Identification of “toxicophoric” features for predicting drug-induced QT interval prolongation

Support Vector Machine model for hERG inhibitory activities based on the integrated hERG database using descriptor selection by NSGA-II

Assessing the hERG liability in the early stages of drug discovery programs is important. The recent increase of hERG-related information in public databases enabled various successful applications of machine learning techniques to predict hERG inhibition. However, most of these researches constructed the datasets from only one database, limiting the predictability and scope of the models. In this study, a hERG classification model was constructed using the largest dataset for hERG inhibition built by integrating multiple databases. The integrated dataset consisted of more than 291,000 structurally diverse compounds derived from ChEMBL, GOSTAR, PubChem, and hERGCentral. The prediction model was built by support vector machine (SVM) with descriptor selection based on Non-dominated Sorting Genetic Algorithm-II (NSGA-II) to optimize the descriptor set for maximum prediction performance with the minimal number of descriptors. The SVM classification model using 72 selected descriptors and ECFP_4 structural fingerprints recorded kappa statistics of 0.733 and accuracy of 0.984 for the test set, substantially outperforming the prediction performance of the current commercial applications for hERG prediction. Finally, the applicability domain of the prediction model was assessed based on the molecular similarity between the training set and test set compounds.

Experimentally Validated Pharmacoinformatics Approach to Predict hERG Inhibition Potential of New Chemical Entities

The hERG (human ether-a-go-go-related gene) encoded potassium ion (K⁺) channel plays a major role in cardiac repolarization. Drug-induced blockade of hERG has been a major cause of potentially lethal ventricular tachycardia termed Torsades de Pointes (TdPs). Therefore, we presented a pharmacoinformatics strategy using combined ligand and structure based models for the prediction of hERG inhibition potential (IC₅₀) of new chemical entities (NCEs) during early stages of drug design and development. Integrated GRid-INdependent Descriptor (GRIND) models, and lipophilic efficiency (LipE), ligand efficiency (LE) guided template selection for the structure based pharmacophore models have been used for virtual screening and subsequent hERG activity (pIC₅₀) prediction of identified hits. Finally selected two hits were experimentally evaluated for hERG inhibition potential (pIC₅₀) using whole cell patch clamp assay. Overall, our results demonstrate a difference of less than ±1.6 log unit between experimentally determined and predicted hERG inhibition potential (IC₅₀) of the selected hits. This revealed predictive ability and robustness of our models and could help in correctly rank the potency order (lower μM to higher nM range) against hERG.

Discovery of novel 5-oxa-2,6-diazaspiro[3.4]oct-6-ene derivatives as potent, selective, and orally available somatostatin receptor subtype 5 (SSTR5) antagonists for treatment of type 2 diabetes mellitus

Somatostatin receptor subtype 5 (SSTR5) has emerged as a novel attractive drug target for type 2 diabetes mellitus. Starting from N-benzyl azetidine derivatives 1 and 2 as in-house hit compounds, we explored the introduction of a carboxyl group into the terminal benzene of 1 to enhance SSTR5 antagonistic activity by the combination of the substituents at the 3-position of the isoxazoline. Incorporation of a carboxyl group at the 4-position of the benzene ring resulted in a significant enhancement in potency, however, the 4-benzoic acid derivative 10c exhibited moderate human ether-a-go-go related gene (hERG) inhibitory activity. A subsequent optimization study revealed that replacement of the 4-benzoic acid with an isonipecotic acid dramatically reduced hERG inhibition (5.6% inhibition at 30μM) by eliminating π-related interaction with hERG K⁺ channel, which resulted in the identification of 1-(2-((2,6-diethoxy-4'-fluorobiphenyl-4-yl)methyl)-5-oxa-2,6-diazaspiro[3.4]oct-6-en-7-yl)piperidin-4-carboxylic acid 25a (hSSTR5/mSSTR5 IC₅₀=9.6/57nM). Oral administration of 25a in high-fat diet fed C57BL/6J mice augmented insulin secretion in a glucose-dependent manner and lowered blood glucose concentration.

hERG Blockade by Iboga Alkaloids

The iboga alkaloids are a class of naturally occurring and synthetic compounds, some of which modify drug self-administration and withdrawal in humans and preclinical models. Ibogaine, the prototypic iboga alkaloid that is utilized clinically to treat addictions, has been associated with QT prolongation, torsades de pointes and fatalities. hERG blockade as IKr was measured using the whole-cell patch clamp technique in HEK 293 cells. This yielded the following IC50 values: ibogaine manufactured by semisynthesis via voacangine (4.09 ± 0.69 µM) or by extraction from T. iboga (3.53 ± 0.16 µM); ibogaine's principal metabolite noribogaine (2.86 ± 0.68 µM); and voacangine (2.25 ± 0.34 µM). In contrast, the IC50 of 18-methoxycoronaridine, a product of rational synthesis and current focus of drug development was >50 µM. hERG blockade was voltage dependent for all of the compounds, consistent with low-affinity blockade. hERG channel binding affinities (K i) for the entire set of compounds, including 18-MC, ranged from 0.71 to 3.89 µM, suggesting that 18-MC binds to the hERG channel with affinity similar to the other compounds, but the interaction produces substantially less hERG blockade. In view of the extended half-life of noribogaine, these results may relate to observations of persistent QT prolongation and cardiac arrhythmia at delayed intervals of days following ibogaine ingestion. The apparent structure-activity relationships regarding positions of substitutions on the ibogamine skeleton suggest that the iboga alkaloids might provide an informative paradigm for investigation of the structural biology of the hERG channel.

Discovery and SAR of N-(1-((substituted piperidin-4-yl)methyl)-3-methoxypiperidin-4-yl)-2-methoxybenzamide derivatives: 5-Hydroxytryptamine receptor 4 agonist as a potent prokinetic agent

A series of novel benzamide derivatives, altering the 4-fluorophenylalkyl moiety in cisapride, were synthesized as 5-HT4 receptor agonists, and SAR of these analogs was examined on in vitro and in vivo prokinetic activities. These compounds were synthesized for high 5-HT4 receptor binding affinities and low hERG affinities. Several types of analogs were obtained and screened for 5-HT4 binding, hERG blocking, agonism, and gastric emptying assessment. Among the analogues, compound 23g showed promising results compared with the other analogs with respect to gastric emptying rates in rats. Therefore, we suggest that it may be a clinical candidate for the development of a potent prokinetic agent to treat GI disorders.

Removal of human ether-à-go-go related gene (hERG) K+ channel affinity through rigidity: a case of clofilium analogues

Cardiotoxicity is a side effect that plagues modern drug design and is very often due to the off-target blockade of the human ether-à-go-go related gene (hERG) potassium channel. To better understand the structural determinants of this blockade, we designed and synthesized a series of 40 derivatives of clofilium, a class III antiarrhythmic agent. These were evaluated in radioligand binding and patch-clamp assays to establish structure-affinity relationships (SAR) for this potassium channel. Efforts were especially focused on studying the influence of the structural rigidity and the nature of the linkers composing the clofilium scaffold. It was shown that introducing triple bonds and oxygen atoms in the n-butyl linker of the molecule greatly reduced affinity without significantly modifying the pKa of the essential basic nitrogen. These findings could prove useful in the first stages of drug discovery as a systematic way of reducing the risk of hERG K(+) channel blockade-induced cardiotoxicity.

Combining structure- and ligand-based approaches for studies of interactions between different conformations of the hERG K+ channel pore and known ligands

Drug-induced insurgence of cardiotoxic effects signaled by the prolongation of the QT interval in the electrocardiogram, has the potential to evolve into a characteristic arrhythmic event named Torsade de Pointes (TdP). Although several different mechanisms can theoretically lead to prolonged QT interval, most of drugs showing this side effect, prolong the cardiac repolarization time through the inhibition of the rapid component of the delayed repolarizing current (IKr) which in humans is carried by a K(+) channel protein encoded by hERG. In this study, four 3D-models, representing different conformational states of hERG K(+) channel, were built by a homology-based technique. A dataset of 59 compounds was collected from the literature and rationally selected according to the availability of IC50 values derived from whole-cell patch clamp performed at 37 °C on HEK cells. Molecular docking was carried out on each one of the four conformations of the channel, hundreds of docking-based molecular descriptors were obtained and used, together with other 2D and 3D molecular descriptors, to develop QSAR models. The statistical parameters describing the accordance between predicted and experimental data and the interpretation of the QSAR models enabled us to assess the reliability of the four 3D-models of the channel pore, thus allowing to look in more depth at binding modes and key features of the interactions occurring between the hERG K(+) channel and ligands endowed of blocking activity.

A simple approach discriminating cardio-safe drugs from toxic ones

More than 130 FDA-approved drugs have been identified for now to prolong the QT interval and possibly lead to sudden cardiac death. Due to their toxic effect, some of these drugs have been withdrawn from the pharmaceutical market. In this study, we have formulated few rules to assess the ability to prolong QT interval and thereby discriminate between cardiotoxic and -safe drugs. These rules have clearly determined that cardio-toxic drugs are more likely to obey Lipinski rule of 5 and Oprea lead-like rule. Moreover, the cardio-toxic drugs have been found to have in common values of -0.5 to 6.5 log P, 1-5 nitrogen atoms, up to 4 oxygen atoms, 5-27 hydrophobic atoms, and 15-53 single bonds. Matthews Correlation Coefficient with the value of 0.6 was also attained and nearly 96% of the cardio-toxic drugs were successfully covered. Thus, despite the simplicity of this methodology, we have obtained interesting and informative results. The proposed set of these simple rules could be employed to infer cardio-toxicity or -safety for current and potential drugs. The present study will have important impact on decision making in the fields of drug development, molecule screening in biological assays, and other applications as well.