to confirm the functional relevance of a novel salt bridge predicted by our refinement protocol. Our work shows how refinement of a high-resolution cryo-EM structure helps to bridge the existing gap between the structure and function in the voltage-sensing domain (VSD) of hERG.

Assessing hERG1 Blockade from Bayesian Machine-Learning-Optimized Site Identification by Ligand Competitive Saturation Simulations

Drug-induced cardiotoxicity is a potentially lethal and yet one of the most common side effects with the drugs in clinical use. Most of the drug-induced cardiotoxicity is associated with an off-target pharmacological blockade of K+ currents carried out by the cardiac Human-Ether-a-go-go-Related (hERG1) potassium channel. There is a compulsory preclinical stage safety assessment for the hERG1 blockade for all classes of drugs, which adds substantially to the cost of drug development. The availability of a high-resolution cryogenic electron microscopy (cryo-EM) structure for the channel in its open/depolarized state solved in 2017 enabled the application of molecular modeling for rapid assessment of drug blockade by molecular docking and simulation techniques. More importantly, if successful, in silico methods may allow a path to lead-compound salvaging by mapping out key block determinants. Here, we report the blind application of the site identification by the ligand competitive saturation (SILCS) protocol to map out druggable/regulatory hotspots in the hERG1 channel available for blockers and activators. The SILCS simulations use small solutes representative of common functional groups to sample the chemical space for the entire protein and its environment using all-atom simulations. The resulting chemical maps, FragMaps, explicitly account for receptor flexibility, protein-fragment interactions, and fragment desolvation penalty allowing for rapid ranking of potential ligands as blockers or nonblockers of hERG1. To illustrate the power of the approach, SILCS was applied to a test set of 55 blockers with diverse chemical scaffolds and pIC50 values measured under uniform conditions. The original SILCS model was based on the all-atom modeling of the hERG1 channel in an explicit lipid bilayer and was further augmented with a Bayesian-optimization/machine-learning (BML) stage employing an independent literature-derived training set of 163 molecules. BML approach was used to determine weighting factors for the FragMaps contributions to the scoring function. pIC50 predictions from the combined SILCS/BML approach to the 55 blockers showed a Pearson correlation (PC) coefficient of >0.535 relative to the experimental data. SILCS/BML model was shown to yield substantially improved performance as compared to commonly used rigid and flexible molecular docking methods for a well-established cohort of hERG1 blockers, where no correlation with experimental data was recorded. SILCS/BML results also suggest that a proper weighting of protonation states of common blockers present at physiological pH is essential for accurate predictions of blocker potency. The precalculated and optimized SILCS FragMaps can now be used for the rapid screening of small molecules for their cardiotoxic potential as well as for exploring alternative binding pockets in the hERG1 channel with applications to the rational design of activators.

A structure-based computational workflow to predict liability and binding modes of small molecules to hERG

Off-target interactions of drugs with the human ether-à-go-go related gene 1 (hERG1) channel have been associated with severe cardiotoxic conditions leading to the withdrawal of many drugs from the market over the last decades. Consequently, predicting drug-induced hERG-liability is now a prerequisite in any drug discovery campaign. Understanding the atomic level interactions of drug with the channel is essential to guide the efficient development of safe drugs. Here we utilize the recent cryo-EM structure of the hERG channel and describe an integrated computational workflow to characterize different drug-hERG interactions. The workflow employs various structure-based approaches and provides qualitative and quantitative insights into drug binding to hERG. Our protocol accurately differentiated the strong blockers from weak and revealed three potential anchoring sites in hERG. Drugs engaging in all these sites tend to have high affinity towards hERG. Our results were cross-validated using a fluorescence polarization kit binding assay and with electrophysiology measurements on the wild-type (WT-hERG) and on the two hERG mutants (Y652A-hERG and F656A-hERG), using the patch clamp technique on HEK293 cells. Finally, our analyses show that drugs binding to hERG disrupt and hijack certain native—structural networks in the channel, thereby, gaining more affinity towards hERG.

Allosteric Coupling Between Drug Binding and the Aromatic Cassette in the Pore Domain of the hERG1 Channel: Implications for a State-Dependent Blockade

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 I_Kr 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.

An Update on the Structure of hERG

The human voltage-sensitive K⁺ channel hERG plays a fundamental role in cardiac action potential repolarization, effectively controlling the QT interval of the electrocardiogram. Inherited loss- or gain-of-function mutations in hERG can result in dangerous “long” (LQTS) or “short” QT syndromes (SQTS), respectively, and the anomalous susceptibility of hERG to block by a diverse range of drugs underlies an acquired LQTS. A recent open channel cryo-EM structure of hERG should greatly advance understanding of the molecular basis of hERG channelopathies and drug-induced LQTS. Here we describe an update of recent research that addresses the nature of the particular gated state of hERG captured in the new structure, and the insight afforded by the structure into the molecular basis for high affinity drug block of hERG, the binding of hERG activators and the molecular basis of hERG's peculiar gating properties. Interpretation of the pharmacology of natural SQTS mutants in the context of the structure is a promising approach to understanding the molecular basis of hERG inactivation, and the structure suggests how voltage-dependent changes in the membrane domain may be transmitted to an extracellular “turret” to effect inactivation through aromatic side chain motifs that are conserved throughout the KCNH family of channels.

Molecular Docking Guided Grid-Independent Descriptor Analysis to Probe the Impact of Water Molecules on Conformational Changes of hERG Inhibitors in Drug Trapping Phenomenon

Human ether a-go-go related gene (hERG) or KV11.1 potassium channels mediate the rapid delayed rectifier current (I_Kr) in cardiac myocytes. Drug-induced inhibition of hERG channels has been implicated in the development of acquired long QT syndrome type (aLQTS) and fatal arrhythmias. Several marketed drugs have been withdrawn for this reason. Therefore, there is considerable interest in developing better tests for predicting drugs which can block the hERG channel. The drug-binding pocket in hERG channels, which lies below the selectivity filter, normally contains K⁺ ions and water molecules. In this study, we test the hypothesis that these water molecules impact drug binding to hERG. We developed 3D QSAR models based on alignment independent descriptors (GRIND) using docked ligands in open and closed conformations of hERG in the presence (solvated) and absence (non-solvated) of water molecules. The ligand–protein interaction fingerprints (PLIF) scheme was used to summarize and compare the interactions. All models delineated similar 3D hERG binding features, however, small deviations of about ~0.4 Å were observed between important hotspots of molecular interaction fields (MIFs) between solvated and non-solvated hERG models. These small changes in conformations do not affect the performance and predictive power of the model to any significant extent. The model that exhibits the best statistical values was attained with a cryo_EM structure of the hERG channel in open state without water. This model also showed the best R² of 0.58 and 0.51 for the internal and external validation test sets respectively. Our results suggest that the inclusion of water molecules during the docking process has little effect on conformations and this conformational change does not impact the predictive ability of the 3D QSAR models.

Open-Access Activity Prediction Tools for Natural Products. Case Study: hERG Blockers

Interference with the hERG potassium ion channel may cause cardiac arrhythmia and can even lead to death. Over the last few decades, several drugs, already on the market, and many more investigational drugs in various development stages, have had to be discontinued because of their hERG-associated toxicity. To recognize potential hERG activity in the early stages of drug development, a wide array of computational tools, based on different principles, such as 3D QSAR, 2D and 3D similarity, and machine learning, have been developed and are reviewed in this chapter. The various available prediction tools Similarity Ensemble Approach, SuperPred, SwissTargetPrediction, HitPick, admetSAR, PASSonline, Pred-hERG, and VirtualToxLab™ were used to screen a dataset of known hERG synthetic and natural product actives and inactives to quantify and compare their predictive power. This contribution will allow the reader to evaluate the suitability of these computational methods for their own related projects. There is an unmet need for natural product-specific prediction tools in this field.

Electrophysiological mechanisms of vandetanib-induced cardiotoxicity: Comparison of action potentials in rabbit Purkinje fibers and pluripotent stem cell-derived cardiomyocytes

Vandetanib, a multi-kinase inhibitor used for the treatment of various cancers, has been reported to induce several adverse cardiac effects. However, the underlying mechanisms of vandetanib-induced cardiotoxicity are unclear. This study aimed to investigate the mechanism of vandetanib-induced cardiotoxicity using intracellular electrophysiological recordings on human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs), rabbit Purkinje fibers, and HEK293 cells transiently expressing human ether-a-go-go-related gene (hERG; the rapidly activating delayed rectifier K⁺ channel, I_Kr), KCNQ1/KCNE1 (the slowly activating delayed rectifier K⁺ current, I_Ks), KCNJ2 (the inwardly rectifying K⁺ current, I_K1) or SCN5A (the inward Na⁺ current, I_Na). Purkinje fiber assays and ion channel studies showed that vandetanib at concentrations of 1 and 3 μM inhibited the hERG currents and prolonged the action potential duration. Alanine scanning and in silico hERG docking studies demonstrated that Y652 and F656 in the hERG S6 domain play critical roles in vandetanib binding. In hiPSC-CMs, vandetanib markedly reduced the maximum rate of depolarization during the AP upstroke. Ion channel studies revealed that hiPSC-CMs were more sensitive to inhibition of the I_Na by vandetanib than in a heterogeneously expressed HEK293 cell model, consistent with the changes in the AP parameters of hiPSC-CMs. The subclasses of Class I antiarrhythmic drugs inhibited I_Na currents in a dose-dependent manner in hiPSC-CMs and SCN5A-encoded HEK293 cells. The inhibitory potency of vandetanib for I_Na was much higher in hiPSC-CMs (IC₅₀: 2.72 μM) than in HEK293 cells (IC₅₀: 36.63 μM). These data suggest that AP and I_Na assays using hiPSC-CMs are useful electrophysiological models for prediction of drug-induced cardiotoxicity.

Dehydroevodiamine and hortiamine, alkaloids from the traditional Chinese herbal drug Evodia rutaecarpa, are IKr blockers with proarrhythmic effects in vitro and in vivo

Evodiae fructus is a widely used herbal drug in traditional Chinese medicine. Evodia extract was found to inhibit hERG channels. The aim of the current study was to identify hERG inhibitors in Evodia extract and to investigate their potential proarrhythmic effects. Dehydroevodiamine (DHE) and hortiamine were identified as I_Kr (rapid delayed rectifier current) inhibitors in Evodia extract by HPLC-microfractionation and subsequent patch clamp studies on human embryonic kidney cells. DHE and hortiamine inhibited I_Kr with IC₅₀s of 253.2±26.3nM and 144.8±35.1nM, respectively. In dog ventricular cardiomyocytes, DHE dose-dependently prolonged the action potential duration (APD). Early afterdepolarizations (EADs) were seen in 14, 67, 100, and 67% of cells after 0.01, 0.1, 1 and 10μM DHE, respectively. The proarrhythmic potential of DHE was evaluated in 8 anesthetized rabbits and in 8 chronic atrioventricular block (cAVB) dogs. In rabbits, DHE increased the QT interval significantly by 12±10% (0.05mg/kg/5min) and 60±26% (0.5mg/kg/5min), and induced Torsade de Pointes arrhythmias (TdP, 0.5mg/kg/5min) in 2 rabbits. In cAVB dogs, 0.33mg/kg/5min DHE increased QT duration by 48±10% (P<0.05*) and induced TdP in 2/4 dogs. A higher dose did not induce TdP. In human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs), methanolic extracts of Evodia, DHE and hortiamine dose-dependently prolonged APD. At 3μM DHE and hortiamine induced EADs. hERG inhibition at submicromolar concentrations, APD prolongation and EADs in hiPSC-CMs and dose-dependent proarrhythmic effects of DHE at micromolar plasma concentrations in cAVB dogs should increase awareness regarding proarrhythmic effects of widely used Evodia extracts.

Modeling squid axon K+ channel by a nucleation and growth kinetic mechanism

A kinetic model accounting for all salient features of the K⁺ channel of the squid giant axon, including the rising phase of the ON gating charge and the Cole-Moore effect, is provided. Upon accounting for a significant feature distinguishing K⁺, Na⁺ and Ca²⁺ channels from channel-forming peptides modeled in our previous 2016 BBA paper, the nucleation-and-growth kinetic model developed therein is extended to simulate ON ionic and gating currents of the K⁺ channel of the squid giant axon at different depolarization potentials by the use of only two free parameters. K⁺ channel opening is considered to proceed by progressive aggregation of single subunits, while they are moving their gating charge outward under depolarizing conditions within their tetrameric structure; K⁺ channel closing proceeds in the opposite direction, by repolarization-induced disaggregation of subunits, accompanied by inward movement of their gating charge.

Modeling of the hERG K+ Channel Blockage Using Online Chemical Database and Modeling Environment (OCHEM)

Human ether-a-go-go related gene (hERG) K+ channel plays an important role in cardiac action potential. Blockage of hERG channel may result in long QT syndrome (LQTS), even cause sudden cardiac death. Many drugs have been withdrawn from the market because of the serious hERG-related cardiotoxicity. Therefore, it is quite essential to estimate the chemical blockage of hERG in the early stage of drug discovery. In this study, a diverse set of 3721 compounds with hERG inhibition data was assembled from literature. Then, we make full use of the Online Chemical Modeling Environment (OCHEM), which supplies rich machine learning methods and descriptor sets, to build a series of classification models for hERG blockage. We also generated two consensus models based on the top-performing individual models. The consensus models performed much better than the individual models both on 5-fold cross validation and external validation. Especially, consensus model II yielded the prediction accuracy of 89.5 % and MCC of 0.670 on external validation. This result indicated that the predictive power of consensus model II should be stronger than most of the previously reported models. The 17 top-performing individual models and the consensus models and the data sets used for model development are available at https://ochem.eu/article/103592.

Natural products modulating the hERG channel: heartaches and hope

This review covers natural products modulating the hERG potassium channel. Risk assessment strategies, structural features of blockers, and the duality target/antitarget are discussed.

Covering: 1996–December 2016

The human Ether-à-go-go Related Gene (hERG) channel is a voltage-gated potassium channel playing an essential role in the normal electrical activity in the heart. It is involved in the repolarization and termination of action potentials in excitable cardiac cells. Mutations in the hERG gene and hERG channel blockage by small molecules are associated with increased risk of fatal arrhythmias. Several drugs have been withdrawn from the market due to hERG channel-related cardiotoxicity. Moreover, as a result of its notorious ligand promiscuity, this ion channel has emerged as an important antitarget in early drug discovery and development. Surprisingly, the hERG channel blocking profile of natural compounds present in frequently consumed botanicals (i.e. dietary supplements, spices, and herbal medicinal products) is not routinely assessed. This comprehensive review will address these issues and provide a critical compilation of hERG channel data for isolated natural products and extracts over the past two decades (1996–2016). In addition, the review will provide (i) a solid basis for the molecular understanding of the physiological functions of the hERG channel, (ii) the translational potential of in vitro/in vivo results to cardiotoxicity in humans, (iii) approaches for the identification of hERG channel blockers from natural sources, (iv) future perspectives for cardiac safety guidelines and their applications within phytopharmaceuticals and dietary supplements, and (v) novel applications of hERG channel modulation (e.g. as a drug target).

Insights into channel dysfunction from modelling and molecular dynamics simulations

Developments in structural biology mean that the number of different ion channel structures has increased significantly in recent years. Structures of ion channels enable us to rationalize how mutations may lead to channelopathies. However, determining the structures of ion channels is still not trivial, especially as they necessarily exist in many distinct functional states. Therefore, the use of computational modelling can provide complementary information that can refine working hypotheses of both wild type and mutant ion channels. The simplest but still powerful tool is homology modelling. Many structures are available now that can provide suitable templates for many different types of ion channels, allowing a full three-dimensional interpretation of mutational effects. These structural models, and indeed the structures themselves obtained by X-ray crystallography, and more recently cryo-electron microscopy, can be subjected to molecular dynamics simulations, either as a tool to help explore the conformational dynamics in detail or simply as a means to refine the models further. Here we review how these approaches have been used to improve our understanding of how diseases might be linked to specific mutations in ion channel proteins. This article is part of the Special Issue entitled 'Channelopathies.'

A multiscale computational modelling approach predicts mechanisms of female sex risk in the setting of arousal-induced arrhythmias

KEY POINTS

This study represents a first step toward predicting mechanisms of sex-based arrhythmias that may lead to important developments in risk stratification and may inform future drug design and screening. We undertook simulations to reveal the conditions (i.e. pacing, drugs, sympathetic stimulation) required for triggering and sustaining reentrant arrhythmias. Using the recently solved cryo-EM structure for the Eag-family channel as a template, we revealed potential interactions of oestrogen with the pore loop hERG mutation (G604S). Molecular models suggest that oestrogen and dofetilide blockade can concur simultaneously in the hERG channel pore.

ABSTRACT

Female sex is a risk factor for inherited and acquired long-QT associated torsade de pointes (TdP) arrhythmias, and sympathetic discharge is a major factor in triggering TdP in female long-QT syndrome patients. We used a combined experimental and computational approach to predict 'the perfect storm' of hormone concentration, I_Kr block and sympathetic stimulation that induces arrhythmia in females with inherited and acquired long-QT. More specifically, we developed mathematical models of acquired and inherited long-QT syndrome in male and female ventricular human myocytes by combining effects of a hormone and a hERG blocker, dofetilide, or hERG mutations. These 'male' and 'female' model myocytes and tissues then were used to predict how various sex-based differences underlie arrhythmia risk in the setting of acute sympathetic nervous system discharge. The model predicted increased risk for arrhythmia in females when acute sympathetic nervous system discharge was applied in the settings of both inherited and acquired long-QT syndrome. Females were predicted to have protection from arrhythmia induction when progesterone is high. Males were protected by the presence of testosterone. Structural modelling points towards two plausible and distinct mechanisms of oestrogen action enhancing torsadogenic effects: oestradiol interaction with hERG mutations in the pore loop containing G604 or with common TdP-related blockers in the intra-cavity binding site. Our study presents findings that constitute the first evidence linking structure to function mechanisms underlying female dominance of arousal-induced arrhythmias.

Dynamics of the EAG1 K+ channel selectivity filter assessed by molecular dynamics simulations

EAG1 channels belong to the KCNH family of voltage gated potassium channels. They are expressed in several brain regions and increased expression is linked to certain cancer types. Recent cryo-EM structure determination finally revealed the structure of these channels in atomic detail, allowing computational investigations. In this study, we performed molecular dynamics simulations to investigate the ion binding sites and the dynamical behavior of the selectivity filter. Our simulations suggest that sites S2 and S4 form stable ion binding sites, while ions placed at sites S1 and S3 rapidly switched to sites S2 and S4. Further, ions tended to dissociate away from S0 within less than 20 ns, due to increased filter flexibility. This was followed by water influx from the extracellular side, leading to a widening of the filter in this region, and likely non-conductive filter configurations. Simulations with the inactivation-enhancing mutant Y464A or Na⁺ ions lead to trapped water molecules behind the SF, suggesting that these simulations captured early conformational changes linked to C-type inactivation.

Potassium currents in the heart: functional roles in repolarization, arrhythmia and therapeutics

This is the second of the two White Papers from the fourth UC Davis Cardiovascular Symposium Systems Approach to Understanding Cardiac Excitation-Contraction Coupling and Arrhythmias (3-4 March 2016), a biennial event that brings together leading experts in different fields of cardiovascular research. The theme of the 2016 symposium was 'K⁺ channels and regulation', and the objectives of the conference were severalfold: (1) to identify current knowledge gaps; (2) to understand what may go wrong in the diseased heart and why; (3) to identify possible novel therapeutic targets; and (4) to further the development of systems biology approaches to decipher the molecular mechanisms and treatment of cardiac arrhythmias. The sessions of the Symposium focusing on the functional roles of the cardiac K⁺ channel in health and disease, as well as K⁺ channels as therapeutic targets, were contributed by Ye Chen-Izu, Gideon Koren, James Weiss, David Paterson, David Christini, Dobromir Dobrev, Jordi Heijman, Thomas O'Hara, Crystal Ripplinger, Zhilin Qu, Jamie Vandenberg, Colleen Clancy, Isabelle Deschenes, Leighton Izu, Tamas Banyasz, Andras Varro, Heike Wulff, Eleonora Grandi, Michael Sanguinetti, Donald Bers, Jeanne Nerbonne and Nipavan Chiamvimonvat as speakers and panel discussants. This article summarizes state-of-the-art knowledge and controversies on the functional roles of cardiac K⁺ channels in normal and diseased heart. We endeavour to integrate current knowledge at multiple scales, from the single cell to the whole organ levels, and from both experimental and computational studies.

An antiarrhythmic agent as a promising lead compound for targeting the hEAG1 ion channel in cancer therapy: insights from molecular dynamics simulations

Experimental evidence suggests that hERG and hEAG potassium channels may serve as important cancer therapy targets because either of the channel blockade or inactivation by different methods leads to inhibition of cancer cells growth and proliferation. However, there is no known hEAG specific blocker, and hERG blockade leads to adverse cardiac side effects, although it is currently used in treating certain types of arrhythmias. There have been some attempts to explain the channels blockade by clofilium, an antiarrhythmic agent, and the results lead to different possible binding modes. This study investigates for the first time the potential of using clofilium as a lead compound for finding a novel cancer therapy agent which may target ion channels. The implied findings from a comparative assessment of literature studies were verified using molecular dynamics simulations. The results indicate a particular structural difference between the two channels that could provide a novel and realistic way of using clofilium analogs which may target the hEAG1 ion channel in cancer therapy.

New potential binding determinant for hERG channel inhibitors

Human ether-à-go-go related gene (hERG) 1 channels conduct the rapid delayed rectifier K⁺ current (I_Kr) and are essential for the repolarization of the cardiac action potential. hERG1 inhibition by structurally diverse drugs may lead to life threatening arrhythmia. Putative binding determinants of hERG1 channel blockers include T623, S624 and V625 on the pore helix, and residues G648, Y652 and F656, located on segment S6. We and others have previously hypothesized that additional binding determinants may be located on helix S5, which is in close contact with the S6 segments. In order to test this hypothesis, we performed a detailed investigation combining ionic current measurements with two-microelectrode voltage clamp and molecular modeling techniques. We identified a novel aromatic high affinity binding determinant for blockers located in helix S5, F557, which is equally potent as Y652. Modeling supports a direct interaction with the outer pore helix.

Drug trapping in hERG K+ channels: (not) a matter of drug size?

Inhibition of hERG K+ channels by structurally diverse drugs prolongs the ventricular action potential and increases the risk of torsade de pointes arrhythmias and sudden cardiac death. The capture of drugs behind closed channel gates, so-called drug trapping, is suggested to harbor an increased pro-arrhythmic risk. In this study, the trapping mechanisms of a trapped hERG blocker propafenone and a bulky derivative (MW: 647.24 g mol-1) were studied by making use of electrophysiological measurements in combination with molecular dynamics simulations. Our study suggests that the hERG cavity is able to accommodate very bulky compounds without disturbing gate closure.

In silico prediction of hERG inhibition

The voltage-gated potassium channel encoded by hERG carries a delayed rectifying potassium current (IKr) underlying repolarization of the cardiac action potential. Pharmacological blockade of the hERG channel results in slowed repolarization and therefore prolongation of action potential duration and an increase in the QT interval as measured on an electrocardiogram. Those are possible to cause sudden death, leading to the withdrawals of many drugs, which is the reason for hERG screening. Computational in silico prediction models provide a rapid, economic way to screen compounds during early drug discovery. In this review, hERG prediction models are classified as 2D and 3D quantitative structure–activity relationship models, pharmacophore models, classification models, and structure based models (using homology models of hERG).

The Therapeutic Potential of hERG1 K+ Channels for Treating Cancer and Cardiac Arrhythmias

hERG potassium channels present pharmacologists and medicinal chemists with a dilemma. On the one hand hERG is a major reason for drugs being withdrawn from the market because of drug induced long QT syndrome and the associated risk of inducing sudden cardiac death, and yet hERG blockers are still widely used in the clinic to treat cardiac arrhythmias. Moreover, in the last decade overwhelming evidence has been provided that hERG channels are aberrantly expressed in cancer cells and that they contribute to tumour cell proliferation, resistance to apoptosis, and neoangiogenesis. Here we provide an overview of the properties of hERG channels and their role in excitable cells of the heart and nervous system as well as in cancer. We consider the therapeutic potential of hERG, not only with regard to the negative impact due to drug induced long QT syndrome, but also its future potential as a treatment in the fight against cancer.

Structure-activity relationships of pentamidine-affected ion channel trafficking and dofetilide mediated rescue

BACKGROUND AND PURPOSE

Drug interference with normal hERG protein trafficking substantially reduces the channel density in the plasma membrane and thereby poses an arrhythmic threat. The chemical substructures important for hERG trafficking inhibition were investigated using pentamidine as a model drug. Furthermore, the relationship between acute ion channel block and correction of trafficking by dofetilide was studied.

EXPERIMENTAL APPROACH

hERG and K(IR)2.1 trafficking in HEK293 cells was evaluated by Western blot and immunofluorescence microscopy after treatment with pentamidine and six pentamidine analogues, and correction with dofetilide and four dofetilide analogues that displayed different abilities to inhibit IKr . Molecular dynamics simulations were used to address mode, number and type of interactions between hERG and dofetilide analogues.

KEY RESULTS

Structural modifications of pentamidine differentially affected plasma membrane levels of hERG and K(IR)2.1. Modification of the phenyl ring or substituents directly attached to it had the largest effect, affirming the importance of these chemical residues in ion channel binding. PA-4 had the mildest effects on both ion channels. Dofetilide corrected pentamidine-induced hERG, but not K(IR)2.1 trafficking defects. Dofetilide analogues that displayed high channel affinity, mediated by pi-pi stacks and hydrophobic interactions, also restored hERG protein levels, whereas analogues with low affinity were ineffective.

CONCLUSIONS AND IMPLICATIONS

Drug-induced trafficking defects can be minimized if certain chemical features are avoided or 'synthesized out'; this could influence the design and development of future drugs. Further analysis of such features in hERG trafficking correctors may facilitate the design of a non-blocking corrector for trafficking defective hERG proteins in both congenital and acquired LQTS.

Modelling three-dimensional protein structures for applications in drug design

A structural perspective of drug target and anti-target proteins, and their molecular interactions with biologically active molecules, largely advances many areas of drug discovery, including target validation, hit and lead finding and lead optimisation. In the absence of experimental 3D structures, protein structure prediction often offers a suitable alternative to facilitate structure-based studies. This review outlines recent methodical advances in homology modelling, with a focus on those techniques that necessitate consideration of ligand binding. In this context, model quality estimation deserves special attention because the accuracy and reliability of different structure prediction techniques vary considerably, and the quality of a model ultimately determines its usefulness for structure-based drug discovery. Examples of G-protein-coupled receptors (GPCRs) and ADMET-related proteins were selected to illustrate recent progress and current limitations of protein structure prediction. Basic guidelines for good modelling practice are also provided.

Assessing hERG pore models as templates for drug docking using published experimental constraints: the inactivated state in the context of drug block

Many structurally and therapeutically diverse drugs interact with the human heart K⁺ channel hERG by binding within the K⁺ permeation pathway of the open channel, leading to drug-induced ‘long QT syndrome’. Drug binding to hERG is often stabilized by inactivation gating. In the absence of a crystal structure, hERG pore homology models have been used to characterize drug interactions. Here we assess potentially inactivated states of the bacterial K⁺ channel, KcsA, as templates for inactivated state hERG pore models in the context of drug binding using computational docking. Although Flexidock and GOLD docking produced low energy score poses in the models tested, each method selected a MthK K⁺ channel-based model over models based on the putative inactivated state KcsA structures for each of the 9 drugs tested. The variety of docking poses found indicates that an optimal arrangement for drug binding of aromatic side chains in the hERG pore can be achieved in several different configurations. This plasticity of the drug “binding site” is likely to be a feature of the hERG inactivated state. The results demonstrate that experimental data on specific drug interactions can be used as structural constraints to assess and refine hERG homology models.

Mechanism of hERG channel block by the psychoactive indole alkaloid ibogaine

Ibogaine is a psychoactive indole alkaloid. Its use as an antiaddictive agent has been accompanied by QT prolongation and cardiac arrhythmias, which are most likely caused by human ether a go-go-related gene (hERG) potassium channel inhibition. Therefore, we studied in detail the interaction of ibogaine with hERG channels heterologously expressed in mammalian kidney tsA-201 cells. Currents through hERG channels were blocked regardless of whether ibogaine was applied via the extracellular or intracellular solution. The extent of inhibition was determined by the relative pH values. Block occurred during activation of the channels and was not observed for resting channels. With increasing depolarizations, ibogaine block grew and developed faster. Steady-state activation and inactivation of the channel were shifted to more negative potentials. Deactivation was slowed, whereas inactivation was accelerated. Mutations in the binding site reported for other hERG channel blockers (Y652A and F656A) reduced the potency of ibogaine, whereas an inactivation-deficient double mutant (G628C/S631C) was as sensitive as wild-type channels. Molecular drug docking indicated binding within the inner cavity of the channel independently of the protonation of ibogaine. Experimental current traces were fit to a kinetic model of hERG channel gating, revealing preferential binding of ibogaine to the open and inactivated state. Taken together, these findings show that ibogaine blocks hERG channels from the cytosolic side either in its charged form alone or in company with its uncharged form and alters the currents by changing the relative contribution of channel states over time.

SuperPain--a resource on pain-relieving compounds targeting ion channels

Pain is more than an unpleasant sensory experience associated with actual or potential tissue damage: it is the most common reason for physician consultation and often dramatically affects quality of life. The management of pain is often difficult and new targets are required for more effective and specific treatment. SuperPain (http://bioinformatics.charite.de/superpain/) is freely available database for pain-stimulating and pain-relieving compounds, which bind or potentially bind to ion channels that are involved in the transmission of pain signals to the central nervous system, such as TRPV1, TRPM8, TRPA1, TREK1, TRESK, hERG, ASIC, P2X and voltage-gated sodium channels. The database consists of ∼8700 ligands, which are characterized by experimentally measured binding affinities. Additionally, 100 000 putative ligands are included. Moreover, the database provides 3D structures of receptors and predicted ligand-binding poses. These binding poses and a structural classification scheme provide hints for the design of new analgesic compounds. A user-friendly graphical interface allows similarity searching, visualization of ligands docked into the receptor, etc.

Discovery and optimization of orally active cyclohexane-based prolylcarboxypeptidase (PrCP) inhibitors

The synthesis, SAR, binding affinities and pharmacokinetic profiles are described for a series of cyclohexane-based prolylcarboxypeptidase (PrCP) inhibitors discovered by high throughput screening. Compounds show high levels of ex vivo target engagement in mouse plasma 20 h post oral dose.

Ligand-protein interactions of selective casein kinase 1δ inhibitors

Casein kinase 1δ (CK1δ) and 1ε (CK1ε) are believed to be necessary enzymes for the regulation of circadian rhythms in all mammals. On the basis of our previously published work demonstrating a CK1ε-preferring compound to be an ineffective circadian clock modulator, we have synthesized a series of pyrazole-substitued pyridine inhibitors, selective for the CK1δ isoform. Additionally, using structure-based drug design, we have been able to exploit differences in the hinge region between CK1δ and p38 to find selective inhibitors that have minimal p38 activity. The SAR, brain exposure, and the effect of these inhibitors on mouse circadian rhythms are described. The in vivo evaluation of these inhibitors demonstrates that selective inhibition of CK1δ at sufficient central exposure levels is capable of modulating circadian rhythms.

Evolution of the genetic code by incorporation of amino acids that improved or changed protein function

Fifty years have passed since the genetic code was deciphered, but how the genetic code came into being has not been satisfactorily addressed. It is now widely accepted that the earliest genetic code did not encode all 20 amino acids found in the universal genetic code as some amino acids have complex biosynthetic pathways and likely were not available from the environment. Therefore, the genetic code evolved as pathways for synthesis of new amino acids became available. One hypothesis proposes that early in the evolution of the genetic code four amino acids-valine, alanine, aspartic acid, and glycine-were coded by GNC codons (N = any base) with the remaining codons being nonsense codons. The other sixteen amino acids were subsequently added to the genetic code by changing nonsense codons into sense codons for these amino acids. Improvement in protein function is presumed to be the driving force behind the evolution of the code, but how improved function was achieved by adding amino acids has not been examined. Based on an analysis of amino acid function in proteins, an evolutionary mechanism for expansion of the genetic code is described in which individual coded amino acids were replaced by new amino acids that used nonsense codons differing by one base change from the sense codons previously used. The improved or altered protein function afforded by the changes in amino acid function provided the selective advantage underlying the expansion of the genetic code. Analysis of amino acid properties and functions explains why amino acids are found in their respective positions in the genetic code.

Interactions between voltage sensor and pore domains in a hERG K+ channel model from molecular simulations and the effects of a voltage sensor mutation

The hERG K(+) channel is important for establishing normal electrical activity in the human heart. The channel's unique gating response to membrane potential changes indicates specific interactions between voltage sensor and pore domains that are poorly understood. In the absence of a crystal structure we constructed a homology model of the full hERG membrane domain and performed 0.5 μs molecular dynamics (MD) simulations in a hydrated membrane. The simulations identify potential interactions involving residues at the extracellular surface of S1 in the voltage sensor and at the N-terminal end of the pore helix in the hERG model. In addition, a diffuse interface involving hydrophobic residues on S4 (voltage sensor) and pore domain S5 of an adjacent subunit was stable during 0.5 μs of simulation. To assess the ability of the model to give insight into the effects of channel mutation we simulated a hERG mutant that contains a Leu to Pro substitution in the voltage sensor S4 helical segment (hERG L532P). Consistent with the retention of gated K(+) conductance, the L532P mutation was accommodated in the S4 helix with little disruption of helical structure. The mutation reduced the extent of interaction across the S4-S5 interface, suggesting a structural basis for the greatly enhanced deactivation rate in hERG L532P. The study indicates that pairwise comparison of wild-type and mutated channel models is a useful approach to interpreting functional data where uncertainty in model structures exist.

Differential hERG ion channel activity of ultrasmall gold nanoparticles

Understanding the mechanism of toxicity of nanomaterials remains a challenge with respect to both mechanisms involved and product regulation. Here we show toxicity of ultrasmall gold nanoparticles (AuNPs). Depending on the ligand chemistry, 1.4-nm-diameter AuNPs failed electrophysiology-based safety testing using human embryonic kidney cell line 293 cells expressing human ether-á-go-go-Related gene (hERG), a Food and Drug Administration-established drug safety test. In patch-clamp experiments, phosphine-stabilized AuNPs irreversibly blocked hERG channels, whereas thiol-stabilized AuNPs of similar size had no effect in vitro, and neither particle blocked the channel in vivo. We conclude that safety regulations may need to be reevaluated and adapted to reflect the fact that the binding modality of surface functional groups becomes a relevant parameter for the design of nanoscale bioactive compounds.

ICA-105574 interacts with a common binding site to elicit opposite effects on inactivation gating of EAG and ERG potassium channels

Rapid and voltage-dependent inactivation greatly attenuates outward currents in ether-a-go-go-related gene (ERG) K(+) channels. In contrast, inactivation of related ether-a-go-go (EAG) K(+) channels is very slow and minimally reduces outward currents. ICA-105574 (ICA, or 3-nitro-N-[4-phenoxyphenyl]-benzamide) has opposite effects on inactivation of these two channel types. Although ICA greatly attenuates ERG inactivation by shifting its voltage dependence to more positive potentials, it enhances the rate and extent of EAG inactivation without altering its voltage dependence. Here, we investigate whether the inverse functional response to ICA in EAG and ERG channels is related to differences in ICA binding site or to intrinsic mechanisms of inactivation. Molecular modeling coupled with site-directed mutagenesis suggests that ICA binds in a channel-specific orientation to a hydrophobic pocket bounded by the S5/pore helix/S6 of one subunit and S6 of an adjacent subunit. ICA is a mixed agonist of mutant EAG and EAG/ERG chimera channels that inactivate by a combination of slow and fast mechanisms. With the exception of three residues, the specific amino acids that form the putative binding pocket for ICA in ERG are conserved in EAG. Mutations introduced into EAG to replicate the ICA binding site in ERG did not alter the functional response to ICA. Together these findings suggest that ICA binds to the same site in EAG and ERG channels to elicit opposite functional effects. The resultant agonist or antagonist activity is determined solely by channel-specific differences in the mechanisms of inactivation gating.

Pore helices play a dynamic role as integrators of domain motion during Kv11.1 channel inactivation gating

Proteins that form ion-selective pores in the membrane of cells are integral to many rapid signaling processes, including regulating the rhythm of the heartbeat. In potassium channels, the selectivity filter is critical for both endowing an exquisite selectivity for potassium ions, as well as for controlling the flow of ions through the pore. Subtle rearrangements in the complex hydrogen-bond network that link the selectivity filter to the surrounding pore helices differentiate conducting (open) from nonconducting (inactivated) conformations of the channel. Recent studies suggest that beyond the selectivity filter, inactivation involves widespread rearrangements of the channel protein. Here, we use rate equilibrium free energy relationship analysis to probe the structural changes that occur during selectivity filter gating in Kv11.1 channels, at near atomic resolution. We show that the pore helix plays a crucial dynamic role as a bidirectional interface during selectivity filter gating. We also define the molecular bases of the energetic coupling between the pore helix and outer helix of the pore domain that occurs early in the transition from open to inactivated states, as well as the coupling between the pore helix and inner helix late in the transition. Our data demonstrate that the pore helices are more than just static structural elements supporting the integrity of the selectivity filter; instead they play a crucial dynamic role during selectivity filter gating.

A molecular switch driving inactivation in the cardiac K+ channel HERG

K⁺ channels control transmembrane action potentials by gating open or closed in response to external stimuli. Inactivation gating, involving a conformational change at the K⁺ selectivity filter, has recently been recognized as a major K⁺ channel regulatory mechanism. In the K⁺ channel hERG, inactivation controls the length of the human cardiac action potential. Mutations impairing hERG inactivation cause life-threatening cardiac arrhythmia, which also occur as undesired side effects of drugs. In this paper, we report atomistic molecular dynamics simulations, complemented by mutational and electrophysiological studies, which suggest that the selectivity filter adopts a collapsed conformation in the inactivated state of hERG. The selectivity filter is gated by an intricate hydrogen bond network around residues S620 and N629. Mutations of this hydrogen bond network are shown to cause inactivation deficiency in electrophysiological measurements. In addition, drug-related conformational changes around the central cavity and pore helix provide a functional mechanism for newly discovered hERG activators.

hERG K+ Channels: Structure, Function, and Clinical Significance

The human ether-a-go-go related gene (hERG) encodes the pore-forming subunit of the rapid component of the delayed rectifier K+ channel, Kv11.1, which are expressed in the heart, various brain regions, smooth muscle cells, endocrine cells, and a wide range of tumor cell lines. However, it is the role that Kv11.1 channels play in the heart that has been best characterized, for two main reasons. First, it is the gene product involved in chromosome 7-associated long QT syndrome (LQTS), an inherited disorder associated with a markedly increased risk of ventricular arrhythmias and sudden cardiac death. Second, blockade of Kv11.1, by a wide range of prescription medications, causes drug-induced QT prolongation with an increase in risk of sudden cardiac arrest. In the first part of this review, the properties of Kv11.1 channels, including biogenesis, trafficking, gating, and pharmacology are discussed, while the second part focuses on the pathophysiology of Kv11.1 channels.

Molecular dynamics

Molecular dynamics (MD) simulation holds the promise of revealing the mechanisms of biological processes in their ultimate detail. It is carried out by computing the interaction forces acting on each atom and then propagating the velocities and positions of the atoms by numerical integration of Newton's equations of motion. In this review, we present an overview of how the MD simulation can be conducted to address computational toxicity problems. The study cases will cover a standard MD simulation performed to investigate the overall flexibility of a cytochrome P450 (CYP) enzyme and a set of more advanced MD simulations to examine the barrier to ion conduction in a human α7 nicotinic acetylcholine receptor (nAChR).

In silico analysis of conformational changes induced by mutation of aromatic binding residues: consequences for drug binding in the hERG K+ channel

Pharmacological inhibition of cardiac hERG K⁺ channels is associated with increased risk of lethal arrhythmias. Many drugs reduce hERG current by directly binding to the channel, thereby blocking ion conduction. Mutation of two aromatic residues (F656 and Y652) substantially decreases the potency of numerous structurally diverse compounds. Nevertheless, some drugs are only weakly affected by mutation Y652A. In this study we utilize molecular dynamics simulations and docking studies to analyze the different effects of mutation Y652A on a selected number of hERG blockers. MD simulations reveal conformational changes in the binding site induced by mutation Y652A. Loss of π-π-stacking between the two aromatic residues induces a conformational change of the F656 side chain from a cavity facing to cavity lining orientation. Docking studies and MD simulations qualitatively reproduce the diverse experimentally observed modulatory effects of mutation Y652A and provide a new structural interpretation for the sensitivity differences.

Molecular determinants for activation of human ether-à-go-go-related gene 1 potassium channels by 3-nitro-n-(4-phenoxyphenyl) benzamide

Human ether-à-go-go-related gene 1 (hERG1) channels mediate repolarization of cardiac action potentials. Inherited long QT syndrome (LQTS) caused by loss-of-function mutations, or unintended blockade of hERG1 channels by many drugs, can lead to severe arrhythmia and sudden death. Drugs that activate hERG1 are a novel pharmacological approach to treat LQTS. 3-Nitro-n-(4-phenoxyphenyl) benzamide [ICA-105574 (ICA)] has been discovered to activate hERG1 by strong attenuation of pore-type inactivation. Here, we used scanning mutagenesis of hERG1 to identify the molecular determinants of ICA action. Three mutations abolished the activator effects of 30 μM ICA, including L622C in the pore helix, F557L in the S5 segment, and Y652A in the S6 segment. One mutation in S6 (A653M) switched the activity of ICA from an activator to an inhibitor, revealing its partial agonist activity. This was confirmed by showing that the noninactivating mutant hERG1 channel (G628C/S631C) was inhibited by ICA and that the addition of the F557L mutation rendered the channel drug-insensitive. Simulated molecular docking of ICA to homology models of hERG1 corroborated the scanning mutagenesis findings. Together, our findings indicate that ICA is a mixed agonist of hERG1 channels. Activation or inhibition of currents is mediated by the same or overlapping binding site located in the pore module between two adjacent subunits of the homotetrameric channel.

Utility of protein structures in overcoming ADMET-related issues of drug-like compounds

The number of solved X-ray structures of proteins relevant for ADMET processes of drug molecules has increased remarkably over recent years. In principle, this development offers the possibility to complement the quantitative structure-property relationship (QSPR)-dominated repertoire of in silico ADMET methods with protein-structure-based approaches. However, the complex nature and the weak nonspecific ligand-binding properties of ADMET proteins take structural biology methods and current docking programs to the limit. In this review we discuss the utility of protein-structure-based design and docking approaches aimed at overcoming issues related to plasma protein binding, active transport via P-glycoprotein, hERG channel mediated cardiotoxicity and cytochrome P450 inhibition, metabolism and induction.