The hERG K+ channel: target and antitarget strategies in drug development

Toxicity of ACP-105: a substance used as doping in sports: application of in silico methods for prediction of selected toxicological endpoints

ACP-105 is a novel non-steroidal Selective Androgen Receptor Modulator (SARM) used by athletes. Its action aims to increase muscle mass and is one of the options in testosterone replacement therapy. Its safety profile remains insufficiently explored, particularly regarding its toxicity in humans. The lack of information about the studied compound in the World Anti-Doping Agency (WADA) became the purpose of this study. Given the increasing use of such compounds in sports, a deeper understanding of their biological risks is crucial. This study not only fills the gap in available information but also contributes to the growing body of research on SARMs, providing insights into their potential hazards and guiding future investigations into their safety. This work aimed to use various in silico techniques to predict the toxicity of ACP-105, including acute toxicity, effects on internal organs, genotoxicity based on the Ames test, eye and skin irritation, and cardiotoxicity by testing hERG inhibitors. A preliminary safety analysis of the compound was based on its chemical structure and interactions with biological targets using various in silico techniques: qualitative (STopTox, ADMETlab, admetSAR, ProTox 3.0, and Toxtree 3.1.0) and quantitative (TEST 5.1.2, Percepta, VEGA QSAR 1.2.3, and SL-Tox) to ensure that the prediction results are as accurate as possible.

ELISA protein detector (EPD): A Python-based ELISA tool for accurate low-level protein quantification

The enzyme-linked immunosorbent assay (ELISA) is a cornerstone technique for quantifying protein secretion in biological research. However, the built-in software provided by ELISA plate readers often struggles to accurately detect low-concentration proteins, particularly in the sub-nanogram/mL range, due to limitations in calibration curve fitting. We developed the ELISA Protein Detector (EPD) to overcome these challenges. This open-source Python-based software employs advanced optimization algorithms to enhance curve fitting precision, particularly at low detection thresholds." EPD features an intuitive user interface, requires minimal technical expertise, and supports robust cross-validation to enhance the reliability of ELISA data analysis. Tested on Windows systems, this tool provides a cost-effective and versatile solution for researchers, enabling accurate quantification of low-level protein concentrations and addressing the shortcomings of standard ELISA software in diverse biological and clinical applications.

Effects of plant extracts and derivatives on cardiac K+, Nav, and Cav channels: a review

Natural products (NPs) are endless sources of compounds for fighting against several pathologies. Many dysfunctions, including cardiovascular disorders, such as cardiac arrhythmias have their modes of action regulation of the concentration of electrolytes inside and outside the cell targeting ion channels. Here, we highlight plant extracts and secondary metabolites' effects on the treatment of related cardiac pathologies on hERG, Nav, and Cav of cardiomyocytes. The natural product's pharmacology of expressed receptors like alpha-adrenergic receptors causes an influx of Ca2+ ions through receptor-operated Ca2+ ion channels. We also examine the NPs associated with cardiac contractions such as myocardial contractility by reducing the L-type calcium current and decreasing the intracellular calcium transient, inhibiting the K+ induced contractions, decreasing amplitude of myocyte shortening and showed negative ionotropic and chronotropic effects due to decreasing cytosolic Ca2+. We examine whether the NPs block potassium channels, particular the hERG channel and regulatory effects on Nav1.7.

Profiling the antidiabetic potential of GC-MS compounds identified from the methanolic extract of Spilanthes filicaulis: experimental and computational insight

This study examines the nutritional composition, phytochemical profiling, and antioxidant, antidiabetic, and anti-inflammatory potential of a methanolic extract of Spilanthes filicaulis leaves (MESFL) via in vitro, ex vivo, and in silico studies. In vitro antioxidant, antidiabetic, and anti-inflammatory activities were examined. In the ex vivo study, liver tissues were subjected to FeSO4-induced oxidative damage and treated with varying concentrations of MESFL. MESFL contains a reasonable amount of nitrogen-free extract, moisture, ash content, crude protein, and fat, with a lesser amount of crude fiber. According to GC-MS analysis, MESFL contains ten compounds, the most abundant of which are 13-octadecenal and Ar-tumerone. In this study, MESFL demonstrated anti-inflammatory activities via membrane stabilizing properties, proteinase inhibition, and inhibition of protein denaturation (IC50 = 72.75 ± 11.06 µg/mL). MESFL also strongly inhibited both α-amylase (IC50 = 307.02 ± 4.25 µg/mL) and α-glucosidase (IC50 = 215.51 ± 0.47 µg/mL) activities. Our findings also showed that FeSO4-induced tissue damage decreased the levels of GSH, SOD, and CAT activities while increasing the levels of MDA. In contrast, treatment with MESFL helped to restore these parameters to near-normal levels, which signifies that MESFL has great potential to address complications from oxidative stress. Furthermore, the in silico interaction of the GCMS-identified phytochemicals with the active sites of α-amylase and α-glucosidase via molecular and ensembled-based docking displayed strong binding affinities of Ar-tumerone and 4-hydroxy-3-methylacetophenone to α-amylase and α-glucosidase, respectively. Taken together, the biological activities of MESFL might be a result of the effects of these secondary metabolites.Communicated by Ramaswamy H. Sarma.

hERG activators exhibit antitumor effects in breast cancer through calcineurin and β-catenin-mediated signaling pathways

Background

Breast cancer remains a leading cause of mortality among women worldwide, with existing therapeutic options often accompanied by significant side effects and a persistent risk of disease recurrence. This highlights the need for novel drug candidates with new mechanisms of action by targeting alternative signaling pathways. While hERG channel is notoriously regarded as an off-target due to drug-induced cardiotoxicity, its therapeutic potential as a drug target remains largely unexplored.

Methods

This study investigated the role of hERG in breast cancer progression and its impact on patient survival. The anti-proliferative, anti-migratory, anti-invasive and pro-apoptotic effects of hERG activators were evaluated using the Cell Counting Kit-8, wound healing assay, transwell assay and cell apoptosis assay, respectively. Western blotting, Ca2+ imaging and immunofluorescence assays were employed to study their antitumor mechanisms of actions.

Results

We identified two novel hERG activators, SDUY429 and SDUY436, which effectively inhibited the proliferation and migration of MDA-MB-231 and MCF-7 cells. In addition, SDUY436 demonstrated significant anti-invasive and pro-apoptotic effects in MDA-MB-231 cells. Mechanistically, the anti-proliferative activity of hERG activators were mediated through calcineurin activation via enhanced calcium ion influx, which facilitated the nuclear translocation of nuclear factor of activated T cells (NFAT) and upregulated p21Waf/Cip expression. Furthermore, both SDUY429 and SDUY436 remarkably suppressed the migration and invasion of MDA-MB-231 cells by downregulating the protein kinase B (AKT)/glycogen synthase kinase-3 beta (GSK3β)/β-catenin signaling pathway. The observed reduction in phospho-AKT-Ser473 (pAKTS473) expression resulted in the decreased levels of phospho-GSK3β-Ser9 (pGSK3βS9), thereby limiting the nuclear localization of β-catenin, which led to the inhibition of cell migration and invasion. Notably, combining SDUY429 or SDUY436 with the AKT inhibitor MK-2206 produced synergistic anti-proliferative effects.

Conclusion

These findings suggest that hERG activators hold promise as new potential therapeutic agents for the treatment of breast cancer, paving the way for future investigations into their clinical applications.

Multiscale mapping of transcriptomic signatures for cardiotoxic drugs

Drug-induced gene expression profiles can identify potential mechanisms of toxicity. We focus on obtaining signatures for cardiotoxicity of FDA-approved tyrosine kinase inhibitors (TKIs) in human induced-pluripotent-stem-cell-derived cardiomyocytes, using bulk transcriptomic profiles. We use singular value decomposition to identify drug-selective patterns across cell lines obtained from multiple healthy human subjects. Cellular pathways affected by cardiotoxic TKIs include energy metabolism, contractile, and extracellular matrix dynamics. Projecting these pathways to published single cell expression profiles indicates that TKI responses can be evoked in both cardiomyocytes and fibroblasts. Integration of transcriptomic outlier analysis with whole genomic sequencing of our six cell lines enables us to correctly reidentify a genomic variant causally linked to anthracycline-induced cardiotoxicity and predict genomic variants potentially associated with TKI-induced cardiotoxicity. We conclude that mRNA expression profiles when integrated with publicly available genomic, pathway, and single cell transcriptomic datasets, provide multiscale signatures for cardiotoxicity that could be used for drug development and patient stratification.

Concurrent Optimizations of Efficacy and Blood-Brain Barrier Permeability in New Macrocyclic LRRK2 Inhibitors for Potential Parkinson's Disease Therapeutics

The elevated activity of leucine-rich repeat kinase 2 (LRRK2) is implicated in the pathogenesis of Parkinson's disease (PD). The quest for effective LRRK2 inhibitors has been impeded by the formidable challenge of crossing the blood-brain barrier (BBB). We leveraged structure-based de novo design and developed robust three-dimensional quantitative structure-activity relationship (3D-QSAR) models to predict BBB permeability, enhancing the likelihood of the inhibitor's brain accessibility. Our strategy involved the synthesis of macrocyclic molecules by linking the two terminal nitrogen atoms of HG-10-102-01 with an alkyl chain ranging from 2 to 4 units, laying the groundwork for innovative LRRK2 inhibitor designs. Through meticulous computational and synthetic optimization of both biochemical efficacy and BBB permeability, 9 out of 14 synthesized candidates demonstrated potent low-nanomolar inhibition and significant BBB penetration. Further assessments of in vitro and in vivo effectiveness, coupled with pharmacological profiling, highlighted 8 as the promising new lead compound for PD therapeutics.

The Benzoylpiperidine Fragment as a Privileged Structure in Medicinal Chemistry: A Comprehensive Review

The phenyl(piperidin-4-yl)methanone fragment (here referred to as the benzoylpiperidine fragment) is a privileged structure in the development of new drugs considering its presence in many bioactive small molecules with both therapeutic (such as anti-cancer, anti-psychotic, anti-thrombotic, anti-arrhythmic, anti-tubercular, anti-parasitic, anti-diabetic, and neuroprotective agents) and diagnostic properties. The benzoylpiperidine fragment is metabolically stable, and it is also considered a potential bioisostere of the piperazine ring, thus making it a feasible and reliable chemical frame to be exploited in drug design. Herein, we discuss the main therapeutic and diagnostic agents presenting the benzoylpiperidine motif in their structure, covering articles reported in the literature since 2000. A specific section is focused on the synthetic strategies adopted to obtain this versatile chemical portion.

Predicting Cardiotoxicity of Molecules Using Attention-Based Graph Neural Networks

In drug discovery, the search for new and effective medications is often hindered by concerns about toxicity. Numerous promising molecules fail to pass the later phases of drug development due to strict toxicity assessments. This challenge significantly increases the cost, time, and human effort needed to discover new therapeutic molecules. Additionally, a considerable number of drugs already on the market have been withdrawn or re-evaluated because of their unwanted side effects. Among the various types of toxicity, drug-induced heart damage is a severe adverse effect commonly associated with several medications, especially those used in cancer treatments. Although a number of computational approaches have been proposed to identify the cardiotoxicity of molecules, the performance and interpretability of the existing approaches are limited. In our study, we proposed a more effective computational framework to predict the cardiotoxicity of molecules using an attention-based graph neural network. Experimental results indicated that the proposed framework outperformed the other methods. The stability of the model was also confirmed by our experiments. To assist researchers in evaluating the cardiotoxicity of molecules, we have developed an easy-to-use online web server that incorporates our model.

Targeting the hERG1 and β1 integrin complex for cancer treatment

INTRODUCTION

Despite great advances, novel therapeutic targets and strategies are still needed, in particular for some carcinomas in the metastatic stage (breast cancer, colorectal cancer, pancreatic ductal adenocarcinoma and the clear cell renal carcinoma). Ion channels may be considered good cancer biomarkers and targets for antineoplastic therapy. These concepts are particularly relevant considering the hERG1 potassium channel as a novel target for antineoplastic therapy.

AREAS COVERED

A great deal of evidence demonstrates that hERG1 is aberrantly expressed in human cancers, in particular in aggressive carcinomas. A relevant cornerstone was the discovery that, in cancer cells, the channel is present in a very peculiar conformation, strictly bound to the β1 subunit of integrin receptors. The hERG1/β1 integrin complex does not occur in the heart. Starting from this evidence, we developed a novel single chain bispecific antibody (scDb-hERG1-β1), which specifically targets the hERG1/β1 integrin complex and exerts antineoplastic effects in preclinical experiments.

EXPERT OPINION

Since hERG1 blockade cannot be pursued for antineoplastic therapy due to the severe cardiac toxic effects (ventricular arrhythmias) that many hERG1 blockers exert, different strategies must be identified to specifically target hERG1 in cancer. The targeting of the hERG1/β1 integrin complex through the bispecific antibody scDb-hERG1-β1 can overcome such hindrances.

Computer-Aided Drug Discovery and Design: Recent Advances and Future Prospects

Computer-aided drug discovery and design involve the use of information technologies to identify and develop, on a rational ground, chemical compounds that align a set of desired physicochemical and biological properties. In its most common form, it involves the identification and/or modification of an active scaffold (or the combination of known active scaffolds), although de novo drug design from scratch is also possible. Traditionally, the drug discovery and design processes have focused on the molecular determinants of the interactions between drug candidates and their known or intended pharmacological target(s). Nevertheless, in modern times, drug discovery and design are conceived as a particularly complex multiparameter optimization task, due to the complicated, often conflicting, property requirements.This chapter provides an updated overview of in silico approaches for identifying active scaffolds and guiding the subsequent optimization process. Recent groundbreaking advances in the field have also analyzed the integration of state-of-the-art machine learning approaches in every step of the drug discovery process (from prediction of target structure to customized molecular docking scoring functions), integration of multilevel omics data, and the use of a diversity of computational approaches to assist target validation and assess plausible binding pockets.

Facilitation of hERG Activation by Its Blocker: A Mechanism to Reduce Drug-Induced Proarrhythmic Risk

Modulation of the human Ether-à-go-go-Related Gene (hERG) channel, a crucial voltage-gated potassium channel in the repolarization of action potentials in ventricular myocytes of the heart, has significant implications on cardiac electrophysiology and can be either antiarrhythmic or proarrhythmic. For example, hERG channel blockade is a leading cause of long QT syndrome and potentially life-threatening arrhythmias, such as torsades de pointes. Conversely, hERG channel blockade is the mechanism of action of Class III antiarrhythmic agents in terminating ventricular tachycardia and fibrillation. In recent years, it has been recognized that less proarrhythmic hERG blockers with clinical potential or Class III antiarrhythmic agents exhibit, in addition to their hERG-blocking activity, a second action that facilitates the voltage-dependent activation of the hERG channel. This facilitation is believed to reduce the proarrhythmic potential by supporting the final repolarizing of action potentials. This review covers the pharmacological characteristics of hERG blockers/facilitators, the molecular mechanisms underlying facilitation, and their clinical significance, as well as unresolved issues and requirements for research in the fields of ion channel pharmacology and drug-induced arrhythmias.

Therapeutic Study of Cinnamic Acid Derivative for Oxidative Stress Ablation: The Computational and Experimental Answers

This study aimed to examine the therapeutic activity of the cinnamic acid derivative KAD-7 (N'-(2,4-dichlorobenzylidene)-3-(4-methoxyphenyl) acrylohydrazide) on Fe2+-induced oxidative hepatic injury via experimental and computational models. In addition, the role of ATPase and ectonucleoside triphosphate diphosphohydrolase (ENTPDase) in the coordination of cellular signals is speculated upon to proffer suitable therapeutics for metabolic stress disorder upon their inhibition. While we know little about therapeutics with flexible dual inhibitors for these protein targets, this study was designed to screen KAD-7's (N'-(2,4-dichlorobenzylidene)-3-(4-methoxyphenyl) acrylohydrazide) inhibitory potential for both protein targets. We induced oxidative hepatic damage via the incubation of hepatic tissue supernatant with 0.1 mM FeSO4 for 30 min at 37 °C. We achieved the treatment by incubating the hepatic tissues with KAD-7 under the same conditions. The catalase (CAT), glutathione (GSH), malondialdehyde (MDA), ATPase, and ENTPDase activity were all measured in the tissues. We predicted how the drug candidate would work against ATPase and ENTPDase targets using molecular methods. When hepatic injury was induced, there was a significant decrease in the levels of the GSH, CAT, and ENTPDase (p < 0.05) activities. In contrast, we found a noticeable rise in the MDA levels and ATPase activity. KAD-7 therapy resulted in lower levels of these activities overall (p < 0.05), as compared to the control levels. We found the compound to have a strong affinity for ATPase (-7.1 kcal/mol) and ENTPDase (-7.4 kcal/mol), and a better chemical reactivity than quercetin. It also met all drug-likeness parameters. Our study shows that KAD-7 can protect the liver from damage caused by FeSO4 by reducing oxidative stress and purinergic actions. Our studies indicate that KAD-7 could be developed as a therapeutic option since it can flexibly inhibit both ATPase and ENTPDase.

Derivation of Highly Predictive 3D-QSAR Models for hERG Channel Blockers Based on the Quantum Artificial Neural Network Algorithm

The hERG potassium channel serves as an annexed target for drug discovery because the associated off-target inhibitory activity may cause serious cardiotoxicity. Quantitative structure-activity relationship (QSAR) models were developed to predict inhibitory activities against the hERG potassium channel, utilizing the three-dimensional (3D) distribution of quantum mechanical electrostatic potential (ESP) as the molecular descriptor. To prepare the optimal atomic coordinates of dataset molecules, pairwise 3D structural alignments were carried out in order for the quantum mechanical cross correlation between the template and other molecules to be maximized. This alignment method stands out from the common atom-by-atom matching technique, as it can handle structurally diverse molecules as effectively as chemical derivatives that share an identical scaffold. The alignment problem prevalent in 3D-QSAR methods was ameliorated substantially by dividing the dataset molecules into seven subsets, each of which contained molecules with similar molecular weights. Using an artificial neural network algorithm to find the functional relationship between the quantum mechanical ESP descriptors and the experimental hERG inhibitory activities, highly predictive 3D-QSAR models were derived for all seven molecular subsets to the extent that the squared correlation coefficients exceeded 0.79. Given their simplicity in model development and strong predictability, the 3D-QSAR models developed in this study are expected to function as an effective virtual screening tool for assessing the potential cardiotoxicity of drug candidate molecules.

GC-MS chemical profiling, antioxidant, anti-diabetic, and anti-inflammatory activities of ethyl acetate fraction of Spilanthes filicaulis (Schumach. and Thonn.) C.D. Adams leaves: experimental and computational studies

Introduction: This study aimed to investigate the chemical profile of GC-MS, antioxidant, anti-diabetic, and anti-inflammatory activities of the ethyl acetate fraction of Spilanthes filicaulis leaves (EFSFL) via experimental and computational studies. Methods: After inducing oxidative damage with FeSO4, we treated the tissues with different concentrations of EFSFL. An in-vitro analysis of EFSFL was carried out to determine its potential for antioxidant, anti-diabetic, and anti-inflammatory activities. We also measured the levels of CAT, SOD, GSH, and MDA. Results and discussion: EFSFL exhibited anti-inflammatory properties through membrane stabilizing properties (IC50 = 572.79 μg/ml), proteinase inhibition (IC50 = 319.90 μg/ml), and inhibition of protein denaturation (IC50 = 409.88 μg/ml). Furthermore, EFSFL inhibited α-amylase (IC50 = 169.77 μg/ml), α-glucosidase (IC50 = 293.12 μg/ml) and DPP-IV (IC50 = 380.94 μg/ml) activities, respectively. Our results indicated that induction of tissue damage reduced the levels of GSH, SOD, and CAT activities, and increased MDA levels. However, EFSFL treatment restores these levels to near normal. GC-MS profiling shows that EFSFL contains 13 compounds, with piperine being the most abundant. In silico interaction of the phytoconstituents using molecular and ensembled-based docking revealed strong binding tendencies of two hit compounds to DPP IV (alpha-caryophyllene and piperine with a binding affinity of -7.8 and -7.8 Kcal/mol), α-glucosidase (alpha-caryophyllene and piperine with a binding affinity of -9.6 and -8.9 Kcal/mol), and to α-amylase (piperine and Benzocycloheptano[2,3,4-I,j]isoquinoline, 4,5,6,6a-tetrahydro-1,9-dihydroxy-2,10-dimethoxy-5-methyl with a binding affinity of -7.8 and -7.9 Kcal/mol), respectively. These compounds also presented druggable properties with favorable ADMET. Conclusively, the antioxidant, antidiabetic, and anti-inflammatory activities of EFSFL could be due to the presence of secondary metabolites.

Mitigating hERG Liability of Toll-Like Receptor 9 and 7 Antagonists through Structure-Based Design

hERG is considered to be a primary anti-target in the drug development process, as the K+ channel encoded by hERG plays an important role in cardiac re-polarization. It is desirable to address the hERG safety liability during early-stage development to avoid the expenses of validating leads that will eventually fail at a later stage. We have previously reported the development of highly potent quinazoline-based TLR7 and TLR9 antagonists for possible application against autoimmune disease. Initial experimental hERG assessment showed that most of the lead TLR7 and TLR9 antagonists suffer from hERG liability rendering them ineffective for further development. The present study herein describes a coordinated strategy to integrate the understanding from structure-based protein-ligand interaction to develop non- hERG binders with IC50 >30 μM with retention of TLR7/9 antagonism through a single point change in the scaffold. This structure-guided strategy can serve as a prototype for abolishing hERG liability during lead optimization.

Evaluation of Some Safety Parameters of Dual Histamine H3 and Sigma-2 Receptor Ligands with Anti-Obesity Potential

Many studies have shown the high efficacy of histamine H₃ receptor ligands in preventing weight gain. In addition to evaluating the efficacy of future drug candidates, it is very important to assess their safety profile, which is established through numerous tests and preclinical studies. The purpose of the present study was to evaluate the safety of histamine H₃/sigma-2 receptor ligands by assessing their effects on locomotor activity and motor coordination, as well as on the cardiac function, blood pressure, and plasma activity of certain cellular enzymes. The ligands tested at a dose of 10 mg/kg b.w. did not cause changes in locomotor activity (except for KSK-74) and did not affect motor coordination. Significant reductions in blood pressure were observed after the administration of compounds KSK-63, KSK-73, and KSK-74, which seems logically related to the increased effect of histamine. Although the results of in vitro studies suggest that the tested ligands can block the human ether-a-go-go-related gene (hERG) potassium channels, they did not affect cardiac parameters in vivo. It should be noted that repeated administration of the tested compounds prevented an increase in the activity of alanine aminotransferase (AlaT) and gamma-glutamyl transpeptidases (gGT) observed in the control animals fed a palatable diet. The obtained results show that the ligands selected for this research are not only effective in preventing weight gain but also demonstrate safety in relation to the evaluated parameters, allowing the compounds to proceed to the next stages of research.

Can We Quickly Learn to "Translate" Bioactive Molecules with Transformer Models?

Meaningful exploration of the chemical space of druglike molecules in drug design is a highly challenging task due to a combinatorial explosion of possible modifications of molecules. In this work, we address this problem with transformer models, a type of machine learning (ML) model originally developed for machine translation. By training transformer models on pairs of similar bioactive molecules from the public ChEMBL data set, we enable them to learn medicinal-chemistry-meaningful, context-dependent transformations of molecules, including those absent from the training set. By retrospective analysis on the performance of transformer models on ChEMBL subsets of ligands binding to COX2, DRD2, or HERG protein targets, we demonstrate that the models can generate structures identical or highly similar to most active ligands, despite the models having not seen any ligands active against the corresponding protein target during training. Our work demonstrates that human experts working on hit expansion in drug design can easily and quickly employ transformer models, originally developed to translate texts from one natural language to another, to "translate" from known molecules active against a given protein target to novel molecules active against the same target.

Identification of promising multi-targeting inhibitors of obesity from Vernonia amygdalina through computational analysis

Vernonia amygdalina, a widely consumed West African food herb, can be a boon in the discovery of safe anti-obesity agents given the extensive reports on its anti-obesity and antidiabetic potentials. The main aim of this study was to screen 78 Vernonia-Derived Phytocompounds (VDPs) against the active site regions of Human Pancreatic Lipase (HPL), Human Pancreatic Amylase and Human Glucosidase (HG) as drug targets associated with obesity in silico. Structure-based virtual screening helped to identify Luteolin 7-O-glucuronoside and Andrographidoid D2 as hit compounds with dual targeting tendency towards the HPL and HG. Analysis of the molecular dynamic simulation trajectory files of the ligand-receptor complexes as computed from the thermodynamic parameters plots showed not only increased flexibility and greater interaction potential of the active site residues of the receptor towards the VDPs as indicated by the root mean square fluctuation but also higher stability as indicated by the root mean square deviation, radius of gyration and number of hydrogen bonds. The cluster analysis further showed that the interactions with important residues were preserved in the dynamic environment. These observations were further verified from Molecular Mechanics Generalized Born Surface Area Analysis, which also showed that residual contributions to the binding free energies were mainly from catalytic residues at the active sites of the enzymes. The hit compounds also feature desirable physicochemical properties and drug-likeness. This study provides in silico evidence for the inhibitory potential of phytochemicals from Vernonia amygdalina against two target enzymes in obesity.

Toward Quantitative Models in Safety Assessment: A Case Study to Show Impact of Dose-Response Inference on hERG Inhibition Models

Due to challenges with historical data and the diversity of assay formats, in silico models for safety-related endpoints are often based on discretized data instead of the data on a natural continuous scale. Models for discretized endpoints have limitations in usage and interpretation that can impact compound design. Here, we present a consistent data inference approach, exemplified on two data sets of Ether-à-go-go-Related Gene (hERG) K+ inhibition data, for dose-response and screening experiments that are generally applicable for in vitro assays. hERG inhibition has been associated with severe cardiac effects and is one of the more prominent safety targets assessed in drug development, using a wide array of in vitro and in silico screening methods. In this study, the IC₅₀ for hERG inhibition is estimated from diverse historical proprietary data. The IC₅₀ derived from a two-point proprietary screening data set demonstrated high correlation (R = 0.98, MAE = 0.08) with IC_50s derived from six-point dose-response curves. Similar IC₅₀ estimation accuracy was obtained on a public thallium flux assay data set (R = 0.90, MAE = 0.2). The IC₅₀ data were used to develop a robust quantitative model. The model's MAE (0.47) and R² (0.46) were on par with literature statistics and approached assay reproducibility. Using a continuous model has high value for pharmaceutical projects, as it enables rank ordering of compounds and evaluation of compounds against project-specific inhibition thresholds. This data inference approach can be widely applicable to assays with quantitative readouts and has the potential to impact experimental design and improve model performance, interpretation, and acceptance across many standard safety endpoints.

Pharmacoinformatic study of inhibitory potentials of selected flavonoids against papain-like protease and 3-chymotrypsin-like protease of SARS-CoV-2

Background

Inhibition of papain-like protease (PLpro) and 3-chymotrypsin-like protease (3CLpro) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is projected to terminate its replication. Hence, these proteases represent viable therapeutic targets.

Methods

Sixty-one flavonoids with reported activities against other RNA viruses were selected and docked in PLpro and 3CLpro. Flavonoids with better binding energies compared to reference inhibitors (lopinavir and ritonavir) in their interaction with PLpro and 3CLpro were selected for drug-likeness and ADMET analysis. The best representative flavonoid for each protease from the ADMET filtering analysis was subjected to molecular dynamics simulations (MDS) and clustering analysis of the trajectory files.

Results

Licorice, ugonin M, procyanidin, silymarin, and gallocatechin gallate had better binding energies (-11.8, -10.1, -9.8, -9.7 and -9.6 kcal/mol respectively) with PLpro compared to lopinavir and ritonavir (-9.1 and -8.5 kcal/mol respectively). Also, isonymphaeol B, baicalin, abyssinone II, tomentin A, and apigetrin had better binding energies (-8.7, -8.3, -8.2, -8.1, and -8.1 kcal/mol respectively) with 3CLpro compared to lopinavir and ritonavir (-7.3 and -7.1 kcal/mol respectively). These flavonoids interacted with the proteases via hydrogen and non-hydrogen bonding. Of these flavonoids, silymarin and isonymphaeol B demonstrated most favourable combination of attributes in terms of binding energies, compliance with Lipinski rule for drug-likeness and favourable pharmacokinetics in silico. These two flavonoids exhibited appreciable degree of structural stability, maintaining strong interaction with residues in the different representative clusters selected during the MDS run.

Conclusion

Silymarin and isonymphaeol B are proposed for further studies as compounds with potential activities against SARS-CoV-2.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40816-022-00347-y.

• Flavonoids displayed varying affinities for PLpro and 3CLpro of SARS-CoV-2

• They interacted via hydrogen and non-hydrogen bonds; nine and twenty-seven flavonoids had better binding affinities for PLpro and 3CLpro respectively than lopinavir and ritonavir

• Silymarin and isonymphaeol B demonstrated most favourable combination of attributes in terms of binding energies, compliance with Lipinski rule for drug-likeness and favourable pharmacokinetics.

• Silymarin and isonymphaeol B exhibited appreciable degree of structural stability, maintaining strong interaction with residues in the different representative clusters selected during the MDS run.

Inhibition of human ether-à-go-go-related gene K+ currents expressed in HEK293 cells by three gingerol components from ginger

OBJECTIVES

Gingerols are bioactive compounds derived from ginger, our experiment investigates the effects of 6-, 8- and 10-Gin on the human ether-à-go-go-related gene (hERG) K+ channels by using patch clamp technology.

KEY FINDINGS

hERG K+ currents were suppressed by 6-, 8- and 10-Gin in a concentration-dependent manner. The IC50 values of 6-, 8- and 10-Gin were 41.5, 16.1 and 86.5 μM for the hERG K+ currents, respectively. The maximum inhibitory effects caused by 6-, 8- and 10-Gin were 44.3% ± 2.0%, 88.6% ± 1.3% and 63.1% ± 1.1%, respectively, and the effects were almost completely reversible.

CONCLUSION

These findings suggest that 8-Gin is the most potent hERG K+ channel inhibitor among gingerol components and may offer a new approach for understanding and treating cancer.

Structural and Biofunctional Insights into the Cyclo(Pro-Pro-Phe-Phe-) Scaffold from Experimental and In Silico Studies: Melanoma and Beyond

Short peptides have great potential as safe and effective anticancer drug leads. Herein, the influence of short cyclic peptides containing the Pro-Pro-Phe-Phe sequence on patient-derived melanoma cells was investigated. Cyclic peptides such as cyclo(Leu-Ile-Ile-Leu-Val-Pro-Pro-Phe-Phe-), called CLA, and cyclo(Pro-homoPro-β3homoPhe-Phe-), called P11, exert the cytotoxic and the cytostatic effects in melanoma cells, respectively. CLA was the most active peptide as it reduced the viability of melanoma cells to 50% of control at about 10 µM, whereas P11 at about 40 µM after 48 h incubation. Interestingly, a linear derivative of P11 did not induce any effect in melanoma cells confirming previous studies showing that cyclic peptides exert better biological activity compared to their linear counterparts. According to in silico predictions, cyclic tetrapeptides show a better pharmacokinetic and toxic profile to humans than CLA. Notably, the spatial structure of those peptides containing synthetic amino acids has not been explored yet. In the Cambridge Structural Database, there is only one such cyclic tetrapeptide, cyclo((R)-β2homoPhe-D-Pro-Lys-Phe-), while in the Protein Data Bank—none. Therefore, we report the first crystal structure of cyclo(Pro-Pro-β3homoPhe-Phe-), denoted as 4B8M, a close analog of P11, which is crucial for drug discovery. Comparative molecular and supramolecular analysis of both structures was performed. The DFT findings revealed that 4B8M is well interpreted in the water solution. The results of complex Hirshfeld surface investigations on the cooperativity of interatomic contacts in terms of electrostatic and energetic features are provided. In short, the enrichment ratio revealed O…H/H…O and C…H/H…C as privileged intercontacts in the crystals in relation to basic and large supramolecular H-bonding synthon patterns. Furthermore, the ability of self-assemble 4B8M leading to a nanotubular structure is also discussed.

A Comprehensive In Silico Exploration of Pharmacological Properties, Bioactivities, Molecular Docking, and Anticancer Potential of Vieloplain F from Xylopia vielana Targeting B-Raf Kinase

Compounds derived from plants have several anticancer properties. In the current study, one guaiane-type sesquiterpene dimer, vieloplain F, isolated from Xylopia vielana species, was tested against B-Raf kinase protein (PDB: 3OG7), a potent target for melanoma. A comprehensive in silico analysis was conducted in this research to understand the pharmacological properties of a compound encompassing absorption, distribution, metabolism, excretion, and toxicity (ADMET), bioactivity score predictions, and molecular docking. During ADMET estimations, the FDA-approved medicine vemurafenib was hepatotoxic, cytochrome-inhibiting, and non-cardiotoxic compared to the vieloplain F. The bioactivity scores of vieloplain F were active for nuclear receptor ligand and enzyme inhibitor. During molecular docking experiments, the compound vieloplain F has displayed a higher binding potential with -11.8 kcal/mol energy than control vemurafenib -10.2 kcal/mol. It was shown that intermolecular interaction with the B-Raf complex and the enzyme's active gorge through hydrogen bonding and hydrophobic contacts was very accurate for the compound vieloplain F, which was then examined for MD simulations. In addition, simulations using MM-GBSA showed that vieloplain F had the greatest propensity to bind to active site residues. The vieloplain F has predominantly represented a more robust profile compared to control vemurafenib, and these results opened the road for vieloplain F for its utilization as a plausible anti-melanoma agent and anticancer drug in the next era.

Mechanism and prevention strategy of a bidirectional relationship between heart failure and cancer (Review)

The relationship between cancer and heart failure has been extensively studied in the last decade. These studies have focused on describing heart injury caused by certain cancer treatments, including radiotherapy, chemotherapy and targeted therapy. Previous studies have demonstrated a higher incidence of cancer in patients with heart failure. Heart failure enhances an over-activation of the sympathetic nervous system and the renin-angiotensin-aldosterone system, and subsequently promotes cancer development. Other studies have found that heart failure and cancer both have a common pathological origin, flanked by chronic inflammation in certain organs. The present review aims to summarize and describe the recent discoveries, suggested mechanisms and relationships between heart failure and cancer. The current review provides more ideas on clinical prevention strategies according to the pathological mechanism involved.

Stress Driven Discovery of Natural Products From Actinobacteria with Anti-Oxidant and Cytotoxic Activities Including Docking and ADMET Properties

Elicitation through abiotic stress, including chemical elicitors like heavy metals, is a new technique for drug discovery. In this research, the effect of heavy metals on actinobacteria Streptomyces sp. SH-1312 for secondary metabolite production, with strong pharmacological activity, along with pharmacokinetics profile, was firstly investigated. The optimum metal stress conditions consisted of actinobacteria strain Streptomyces sp. SH-1312 with addition of mix metals (Co²⁺ + Zn²⁺) ions at 0.5 mM in Gause’s medium. Under these conditions, the stress metabolite anhydromevalonolactone (MVL) was produced, which was absent in the normal culture of strain and other metals combinations. Furthermore, the stress metabolite was also evaluated for its anti-oxidant and cytotoxic activities. The compound exhibited remarkable anti-oxidant activities, recording the IC₅₀ value of 19.65 ± 5.7 µg/mL in DPPH, IC₅₀ of 15.49 ± 4.8 against NO free radicals, the IC₅₀ value of 19.65 ± 5.22 µg/mL against scavenging ability, and IC₅₀ value of 19.38 ± 7.11 µg/mL for iron chelation capacity and the cytotoxic activities against PC3 cell lines were recorded with IC₅₀ values of 35.81 ± 4.2 µg/mL after 24 h, 23.29 ± 3.8 µg/mL at 48 h, and 16.25 ± 6.5 µg/mL after 72 h. Further mechanistic studies have revealed that the compound MVL has shown its pharmacological efficacy by upregulation of P53 and BAX while downregulation of BCL-2 expression, indicating that MVL is following apoptosis in varying degrees. To better understand the pharmacological properties of MVL, in this work, the absorption, distribution, metabolism, excretion, and toxicity (ADMET) were also evaluated. During ADMET predictions, MVL has displayed a safer profile in case of hepatotoxicity, cytochrome inhibition and also displayed as non-cardiotoxic. The compound MVL showed good binding energy in the molecular docking studies, and the results revealed that MVL bind in the active region of the target protein of P53 and BAX. This work triumphantly announced a prodigious effect of heavy metals on actinobacteria with fringe benefits as a key tool of MVL production with a strong pharmacological and pharmacokinetic profile.

The Antiarrhythmic Activity of Novel Pyrrolidin-2-one Derivative S-75 in Adrenaline-Induced Arrhythmia

Arrhythmia is a quivering or irregular heartbeat that can often lead to blood clots, stroke, heart failure, and other heart-related complications. The limited efficacy and safety of antiarrhythmic drugs require the design of new compounds. Previous research indicated that pyrrolidin-2-one derivatives possess an affinity for α₁-adrenergic receptors. The blockade of α₁-adrenoceptor may play a role in restoring normal sinus rhythm; therefore, we aimed to verify the antiarrhythmic activity of novel pyrrolidin-2-one derivative S-75. In this study, we assessed the influence on sodium, calcium, potassium channels, and β₁-adrenergic receptors to investigate the mechanism of action of S-75. Lack of affinity for β₁-adrenoceptors and weak effects on ion channels decreased the role of these adrenoceptors and channels in the pharmacological activity of S-75. Next, we evaluated the influence of S-75 on normal ECG in rats and isolated rat hearts, and the tested derivative did not prolong the QT_c interval, which may confirm the lack of the proarrhythmic potential. We tested antiarrhythmic activity in adrenaline-, aconitine- and calcium chloride-induced arrhythmia models in rats. The studied compound showed prophylactic antiarrhythmic activity in the adrenaline-induced arrhythmia, but no significant activity in the model of aconitine- or calcium chloride-induced arrhythmia. In addition, S-75 was not active in the model of post-reperfusion arrhythmias of the isolated rat hearts. Conversely, the compound showed therapeutic antiarrhythmic properties in adrenaline-induced arrhythmia, reducing post-arrhythmogen heart rhythm disorders, and decreasing animal mortality. Thus, we suggest that the blockade of α₁-adrenoceptor might be beneficial in restoring normal heart rhythm in adrenaline-induced arrhythmia.

Computational Exploration of Anti-Cancer Potential of Guaiane Dimers from Xylopia vielana by Targeting B-Raf Kinase Using Chemo-Informatics, Molecular Docking and MD Simulation Studies

BACKGROUND

Natural products from herbs are prolific to display robust anticancer activities.

OBJECTIVES

In the current study, B-Raf kinase protein (PDB: 3OG7), a potent target for melanoma, was tested against two guaiane-type sesquiterpene dimers, xylopin E-F, obtained from Xylopia vielana.

METHODS

In this work, a systematic in silico study using ADMET analysis, bioactivity score forecasts, molecular docking, and its simulations were conducted to understand compounds' pharmacological properties.

RESULTS

During ADMET predictions of both the compounds, Xylopin E-F has displayed a safer profile in hepatotoxicity, cytochrome inhibition, and only xylopin F displayed as non-cardiotoxic compared to FDA approved drug vemurafenib. Both the compounds were proceeded to molecular docking experiments using Autodock docking software and both the compounds Xylopin E-F have displayed higher binding potential with -11.5Kcal/mol energy compared to control vemurafenib -10.2 Kcal/mol. All the compounds were further evaluated for their MD simulations and their molecular interactions with the B-Raf kinase complex displayed precise interactions with the active gorge of the enzyme by hydrogen bonding.

CONCLUSIONS

Overall, xylopin F had a better profile relative to xylopin E and vemurafenib, and these findings indicated that this bio-molecule could be used as an anti-melanoma agent and as a possible anticancer drug in the future. Therefore, this is a systematic optimized in silico approach to creating an anticancer pathway for guaiane dimers against the backdrop of its potential for future drug development.

Effective Perturbations on the Amplitude and Hysteresis of Erg-Mediated Potassium Current Caused by 1-Octylnonyl 8-[(2-hydroxyethyl)[6-oxo-6(undecyloxy)hexyl]amino]-octanoate (SM-102), a Cationic Lipid

SM-102 (1-octylnonyl 8-[(2-hydroxyethyl)[6-oxo-6-(undecyloxy)hexyl]amino]-octanoate) is an amino cationic lipid that has been tailored for the formation of lipid nanoparticles and it is one of the essential ingredients present in the ModernaTM COVID-19 vaccine. However, to what extent it may modify varying types of plasmalemmal ionic currents remains largely uncertain. In this study, we investigate the effects of SM-102 on ionic currents either in two types of endocrine cells (e.g., rat pituitary tumor (GH3) cells and mouse Leydig tumor (MA-10) cells) or in microglial (BV2) cells. Hyperpolarization-activated K+ currents in these cells bathed in high-K+, Ca2+-free extracellular solution were examined to assess the effects of SM-102 on the amplitude and hysteresis of the erg-mediated K+ current (IK(erg)). The SM-102 addition was effective at blocking IK(erg) in a concentration-dependent fashion with a half-maximal concentration (IC50) of 108 μM, a value which is similar to the KD value (i.e., 134 μM) required for its accentuation of deactivation time constant of the current. The hysteretic strength of IK(erg) in response to the long-lasting isosceles-triangular ramp pulse was effectively decreased in the presence of SM-102. Cell exposure to TurboFectinTM 8.0 (0.1%, v/v), a transfection reagent, was able to inhibit hyperpolarization-activated IK(erg) effectively with an increase in the deactivation time course of the current. Additionally, in GH3 cells dialyzed with spermine (30 μM), the IK(erg) amplitude progressively decreased; moreover, a further bath application of SM-102 (100 μM) or TurboFectin (0.1%) diminished the current magnitude further. In MA-10 Leydig cells, the IK(erg) was also blocked by the presence of SM-102 or TurboFectin. The IC50 value for SM-102-induced inhibition of IK(erg) in MA-10 cells was 98 μM. In BV2 microglial cells, the amplitude of the inwardly rectifying K+ current was inhibited by SM-102. Taken together, the presence of SM-102 concentration-dependently inhibited IK(erg) in endocrine cells (e.g., GH3 or MA-10 cells), and such action may contribute to their functional activities, assuming that similar in vivo findings exist.

Structure-based virtual screening suggests inhibitors of 3-Chymotrypsin-Like Protease of SARS-CoV-2 from Vernonia amygdalina and Occinum gratissimum

Antiviral culinary plants are potential bioresources for preventive nutraceuticals and/or antiviral drugs in COVID-19. Structure-based virtual screening was undertaken to screen 173 compounds previously reported from Vernonia amygdalina and Occinum gratissimum for direct interaction with the active site of the 3-Chymotrypsin-Like Protease (3CL^pro) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Based on docking scores and comparison with reference inhibitors, a hit-list of 10 top phytocompounds was defined, which also had strong interactions with the catalytic centre of 3CL^pro from three related strains of coronavirus (SARS-CoV, MERS-CoV, HKU4). Among these, six compounds (neoandrographolide, vernolide, isorhamnetin, chicoric acid, luteolin, and myricetin) exhibited the highest binding tendencies to the equilibrated conformers of SARS-CoV-2 3CL^pro in an in-depth docking analysis to 5 different representative conformations from the cluster analysis of the molecular dynamics simulation (MDS) trajectories of the protein. In silico drug-likeness analyses revealed two drug-like terpenoids viz: neoandrographolide and vernolide as promising inhibitors of SARS-CoV-2 3CL^pro. These structures were accommodated within the substrate-binding pocket; and interacted with the catalytic dyad (Cys¹⁴⁵ and His⁴¹), the oxyanion loop (residues 138-145), and the S1/S2 sub-sites of the enzyme active site through the formation of an array of hydrogen bonds and hydrophobic interactions. Molecular dynamics simulation and binding free energy calculation revealed that the terpenoid-enzyme complexes exhibit strong interactions and structural stability. Therefore, these compounds may stabilize the conformation of the flexible oxyanion loop; and thereby interfere with the tetrahedral oxyanion intermediate formation during the proteolytic activity of the enzyme.

Dual targeting of cytokine storm and viral replication in COVID-19 by plant-derived steroidal pregnanes: An in silico perspective

The high morbidity and mortality rate of Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) infection arises majorly from the Acute Respiratory Distress Syndrome and "cytokine storm" syndrome, which is sustained by an aberrant systemic inflammatory response and elevated pro-inflammatory cytokines. Thus, phytocompounds with broad-spectrum anti-inflammatory activity that target multiple SARS-CoV-2 proteins will enhance the development of effective drugs against the disease. In this study, an in-house library of 117 steroidal plant-derived pregnanes (PDPs) was docked in the active regions of human glucocorticoid receptors (hGRs) in a comparative molecular docking analysis. Based on the minimal binding energy and a comparative dexamethasone binding mode analysis, a list of top twenty ranked PDPs docked in the agonist conformation of hGR, with binding energies ranging between -9.8 and -11.2 kcal/mol, was obtained and analyzed for possible interactions with the human Janus kinases 1 and Interleukins-6 and SARS-CoV-2 3-chymotrypsin-like protease, Papain-like protease and RNA-dependent RNA polymerase. For each target protein, the top three ranked PDPs were selected. Eight PDPs (bregenin, hirundigenin, anhydroholantogenin, atratogenin A, atratogenin B, glaucogenin A, glaucogenin C and glaucogenin D) with high binding tendencies to the catalytic residues of multiple targets were identified. A high degree of structural stability was observed from the 100 ns molecular dynamics simulation analyses of glaucogenin C and hirundigenin complexes of hGR. The selected top-eight ranked PDPs demonstrated high druggable potentials and favourable in silico ADMET properties. Thus, the therapeutic potentials of glaucogenin C and hirundigenin can be explored for further in vitro and in vivo studies.

Prediction of hERG inhibition of drug discovery compounds using biomimetic HPLC measurements

The major causes of failure of drug discovery compounds in clinics are the lack of efficacy and toxicity. To reduce late-stage failures in the drug discovery process, it is essential to estimate early the probability of adverse effects and potential toxicity. Cardiotoxicity is one of the most often observed problems related to a compound's inhibition of the hERG channel responsible for the potassium cation flux. Biomimetic HPLC methods can be used for the early screening of a compound's lipophilicity, protein binding and phospholipid partition. Based on the published hERG pIC50 data of 90 marketed drugs and their measured biomimetic properties, a model has been developed to predict the hERG inhibition using the measured binding of compounds to alpha-1-acid-glycoprotein (AGP) and immobilised artificial membrane (IAM). A representative test set of 16 compounds was carefully selected. The training set, involving the remaining compounds, served to establish the linear model. The mechanistic model supports the hypothesis that compounds have to traverse the cell membrane and bind to the hERG ion channel to cause the inhibition. The AGP and the hERG ion channel show structural similarity, as both bind positively charged compounds with strong shape selectivity. In contrast, a good IAM partition is a prerequisite for cell membrane traversal. For reasons of comparison, a corresponding model was derived by replacing the measured biomimetic properties with calculated physicochemical properties. The model established with the measured biomimetic binding properties proved to be superior and can explain over 70% of the variance of the hERG pIC50 values.

NBD-Based Environment-Sensitive Fluorescent Probes for the Human Ether-a-Go-Go-Related Gene Potassium Channel

Three environment-sensitive probes were developed for the hERG channel based on the nitrobenzoxadiazole fluorophore herein. After careful evaluation, probes M1 and M3 were found to have a high affinity for imaging the hERG channel in the cell-based experiment. Compared with other fluorescent labeling technologies (such as fluorescent proteins), these probes afford a convenient and economical method to determine hERG channel in vitro and in cellulo. Therefore, these probes are expected to be applicable for usage in physiological and pathological studies of hERG channels and have the potential to establish a screening system for hERG channels.

The Complex Management of Atrial Fibrillation and Cancer in the COVID-19 Era: Drug Interactions, Thromboembolic Risk, and Proarrhythmia

PURPOSE OF REVIEW

Cardiotoxicity by anticancer agents has emerged as a multifaceted issue and is expected to affect both mortality and morbidity. This review summarizes clinical challenges in the management of oncological patients requiring anticoagulants for atrial fibrillation (AF) also considering the current outbreak of the COVID-19 (coronavirus disease 2019) pandemic, since this infection can add challenges to the management of both conditions. Specifically, the aims are manyfold: (1) describe the evolving use of direct oral anticoagulants (DOACs) in AF patients with cancer; (2) critically appraise the risk of clinically important drug-drug interactions (DDIs) between DOACs and oral targeted anticancer agents; (3) address expected DDIs between DOACs and candidate anti-COVID drugs, with implications on management of the underlying thrombotic risk; and (4) characterize the proarrhythmic liability in cardio-oncology in the setting of COVID-19, focusing on QT prolongation.

RECENT FINDINGS

AF in cardio-oncology poses diagnostic and management challenges, also due to the number of anticancer drugs recently associated with AF onset/worsening. Oral targeted drugs can potentially interact with DOACs, with increased bleeding risk mainly due to pharmacokinetic DDIs. Moreover, the vast majority of oral anticancer agents cause QT prolongation with direct and indirect mechanisms, potentially resulting in the occurrence of torsade de pointes, especially in susceptible patients with COVID-19 receiving additional drugs with QT liability. Oncologists and cardiologists must be aware of the increased bleeding risk and arrhythmic susceptibility of patients with AF and cancer due to DDIs. High-risk individuals with COVID-19 should be prioritized to target preventive strategies, including optimal antithrombotic management, medication review, and stringent monitoring.

Critical Assessment of Artificial Intelligence Methods for Prediction of hERG Channel Inhibition in the "Big Data" Era

The rise of novel artificial intelligence (AI) methods necessitates their benchmarking against classical machine learning for a typical drug-discovery project. Inhibition of the potassium ion channel, whose alpha subunit is encoded by the human ether-à-go-go-related gene (hERG), leads to a prolonged QT interval of the cardiac action potential and is a significant safety pharmacology target for the development of new medicines. Several computational approaches have been employed to develop prediction models for the assessment of hERG liabilities of small molecules including recent work using deep learning methods. Here, we perform a comprehensive comparison of hERG effect prediction models based on classical approaches (random forests and gradient boosting) and modern AI methods [deep neural networks (DNNs) and recurrent neural networks (RNNs)]. The training set (∼9000 compounds) was compiled by integrating the hERG bioactivity data from the ChEMBL database with experimental data generated from an in-house, high-throughput thallium flux assay. We utilized different molecular descriptors including the latent descriptors, which are real-value continuous vectors derived from chemical autoencoders trained on a large chemical space (>1.5 million compounds). The models were prospectively validated on ∼840 in-house compounds screened in the same thallium flux assay. The best results were obtained with the XGBoost method and RDKit descriptors. The comparison of models based only on latent descriptors revealed that the DNNs performed significantly better than the classical methods. The RNNs that operate on SMILES provided the highest model sensitivity. The best models were merged into a consensus model that offered superior performance compared to reference models from academic and commercial domains. Furthermore, we shed light on the potential of AI methods to exploit the big data in chemistry and generate novel chemical representations useful in predictive modeling and tailoring a new chemical space.

KV11.1, NaV1.5, and CaV1.2 Transporter Proteins as Antitarget for Drug Cardiotoxicity

Safety assessment of pharmaceuticals is a rapidly developing area of pharmacy and medicine. The new advanced guidelines for testing the toxicity of compounds require specialized tools that provide information on the tested drug in a quick and reliable way. Ion channels represent the third-largest target. As mentioned in the literature, ion channels are an indispensable part of the heart's work. In this paper the most important information concerning the guidelines for cardiotoxicity testing and the way the tests are conducted has been collected. Attention has been focused on the role of selected ion channels in this process.

Characterization of the Synergistic Inhibition of IK(erg) and IK(DR) by Ribociclib, a Cyclin-Dependent Kinase 4/6 Inhibitor

Ribociclib (RIB, LE011, Kisqali^®), an orally administered inhibitor of cyclin-dependent kinase-4/6 (CDK-4/6) complex, is clinically effective for the treatment of several malignancies, including advanced breast cancer. However, information regarding the effects of RIB on membrane ion currents is limited. In this study, the addition of RIB to pituitary tumor (GH₃) cells decreased the peak amplitude of erg-mediated K⁺ current (I_K(erg)), which was accompanied by a slowed deactivation rate of the current. The IC₅₀ value for RIB-perturbed inhibition of deactivating I_K(erg) in these cells was 2.7 μM. In continued presence of μM RIB, neither the subsequent addition of 17β-estradiol (30 μM), phorbol 12-myristate 13-acetate (10 μM), or transforming growth factor-β (1 μM) counteracted the inhibition of deactivating I_K(erg). Its presence affected the decrease in the degree of voltage-dependent hysteresis for I_K(erg) elicitation by long-duration triangular ramp voltage commands. The presence of RIB differentially inhibited the peak or sustained component of delayed rectifier K⁺ current (I_K(DR)) with an effective IC₅₀ of 28.7 or 11.4 μM, respectively, while it concentration-dependently decreased the amplitude of M-type K⁺ current with IC₅₀ of 13.3 μM. Upon 10-s long membrane depolarization, RIB elicited a decrease in the I_K(DR) amplitude, which was concomitant with an accelerated inactivation time course. However, the inability of RIB (10 μM) to modify the magnitude of the hyperpolarization-activated cation current was disclosed. The mean current–voltage relationship of I_K(erg) present in HL-1 atrial cardiomyocytes was inhibited in the presence of RIB (10 μM). Collectively, the hyperpolarization-activated cation current was observed. RIB-mediated perturbations in ionic currents presented herein are upstream of its suppressive action on cytosolic CDK-4/6 activities and partly participates in its modulatory effects on the functional activities of pituitary tumor cells (e.g., GH₃ cells) or cardiac myocytes (e.g., HL-1 cells).

Probucol-induced hERG Channel Reduction can be Rescued by Matrine and Oxymatrine in vitro

Background

The human ether-a-go-go-related gene (hERG) potassium channel is the rapidly activating component of cardiac delayed rectifier potassium current (I_Kr), which is a crucial determinant of cardiac repolarization. The reduction of hERG current is commonly believed to cause Long QT Syndrome (LQTs). Probucol, a cholesterol-lowering drug, induces LQTs by inhibiting the expression of the hERG channel. Unfortunately, there is currently no effective therapeutic method to rescue probucol-induced LQTs.

Methods

Patch-clamp recording techniques were used to detect the action potential duration (APD) and current of hERG. Western blot was performed to measure the expression levels of proteins.

Results

In this study, we demonstrated that 1 μM matrine and oxymatrine could rescue the hERG current and hERG surface expression inhibited by probucol. In addition, matrine and oxymatrine significantly shortened the prolonged action potential duration induced by probucol in neonatal cardiac myocytes. We proposed a novel mechanism underlying the probucol induced decrease in the expression of transcription factor Specificity protein 1 (Sp1), which is an established transactivator of the hERG gene. We also demonstrated that matrine and oxymatrine were able to upregulate Sp1 expression which may be one of the possible mechanisms by which matrine and oxymatrine rescued probucol-induced hERG channel deficiency.

Conclusion

Our current results demonstrate that matrine and oxymatrine could rescue probucol-induced hERG deficiency in vitro, which may lead to potentially effective therapeutic drugs for treating acquired LQT2 by probucol in the future.

Prediction of hERG potassium channel blockage using ensemble learning methods and molecular fingerprints

The human ether-a-go-go-related gene (hERG) encodes a tetrameric potassium channel called Kv11.1. This channel can be blocked by certain drugs, which leads to long QT syndrome, causing cardiotoxicity. This is a significant problem during drug development. Using computer models to predict compound cardiotoxicity during the early stages of drug design will help to solve this problem. In this study, we used a dataset of 1865 compounds exhibiting known hERG inhibitory activities as a training set. Thirty cardiotoxicity classification models were established using three machine learning algorithms based on molecular fingerprints and molecular descriptors. Through using these models as the base classifier, a new cardiotoxicity classification model with better predictive performance was developed using ensemble learning method. The accuracy of the best base classifier, which was generated using the XGBoost method with molecular descriptors, was 84.8 %, and the area under the receiver-operating characteristic curve (AUC) was 0.876 in the five fold cross-validation. However, all of the ensemble models that we developed had higher predictive performance than the base classifiers in the five fold cross-validation. The best predictive performance was achieved by the Ensemble-Top7 model, with accuracy of 84.9 % and AUC of 0.887. We also tested the ensemble model using external validation data and achieved accuracy of 85.0 % and AUC of 0.786. Furthermore, we identified several hERG-related substructures, which provide valuable information for designing drug candidates.

Synthesis, Antitumor Activity and Molecular Docking Studies on Seven Novel Thiazacridine Derivatives

AIM AND OBJECTIVE

In the last decades, cancer has become a major problem in public health all around the globe. Chimeric chemical structures have been established as an important trend on medicinal chemistry in the last years. Thiazacridines are hybrid molecules composed of a thiazolidine and acridine nucleus, both pharmacophores that act on important biological targets for cancer. By the fact it is a serious disease, seven new 3-acridin-9-ylmethyl-thiazolidine-2,4-dione derivatives were synthesized, characterized, analyzed by computer simulation and tested in tumor cells. In order to find out if the compounds have therapeutic potential.

MATERIALS AND METHODS

Seven new 3-acridin-9-ylmethyl-thiazolidine-2,4-dione derivatives were synthesized through Michael addition and Knoevenagel condensation strategies. Characterization was performed by NMR and Infrared spectroscopy techniques. Regarding biological activity, thiazacridines were tested against solid and hematopoietic tumoral cell lines, namely Jurkat (acute T-cell leukemia); HL-60 (acute promyelocytic leukemia); DU 145 (prostate cancer); MOLT-4 (acute lymphoblastic leukemia); RAJI (Burkitt's lymphoma); K562 (chronic myelogenous leukemia) and normal cells PBMC (healthy volunteers). Molecular docking analysis was also performed in order to assess major targets of these new compounds. Cell cycle and clonogenic assay were also performed.

RESULTS

Compound LPSF/AA-62 (9f) exhibited the most potent anticancer activity against HL-60 (IC50 3,7±1,7 μM), MOLT-4 (IC50 5,7±1,1 μM), Jurkat (IC50 18,6 μM), Du-145 (IC50 20±5 μM) and Raji (IC50 52,3±9,2 μM). While the compound LPSF/AA-57 (9b) exhibited anticancer activity against the K562 cell line (IC50 51,8±7,8 μM). Derivative LPSF/AA-62 (9f) did not interfere in the cell cycle phases of the Molt-4 lineage. However, the LPSF/AA-62 (9f) derivative significantly reduced the formation of prostate cancer cell clones. The compound LPSF/AA-62 (9f) has shown strong anchorage stability with enzymes topoisomerases 1 and 2, in particular due the presence of chlorine favored hydrogen bonds with topoisomerase 1.

CONCLUSION

The 3-(acridin-9-ylmethyl)-5-((10-chloroanthracen-9-yl)methylene)thiazolidine-2,4-dione (LPSF/AA-62) presented the most promising results, showing anti-tumor activity in 5 of the 6 cell types tested, especially inhibiting the formation of colonies of prostate tumor cells (DU-145).

Characterization of Convergent Suppression by UCL-2077 (3-(Triphenylmethylaminomethyl)pyridine), Known to Inhibit Slow Afterhyperpolarization, of erg-Mediated Potassium Currents and Intermediate-Conductance Calcium-Activated Potassium Channels

UCL-2077 (triphenylmethylaminomethyl)pyridine) was previously reported to suppress slow afterhyperpolarization in neurons. However, the information with respect to the effects of UCL-2077 on ionic currents is quite scarce. The addition of UCL-2077 decreased the amplitude of erg-mediated K⁺ current (I_K(erg)) together with an increased deactivation rate of the current in pituitary GH₃ cells. The IC₅₀ and K_D values of UCL-2077-induced inhibition of I_K(erg) were 4.7 and 5.1 μM, respectively. UCL-2077 (10 μM) distinctly shifted the midpoint in the activation curve of I_K(erg) to less hyperpolarizing potentials by 17 mV. Its presence decreased the degree of voltage hysteresis for I_K(erg) elicitation by long-lasting triangular ramp pulse. It also diminished the probability of the opening of intermediate-conductance Ca²⁺-activated K⁺ channels. In cell-attached current recordings, UCL-2077 raised the frequency of action currents. When KCNH2 mRNA was knocked down, a UCL-2077-mediated increase in AC firing was attenuated. Collectively, the actions elaborated herein conceivably contribute to the perturbating effects of this compound on electrical behaviors of excitable cells.

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.

Deep Learning-Based Prediction of Drug-Induced Cardiotoxicity

Blockade of the human ether-à-go-go-related gene (hERG) channel by small molecules induces the prolongation of the QT interval which leads to fatal cardiotoxicity and accounts for the withdrawal or severe restrictions on the use of many approved drugs. In this study, we develop a deep learning approach, termed deephERG, for prediction of hERG blockers of small molecules in drug discovery and postmarketing surveillance. In total, we assemble 7,889 compounds with well-defined experimental data on the hERG and with diverse chemical structures. We find that deephERG models built by a multitask deep neural network (DNN) algorithm outperform those built by single-task DNN, naı̈ve Bayes (NB), support vector machine (SVM), random forest (RF), and graph convolutional neural network (GCNN). Specifically, the area under the receiver operating characteristic curve (AUC) value for the best model of deephERG is 0.967 on the validation set. Furthermore, based on 1,824 U.S. Food and Drug Administration (FDA) approved drugs, 29.6% drugs are computationally identified to have potential hERG inhibitory activities by deephERG, highlighting the importance of hERG risk assessment in early drug discovery. Finally, we showcase several novel predicted hERG blockers on approved antineoplastic agents, which are validated by clinical case reports, experimental evidence, and the literature. In summary, this study presents a powerful deep learning-based tool for risk assessment of hERG-mediated cardiotoxicities in drug discovery and postmarketing surveillance.

Relative positioning of Kv11.1 (hERG) K+ channel cytoplasmic domain-located fluorescent tags toward the plasma membrane

Recent cryo-EM data have provided a view of the KCNH potassium channels molecular structures. However, some details about the cytoplasmic domains organization and specially their rearrangements associated to channel functionality are still lacking. Here we used the voltage-dependent dipicrylamine (DPA)-induced quench of fluorescent proteins (FPS) linked to different positions at the cytoplasmic domains of KCNH2 (hERG) to gain some insights about the coarse structure of these channel parts. Fast voltage-clamp fluorometry with HEK293 cells expressing membrane-anchored FPs under conditions in which only the plasma membrane potential is modified, demonstrated DPA voltage-dependent translocation and subsequent FRET-triggered FP quenching. Our data demonstrate for the first time that the distance between an amino-terminal FP tag and the intracellular plasma membrane surface is shorter than that between the membrane and a C-terminally-located tag. The distances varied when the FPs were attached to other positions along the channel cytoplasmic domains. In some cases, we also detected slower fluorometric responses following the fast voltage-dependent dye translocation, indicating subsequent label movements orthogonal to the plasma membrane. This finding suggests the existence of additional conformational rearrangements in the hERG cytoplasmic domains, although their association with specific aspects of channel operation remains to be established.

Generation and characterization of novel recombinant anti-hERG1 scFv antibodies for cancer molecular imaging

Modern molecular imaging techniques have greatly improved tumor detection and post-treatment follow-up of cancer patients. In this context, antibody-based imaging is rapidly becoming the gold standard, since it combines the unique specificity of antibodies with the sensitivity of the different imaging technologies. The aim of this study was to generate and characterize antibodies in single chain Fragment variable (scFv) format directed to an emerging cancer biomarker, the human ether-à-go-go-related gene-1 (hERG1) potassium channel, and to obtain a proof of concept for their potential use for in vivo molecular imaging.

The anti-hERG1scFv was generated from a full length monoclonal antibody and then mutagenized, substituting a Phenylalanine residue in the third framework of the V_H domain with a Cysteine residue. The resulting scFv-hERG1-Cys showed much higher stability and protein yield, increased affinity and more advantageous binding kinetics, compared to the “native” anti-hERG1scFv. The scFv-hERG1-Cys was hence chosen and characterized: it showed a good binding to the native hERG1 antigen expressed on cells, was stable in serum and displayed a fast pharmacokinetic profile once injected intravenously in nude mice. The calculated half-life was 3.1 hours and no general toxicity or cardiac toxic effects were detected. Finally, the in vivo distribution of an Alexa Fluor 750 conjugated scFv-hERG1-Cys was evaluated both in healthy and tumor-bearing nude mice, showing a good tumor-to-organ ratio, ideal for visualizing hERG1-expressing tumor masses in vivo.

In conclusion, the scFv-hERG1-Cys possesses features which make it a suitable tool for application in cancer molecular imaging.

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.

Investigating the state dependence of drug binding in hERG channels using a trapped-open channel phenotype

The hERG channel is a key player in repolarization of the cardiac action potential. Pharmacological blockade of hERG channels depletes the cardiac repolarization reserve, increasing the risk of cardiac arrhythmias. The promiscuous nature of drug interactions with hERG presents a therapeutic challenge for drug design and development. Despite considerable effort, the mechanisms of drug binding remain incompletely understood. One proposed mechanism is that high-affinity drug binding preferentially occurs when channels are in the inactivated state. However, this has been difficult to test, since inactivation is rapid in hERG and access to the drug binding site is limited by slower opening of the activation gate. Here, we have directly assessed the role of inactivation in cisparide and terfenadine drug binding in mutant (I663P) hERG channels where the activation gate is trapped-open. We firstly demonstrate the utility of this approach by showing that inactivation, ion selectivity and high affinity drug binding are preserved in I663P mutant channels. We then assess the role of inactivation by applying cisapride and terfenadine at different membrane voltages, which induce varying degrees of inactivation. We show that the extent of block does not correlate with the extent of inactivation. These data suggest that inactivation is not a major determinant of cisapride or terfenadine binding in hERG channels.