Correction: Greiner et al. Consecutive-Day Ventricular and Atrial Cardiomyocyte Isolations from the Same Heart: Shifting the Cost-Benefit Balance of Cardiac Primary Cell Research. Cells 2022, 11, 233.

In the original publication [...].

Probes for the heterogeneity of muscimol binding sites in rat brain.

Introduction: The plant-based alkaloid muscimol is a potent agonist of inhibitory GABAA-neurotransmitter receptors. GABAA receptors are a heterogeneous family of pentameric complexes, with 5 out of 19 subunits assembling around the central anion pore. Muscimol is considered to bind to all receptor subtypes at the orthosteric drug binding site at the ß+/α- interface. Recently, we observed that the antipsychotic drugs clozapine (CLZ), loxapine (LOX) and chlorpromazine (CPZ) although exerting functional inhibition on multiple GABAA receptor subtypes showed diverging results in displacing 3H-muscimol. While a complete displacement could be observed in hippocampal membranes by bicuculline (BIC), and no displacement with CPZ, the compounds CLZ and LOX competed partially. Non-sigmoidal, complex dose response curves were indicative of multiple sites. In the current study we now aimed to investigate more extensively this heterogeneity of bicuculline sensitive muscimol sites in rat brain. Methods: We tested membranes from four different brain regions (hippocampus, cerebellum, thalamus and striatum) and selected recombinantly expressed subunit combinations with displacement assays. 3H-muscimol displacement was tested with BIC, LOX, CLZ and CPZ. In silico ligand structural analysis and computational docking was performed. Results: We observed a unique pharmacology of each tested compound in the studied brain regions. Combining two of the tested ligands suggests that in striatum all CLZ sites are contained in the pool of LOX sites, while the CPZ sites may in part be non-overlapping with LOX sites. Experiments on recombinantly expressed receptors indicate, that BIC can displace 3H-muscimol from all tested receptors, while LOX and CLZ display different and variable competition indicative of multiple sites. Molecular docking produced structural correlates of the observed diversity of muscimol sites on the basis of bicuculline bound experimental structures. Discussion: These findings indicate that 3H-muscimol binding sites in rat brain are heterogeneous, with different populations of receptors, which are CPZ, LOX or CLZ sensitive or insensitive. These binding sites show a varying distribution in different rat brain regions. Molecular docking suggests that the so-called loop F region of α subunits drives the observed differences.

Synchronous force and Ca2+ measurements for repeated characterization of excitation-contraction coupling in human myocardium.

Dysfunctional Ca2+ signaling affects the myocardial systole and diastole, may trigger arrhythmia and cause transcriptomic and proteomic modifications in heart failure. Thus, synchronous real-time measurement of Ca2+ and force is essential to investigate the relationship between contractility and Ca2+ signaling and the alteration of excitation-contraction coupling (ECC) in human failing myocardium. Here, we present a method for synchronized acquisition of intracellular Ca2+ and contraction force in long-term cultivated slices of human failing myocardium. Synchronous time series of contraction force and intracellular Ca2+ were used to calculate force-calcium loops and to analyze the dynamic alterations of ECC in response to various pacing frequencies, post-pause potentiation, high mechanical preload and pharmacological interventions in human failing myocardium. We provide an approach to simultaneously and repeatedly investigate alterations of contractility and Ca2+ signals in long-term cultured myocardium, which will allow detecting the effects of electrophysiological or pharmacological interventions on human myocardial ECC.

Active Learning Approach for Guiding Site-of-Metabolism Measurement and Annotation.

The ability to determine and predict metabolically labile atom positions in a molecule (also called "sites of metabolism" or "SoMs") is of high interest to the design and optimization of bioactive compounds, such as drugs, agrochemicals, and cosmetics. In recent years, several in silico models for SoM prediction have become available, many of which include a machine-learning component. The bottleneck in advancing these approaches is the coverage of distinct atom environments and rare and complex biotransformation events with high-quality experimental data. Pharmaceutical companies typically have measured metabolism data available for several hundred to several thousand compounds. However, even for metabolism experts, interpreting these data and assigning SoMs are challenging and time-consuming. Therefore, a significant proportion of the potential of the existing metabolism data, particularly in machine learning, remains dormant. Here, we report on the development and validation of an active learning approach that identifies the most informative atoms across molecular data sets for SoM annotation. The active learning approach, built on a highly efficient reimplementation of SoM predictor FAME 3, enables experts to prioritize their SoM experimental measurements and annotation efforts on the most rewarding atom environments. We show that this active learning approach yields competitive SoM predictors while requiring the annotation of only 20% of the atom positions required by FAME 3. The source code of the approach presented in this work is publicly available.

Contractility measurements for cardiotoxicity screening with ventricular myocardial slices of pigs.

AIMS: Cardiotoxicity is one major reason why drugs do not enter or are withdrawn from the market. Thus, approaches are required to predict cardiotoxicity with high specificity and sensitivity. Ideally, such methods should be performed within intact cardiac tissue with high relevance for humans and detect acute and chronic side effects on electrophysiological behaviour, contractility, and tissue structure in an unbiased manner. Herein, we evaluate healthy pig myocardial slices and biomimetic cultivation setups (BMCS) as a new cardiotoxicity screening approach. METHODS AND RESULTS: Pig left ventricular samples were cut into slices and spanned into BMCS with continuous electrical pacing and online force recording. Automated stimulation protocols were established to determine the force-frequency relationship (FFR), frequency dependence of contraction duration, effective refractory period (ERP), and pacing threshold. Slices generated 1.3 ± 0.14 mN/mm2 force at 0.5 Hz electrical pacing and showed a positive FFR and a shortening of contraction duration with increasing pacing rates. Approximately 62% of slices were able to contract for at least 6 days while showing stable ERP, contraction duration-frequency relationship, and preserved cardiac structure confirmed by confocal imaging and X-ray diffraction analysis. We used specific blockers of the most important cardiac ion channels to determine which analysis parameters are influenced. To validate our approach, we tested five drug candidates selected from the Comprehensive in vitro Proarrhythmia Assay list as well as acetylsalicylic acid and DMSO as controls in a blinded manner in three independent laboratories. We were able to detect all arrhythmic drugs and their respective mode of action on cardiac tissue including inhibition of Na+, Ca2+, and hERG channels as well as Na+/Ca2+ exchanger. CONCLUSION: We systematically evaluate this approach for cardiotoxicity screening, which is of high relevance for humans and can be upscaled to medium-throughput screening. Thus, our approach will improve the predictive value and efficiency of preclinical cardiotoxicity screening.

Ryanodine Receptor Staining Identifies Viable Cardiomyocytes in Human and Rabbit Cardiac Tissue Slices.

In terms of preserving multicellularity and myocardial function in vitro, the cultivation of beating myocardial slices is an emerging technique in basic and translational cardiac research. It can be used, for example, for drug screening or to study pathomechanisms. Here, we describe staining for viable cardiomyocytes based on the immunofluorescence of ryanodine receptors (RyRs) in human and rabbit myocardial slices. Biomimetic chambers were used for culture and measurements of contractile force. Fixable fluorophore-conjugated dextran, entering cells with a permeable membrane, was used for death staining. RyRs, nuclei and the extracellular matrix, including the t-system, were additionally stained and analyzed by confocal microscopy and image processing. We found the mutual exclusion of the RyR and dextran signals in cultivated slices. T-System density and nucleus size were reduced in RyR-negative/dextran-positive myocytes. The fraction of RyR-positive myocytes and pixels correlated with the contractile force. In RyR-positive/dextran-positive myocytes, we found irregular RyR clusters and SERCA distribution patterns, confirmed by an altered power spectrum. We conclude that RyR immunofluorescence indicates viable cardiomyocytes in vibratome-cut myocardial slices, facilitating the detection and differential structural analysis of living vs. dead or dying myocytes. We suggest the loss of sarcoplasmic reticulum integrity as an early event during cardiomyocyte death.

High-Quality Conformer Generation with CONFORGE: Algorithm and Performance Assessment.

Knowledge of the putative bound-state conformation of a molecule is an essential prerequisite for the successful application of many computer-aided drug design methods that aim to assess or predict its capability to bind to a particular target receptor. An established approach to predict bioactive conformers in the absence of receptor structure information is to sample the low-energy conformational space of the investigated molecules and derive representative conformer ensembles that can be expected to comprise members closely resembling possible bound-state ligand conformations. The high relevance of such conformer generation functionality led to the development of a wide panel of dedicated commercial and open-source software tools throughout the last decades. Several published benchmarking studies have shown that open-source tools usually lag behind their commercial competitors in many key aspects. In this work, we introduce the open-source conformer ensemble generator CONFORGE, which aims at delivering state-of-the-art performance for all types of organic molecules in drug-like chemical space. The ability of CONFORGE and several well-known commercial and open-source conformer ensemble generators to reproduce experimental 3D structures as well as their computational efficiency and robustness has been assessed thoroughly for both typical drug-like molecules and macrocyclic structures. For small molecules, CONFORGE clearly outperformed all other tested open-source conformer generators and performed at least equally well as the evaluated commercial generators in terms of both processing speed and accuracy. In the case of macrocyclic structures, CONFORGE achieved the best average accuracy among all benchmarked generators, with RDKit's generator coming close in second place.

Navigating the complex landscape of benzodiazepine- and Z-drug diversity: insights from comprehensive FDA adverse event reporting system analysis and beyond.

Introduction: Medications which target benzodiazepine (BZD) binding sites of GABAA receptors (GABAARs) have been in widespread use since the nineteen-sixties. They carry labels as anxiolytics, hypnotics or antiepileptics. All benzodiazepines and several nonbenzodiazepine Z-drugs share high affinity binding sites on certain subtypes of GABAA receptors, from which they can be displaced by the clinically used antagonist flumazenil. Additional binding sites exist and overlap in part with sites used by some general anaesthetics and barbiturates. Despite substantial preclinical efforts, it remains unclear which receptor subtypes and ligand features mediate individual drug effects. There is a paucity of literature comparing clinically observed adverse effect liabilities across substances in methodologically coherent ways. Methods: In order to examine heterogeneity in clinical outcome, we screened the publicly available U.S. FDA adverse event reporting system (FAERS) database for reports of individual compounds and analyzed them for each sex individually with the use of disproportionality analysis. The complementary use of physico-chemical descriptors provides a molecular basis for the analysis of clinical observations of wanted and unwanted drug effects. Results and Discussion: We found a multifaceted FAERS picture, and suggest that more thorough clinical and pharmacoepidemiologic investigations of the heterogenous side effect profiles for benzodiazepines and Z-drugs are needed. This may lead to more differentiated safety profiles and prescription practice for particular compounds, which in turn could potentially ease side effect burden in everyday clinical practice considerably. From both preclinical literature and pharmacovigilance data, there is converging evidence that this very large class of psychoactive molecules displays a broad range of distinctive unwanted effect profiles - too broad to be explained by the four canonical, so-called "diazepam-sensitive high-affinity interaction sites". The substance-specific signatures of compound effects may partly be mediated by phenomena such as occupancy of additional binding sites, and/or synergistic interactions with endogenous substances like steroids and endocannabinoids. These in turn drive the wanted and unwanted effects and sex differences of individual compounds.

Corrigendum: long-term cultivation of human atrial myocardium.

[This corrects the article DOI: 10.3389/fphys.2022.839139.].

GABAA receptor-mediated seizure liabilities: a mixed-methods screening approach.

GABAA receptors, members of the pentameric ligand-gated ion channel superfamily, are widely expressed in the central nervous system and mediate a broad range of pharmaco-toxicological effects including bidirectional changes to seizure threshold. Thus, detection of GABAA receptor-mediated seizure liabilities is a big, partly unmet need in early preclinical drug development. This is in part due to the plethora of allosteric binding sites that are present on different subtypes of GABAA receptors and the critical lack of screening methods that detect interactions with any of these sites. To improve in silico screening methods, we assembled an inventory of allosteric binding sites based on structural data. Pharmacophore models representing several of the binding sites were constructed. These models from the NeuroDeRisk IL Profiler were used for in silico screening of a compiled collection of drugs with known GABAA receptor interactions to generate testable hypotheses. Amoxapine was one of the hits identified and subjected to an array of in vitro assays to examine molecular and cellular effects on neuronal excitability and in vivo locomotor pattern changes in zebrafish larvae. An additional level of analysis for our compound collection is provided by pharmacovigilance alerts using FAERS data. Inspired by the Adverse Outcome Pathway framework, we postulate several candidate pathways leading from specific binding sites to acute seizure induction. The whole workflow can be utilized for any compound collection and should inform about GABAA receptor-mediated seizure risks more comprehensively compared to standard displacement screens, as it rests chiefly on functional data.

Temporal localized states and square-waves in semiconductor micro-resonators with strong time-delayed feedback.

In this paper, we study the dynamics of a vertically emitting micro-cavity operated in the Gires-Tournois regime that contains a semiconductor quantum-well and that is subjected to strong time-delayed optical feedback and detuned optical injection. Using a first principle time-delay model for the optical response, we disclose sets of multistable dark and bright temporal localized states coexisting on their respective bistable homogeneous backgrounds. In the case of anti-resonant optical feedback, we identify square-waves with a period of twice the round-trip in the external cavity. Finally, we perform a multiple time scale analysis in the good cavity limit. The resulting normal form is in good agreement with the original time-delayed model.

A new set of KNIME nodes implementing the QPhAR algorithm.

Dissemination of novel research methods, especially in the form of chemoinformatics software, depends heavily on their ease of applicability for non-expert users with only a little or no programming skills and knowledge in computer science. Visual programming has become widely popular over the last few years, also enabling researchers without in-depth programming skills to develop tailored data processing pipelines using elements from a repository of predefined standard procedures. In this work, we present the development of a set of nodes for the KNIME platform implementing the QPhAR algorithm. We show how the developed KNIME nodes can be included in a typical workflow for biological activity prediction. Furthermore, we present best-practice guidelines that should be followed to obtain high-quality QPhAR models. Finally, we show a typical workflow to train and optimise a QPhAR model in KNIME for a set of given input compounds, applying the discussed best practices.

Apo2ph4: A Versatile Workflow for the Generation of Receptor-based Pharmacophore Models for Virtual Screening.

Pharmacophore models are widely used as efficient virtual screening (VS) filters for the target-directed enrichment of large compound libraries. However, the generation of pharmacophore models that have the power to discriminate between active and inactive molecules traditionally requires structural information about ligand-target complexes or at the very least knowledge of one active ligand. The fact that the discovery of the first known active ligand of a newly investigated target represents a major hurdle at the beginning of every drug discovery project underscores the need for methods that are able to derive high-quality pharmacophore models even without the prior knowledge of any active ligand structures. In this work, we introduce a novel workflow, called apo2ph4, that enables the rapid derivation of pharmacophore models solely from the three-dimensional structure of the target receptor. The utility of this workflow is demonstrated retrospectively for the generation of a pharmacophore model for the M2 muscarinic acetylcholine receptor. Furthermore, in order to show the general applicability of apo2ph4, the workflow was employed for all 15 targets of the recently published LIT-PCBA dataset. Pharmacophore-based VS runs using the apo2ph4-derived models achieved a significant enrichment of actives for 13 targets. In the last presented example, a pharmacophore model derived from the etomidate site of the α1ß2γ2 GABAA receptor was used in VS campaigns. Subsequent in vitro testing of selected hits revealed that 19 out of 20 (95%) tested compounds were able to significantly enhance GABA currents, which impressively demonstrates the applicability of apo2ph4 for real-world drug design projects.

Novel alpha6 preferring GABA-A receptor ligands based on loreclezole.

The family of GABA-A receptors contains nineteen mammalian subunits from which pentameric, GABA gated anion channels are assembled. The subunit encoded by the GABRA6 gene is highly expressed in the cerebellum and the receptors to which it contributes have recently been demonstrated to be a promising candidate as a novel drug target. Here we examined a series of loreclezole derivatives for potentially selective action at α6ß3γ2 receptors with the help of computational methods and functional testing with the two-electrode voltage clamp technique. The synthetic routes to some previously published ligands were improved, and a new derivative was synthesized based on computational docking results. This new loreclezole derivative, [3-(2-chloro-4-methylphenyl)-3-methylbutanenitrile (40)], was shown to display stronger modulatory action in concatenated α6ß3γ2 receptors compared to their α1ß3γ2 counterpart. The hypothetical bound state structure provides valuable guidance for future design of selective therapeutics.

Square-wave generation in vertical external-cavity Kerr-Gires-Tournois interferometers.

We study theoretically the mechanisms of square-wave (SW) formation in vertical external-cavity Kerr-Gires-Tournois interferometers in the presence of anti-resonant injection. We provide simple analytical approximations for their plateau intensities and for the conditions of their emergence. We demonstrate that SWs may appear via a homoclinic snaking scenario, leading to the formation of complex-shaped multistable SW solutions. The resulting SWs can host localized structures and robust bound states.

Applications of the Novel Quantitative Pharmacophore Activity Relationship Method QPhAR in Virtual Screening and Lead-Optimisation.

Pharmacophores are an established concept for the modelling of ligand-receptor interactions based on the abstract representations of stereoelectronic molecular features. They became widely popular as filters for the fast virtual screening of large compound libraries. A lot of effort has been put into the development of sophisticated algorithms and strategies to increase the computational efficiency of the screening process. However, hardly any focus has been put on the development of automated procedures that optimise pharmacophores towards higher discriminatory power, which still has to be done manually by a human expert. In the age of machine learning, the researcher has become the decision-maker at the top level, outsourcing analysis tasks and recurrent work to advanced algorithms and automation workflows. Here, we propose an algorithm for the automated selection of features driving pharmacophore model quality using SAR information extracted from validated QPhAR models. By integrating the developed method into an end-to-end workflow, we present a fully automated method that is able to derive best-quality pharmacophores from a given input dataset. Finally, we show how the QPhAR-generated models can be used to guide the researcher with insights regarding (un-)favourable interactions for compounds of interest.

Preparation of Human Myocardial Tissue for Long-Term Cultivation.

Cardiomyocyte cultivation has seen a vast number of developments, ranging from two-dimensional (2D) cell cultivation to iPSC derived organoids. In 2019, an ex vivo way to cultivate myocardial slices obtained from human heart samples was demonstrated, while approaching in vivo condition of myocardial contraction. These samples originate mostly from heart transplantations or left-ventricular assist device placements. Using a vibratome and a specially developed cultivation system, 300 µm thick slices are placed between a fixed and a spring wire, allowing for stable and reproducible cultivation for several weeks. During cultivation, the slices are continuously stimulated according to individual settings. Contractions can be displayed and recorded in real-time, and pharmacological agents can be readily applied. User-defined stimulation protocols can be scheduled and performed to assess vital contraction parameters like post-pause-potentiation, stimulation threshold, force-frequency relation, and refractory period. Furthermore, the system enables a variable pre- and afterload setting for a more physiological cultivation. Here, we present a step-by-step guide on how to generate a successful long-term cultivation of human left ventricular myocardial slices, using a commercial biomimetic cultivation solution.

A normal form for frequency combs and localized states in Kerr-Gires-Tournois interferometers.

We elucidate the mechanisms that underlay the formation of temporal localized states and frequency combs in vertical external-cavity Kerr-Gires-Tournois interferometers. We reduce our first-principles model based upon delay algebraic equations to a minimal pattern formation scenario. It consists in a real cubic Ginzburg-Landau equation modified by high-order effects such as third-order dispersion and nonlinear drift, which are responsible for generating localized states via the locking of domain walls connecting the high and low intensity levels of the injected micro-cavity. We interpret the effective parameters of the normal form in relation with the configuration of the optical setup. Comparing the two models, we observe an excellent agreement close to the onset of bistability.

Molecular Mingling: Multimodal Predictions of Ligand Promiscuity in Pentameric Ligand-Gated Ion Channels.

Background: Human pentameric ligand-gated ion channels (pLGICs) comprise nicotinic acetylcholine receptors (nAChRs), 5-hydroxytryptamine type 3 receptors (5-HT3Rs), zinc-activated channels (ZAC), γ-aminobutyric acid type A receptors (GABAARs) and glycine receptors (GlyRs). They are recognized therapeutic targets of some of the most prescribed drugs like general anesthetics, anxiolytics, smoking cessation aids, antiemetics and many more. Currently, approximately 100 experimental structures of pLGICs with ligands bound exist in the protein data bank (PDB). These atomic-level 3D structures enable the generation of a comprehensive binding site inventory for the superfamily and the in silico prediction of binding site properties. Methods: A panel of high throughput in silico methods including pharmacophore screening, conformation analysis and descriptor calculation was applied to a selection of allosteric binding sites for which in vitro screens are lacking. Variant abundance near binding site forming regions and computational docking complement the approach. Results: The structural data reflects known and novel binding sites, some of which may be unique to individual receptors, while others are broadly conserved. The membrane spanning domain, comprising four highly conserved segments, contains ligand interaction sites for which in vitro assays suitable for high throughput screenings are critically lacking. This is also the case for structurally more variable novel sites in the extracellular domain. Our computational results suggest that the phytocannabinoid Δ9-tetrahydrocannabinol (Δ9-THC) can utilize multiple pockets which are likely to exist on most superfamily members. Conclusion: With this study, we explore the potential for polypharmacology among pLGICs. Our data suggest that ligands can display two forms of promiscuity to an extent greater than what has been realized: 1) Ligands can interact with homologous sites in many members of the superfamily, which bears toxicological relevance. 2) Multiple pockets in distinct localizations of individual receptor subtypes share common ligands, which counteracts efforts to develop selective agents. Moreover, conformational states need to be considered for in silico drug screening, as certain binding sites display considerable flexibility. In total, this work contributes to a better understanding of polypharmacology across pLGICs and provides a basis for improved structure guided in silico drug development and drug derisking.

Confocal microscopy-based estimation of intracellular conductivities in myocardium for modeling of the normal and infarcted heart.

Ventricular arrhythmias are the leading cause of mortality in patients with ischemic heart diseases, such as myocardial infarction (MI). Computational simulation of cardiac electrophysiology provides insights into these arrhythmias and their treatment. However, only sparse information is available on crucial model parameters, for instance, the anisotropic intracellular electrical conductivities. Here, we introduced an approach to estimate these conductivities in normal and MI hearts. We processed and analyzed images from confocal microscopy of left ventricular tissue of a rabbit MI model to generate 3D reconstructions. We derived tissue features including the volume fraction of myocytes (Vmyo), gap junctions-containing voxels (Vgj), and fibrosis (Vfibrosis). We generated models of the intracellular space and intercellular coupling. Applying numerical methods for solving Poisson's equation for stationary electrical currents, we calculated normal (σmyo,n), longitudinal (σmyo,l), and transverse (σmyo,t) intracellular conductivities. Using linear regression analysis, we assessed relationships of conductivities to tissue features. Vgj and Vmyo were reduced in MI vs. control, but Vfibrosis was increased. Both σmyo,l and σmyo,n were lower in MI than in control. Differences of σmyo,t between control and MI were not significant. We found strong positive relationships of σmyo,l with Vmyo and Vgj, and a strong negative relationship with Vfibrosis. The relationships of σmyo,n with these tissue features were similar but less pronounced. Our study provides quantitative insights into the intracellular conductivities in the normal and MI heart. We suggest that our study establishes a framework for the estimation of intracellular electrical conductivities of myocardium with various pathologies.