Development of Safe Drugs: The hERG Challenge

Discovery of 3-((4-Benzylpyridin-2-yl)amino)benzamides as Potent GPR52 G Protein-Biased Agonists

Orphan GPR52 is emerging as a promising neurotherapeutic target. Optimization of previously reported lead 4a employing an iterative drug design strategy led to the identification of a series of unique GPR52 agonists, such as 10a (PW0677), 15b (PW0729), and 24f (PW0866), with improved potency and efficacy. Intriguingly, compounds 10a and 24f showed greater bias for G protein/cAMP signaling and induced significantly less in vitro desensitization than parent compound 4a, indicating that reducing GPR52 β-arrestin activity with biased agonism results in sustained GPR52 activation. Further exploration of compounds 15b and 24f indicated improved potency and efficacy, and excellent target selectivity, but limited brain exposure warranting further optimization. These balanced and biased GPR52 agonists provide important pharmacological tools to study GPR52 activation, signaling bias, and therapeutic potential for neuropsychiatric and neurological diseases.

Novel Alaninamide Derivatives with Drug-like Potential for Development as Antiseizure and Antinociceptive Therapies─In Vitro and In Vivo Characterization

In the present study, a series of original alaninamide derivatives have been designed applying a combinatorial chemistry approach, synthesized, and characterized in the in vivo and in vitro assays. The obtained molecules showed potent and broad-spectrum activity in basic seizure models, namely, the maximal electroshock (MES) test, the 6 Hz (32 mA) seizure model, and notably, the 6 Hz (44 mA) model of pharmacoresistant seizures. Most potent compounds 26 and 28 displayed the following pharmacological values: ED50 = 64.3 mg/kg (MES), ED50 = 15.6 mg/kg (6 Hz, 32 mA), ED50 = 29.9 mg/kg (6 Hz, 44 mA), and ED50 = 34.9 mg/kg (MES), ED50 = 12.1 mg/kg (6 Hz, 32 mA), ED50 = 29.5 mg/kg (6 Hz, 44 mA), respectively. Additionally, 26 and 28 were effective in the ivPTZ seizure threshold test and had no influence on the grip strength. Moreover, lead compound 28 was tested in the PTZ-induced kindling model, and then, its influence on glutamate and GABA levels in the hippocampus and cortex was evaluated by the high-performance liquid chromatography (HPLC) method. In addition, 28 revealed potent efficacy in formalin-induced tonic pain, capsaicin-induced pain, and oxaliplatin- and streptozotocin-induced peripheral neuropathy. Pharmacokinetic studies and in vitro ADME-Tox data proved favorable drug-like properties of 28. The patch-clamp recordings in rat cortical neurons showed that 28 at a concentration of 10 μM significantly inhibited fast sodium currents. Therefore, 28 seems to be an interesting candidate for future preclinical development in epilepsy and pain indications.

Isolation, characterization and pharmacological potentials of methanol extract of Cassia fistula leaves: Evidenced from mice model along with molecular docking analysis

The purpose of the current investigation was to conduct a detailed analysis of the chemical components and medicinal properties of the methanolic crude extract derived from the leaves of Cassia fistula. This analysis was carried out using both experimental (in vivo) and computational (in silico) methods. Eleven chemicals were chromatographically isolated using GC-MS/MS, which utilizes a library of NIST and Wiley 2020 versions. FTIR analysis of the extract was performed to identify the functional group of the compounds. The glucose-lowering capacity, analgesic, and anti-diarrheal activities of methanolic crude extract were analyzed utilizing a well-known oral glucose tolerance test, tail immersion method, writhing assay, and castor oil-induced diarrheal mice methods, respectively. After 60 min, 120 min, and 180 min of loading the drugs, a significant reduction of blood glucose levels was examined (p < 0.05) in all the extracts of this plant (200 mg/kg, 400 mg/kg and 600 mg/kg) utilized in this research at a time-dependent manner. Similarly, all the crude extracts showed significant (p < 0.05) effects against pain centrally and peripherally compared to the standard drug morphine (2 mg/kg bw) and diclofenac sodium (50 mg/kg bw). Moreover, the methanol extract (400 mg/kg bw) manifested anti-diarrheal efficacy by inhibiting 72.0 % of the diarrheal episode in mice compared to the standard drug loperamide (inhibition = 80.0%). The results of the computational investigations corroborated existing in-vivo findings. Greater or close to equivalent binding affinity to the active binding sites of kappa opioid receptor, glucose transporter 3 (GLUT 3), and cyclooxygenase 2 was indicative of the potential anti-diarrheal, hypoglycemic, and analgesic characteristics of the isolated compounds (COX-2). Moreover, anticancer and antimicrobial potentiality was also found impressive through evaluation of binding affinity with epidermal growth factor receptor (EGFR) and dihydrofolate reductase (DHFR) receptors. Results from this study indicated that C. fistula might be a beneficial natural resource for treating diarrhea, hyperglycemia, and pain. However, additional research is required to conduct a comprehensive phytochemical screening and establish precise action mechanisms of the crude extract or the plant-derived compounds.

Benchmarking of Small Molecule Feature Representations for hERG, Nav1.5, and Cav1.2 Cardiotoxicity Prediction

In the field of drug discovery, there is a substantial challenge in seeking out chemical structures that possess desirable pharmacological, toxicological, and pharmacokinetic properties. Complications arise when drugs interfere with the functioning of cardiac ion channels, leading to serious cardiovascular consequences. The discontinuation and removal of numerous approved drugs from the market or at late development stages in the pipeline due to such inhibitory effects further highlight the urgency of addressing this issue. Consequently, the early prediction of potential blockers targeting cardiac ion channels during the drug discovery process is of paramount importance. This study introduces a deep learning framework that computationally determines the cardiotoxicity associated with the voltage-gated potassium channel (hERG), the voltage-gated calcium channel (Cav1.2), and the voltage-gated sodium channel (Nav1.5) for drug candidates. The predictive capabilities of three feature representations─molecular fingerprints, descriptors, and graph-based numerical representations─are rigorously benchmarked. Additionally, a novel training and evaluation data set framework is presented, enabling predictive model training of drug off-target cardiotoxicity using a comprehensive and large curated data set covering these three cardiac ion channels. To facilitate these predictions, a robust and comprehensive small molecule cardiotoxicity prediction tool named CToxPred has been developed. It is made available as open source under the permissive MIT license at https://github.com/issararab/CToxPred.

The scorpion toxin BeKm-1 blocks hERG cardiac potassium channels using an indispensable arginine residue

BeKm-1 is a peptide toxin from scorpion venom that blocks the pore of the potassium channel hERG (Kv11.1) in the human heart. Although individual protein structures have been resolved, the structure of the complex between hERG and BeKm-1 is unknown. Here, we used molecular dynamics and ensemble docking, guided by previous double-mutant cycle analysis data, to obtain an in silico model of the hERG-BeKm-1 complex. Adding to the previous mutagenesis study of BeKm-1, our model uncovers the key role of residue Arg20, which forms three interactions (a salt bridge and hydrogen bonds) with the channel vestibule simultaneously. Replacement of this residue even by lysine weakens the interactions significantly. In accordance, the recombinantly produced BeKm-1R20K mutant exhibited dramatically decreased activity on hERG. Our model may be useful for future drug design attempts.

Synthetic approaches and application of clinically approved small-molecule Anti-HIV drugs: An update

Application of chemotherapeutic agents to inhibit the HIV replication process has brought about a significant metamorphosis in the landscape of AIDS. Substantial declines in morbidity and mortality rates have been attained, accompanied by notable decreases in healthcare resource utilization. However, treatment modalities do not uniformly inhibit HIV replication in every patient, while the emergence of drug-resistant viral strains poses a substantial obstacle to subsequent therapeutic interventions. Furthermore, chronic administration of therapy may lead to the manifestation of toxicities. These challenges necessitate the exploration of novel pharmacological agents and innovative therapeutic approaches aimed at effectively managing the persistent viral replication characteristic of chronic infection. This review examines the role of clinically approved small-molecule drugs in the treatment of HIV/AIDS, which provides an in-depth analysis of the major classes of small-molecule drugs, including nucleoside/nucleotide reverse transcriptase inhibitors (NRTIs), non-nucleoside reverse transcriptase inhibitors (NNRTIs), protease inhibitors (PIs), integrase inhibitors, entry inhibitors, and pharmacokinetic enhancers. The review mainly discusses the application, synthetic routes, and mechanisms of action of small-molecule drugs employed in the treatment of HIV, as well as their use in combination with antiretroviral therapy, presenting viewpoints on forthcoming avenues in the development of novel anti-HIV drugs.

Structure-based design of novel heterocycle-substituted ATDP analogs as non-nucleoside reverse transcriptase inhibitors with improved selectivity and solubility

Following on our recently developed biphenyl-ATDP non-nucleoside reverse transcriptase inhibitor ZLM-66 (SI = 2019.80, S = 1.9 μg/mL), a series of novel heterocycle-substituted ATDP derivatives with significantly improved selectivity and solubility were identified by replacement of the biphenyl moiety of ZLM-66 with heterocyclic group with lower lipophilicity. Evidently, the representative analog 7w in this series exhibited dramatically enhanced selectivity and solubility (SI = 12,497.73, S = 4472 μg/mL) in comparison with ZLM-66 (SI = 2019.80, S = 1.9 μg/mL). This new NNRTI conferred low nanomolar inhibition of wild-type HIV-1 strain and tested mutant strains (K103N, L100I, Y181C, E138K, and K103N + Y181C). The analog also demonstrated favorable safety and pharmacokinetic profiles, as evidenced by its insensitivity to CYP and hERG, lack of mortality and pathological damage, and good oral bioavailability in rats (F = 27.1%). Further development of 7w for HIV therapy will be facilitated by this valuable information.

Systematical Evaluation of the Structure-Cardiotoxicity Relationship of 7-Azaindazole-based PI3K Inhibitors Designed by Bioisosteric Approach

A growing concern of cardiotoxicity induced by PI3K inhibitors has raised the requirements to evaluate the structure-cardiotoxicity relationship (SCR) in the development process of novel inhibitors. Based on three bioisosteric 7-azaindazole-based candidate inhibitors namely FD269, FD268 and FD274 that give same order of inhibitory concentration 50% (IC50) magnitude against PI3Ks, in this work, we proposed to systematically evaluate the SCR of 7-azaindazole-based PI3K inhibitors designed by bioisosteric approach. The 24-h lethal concentrations 50% (LC50) of FD269, FD268 and FD274 against zebrafish embryos were 0.35, 4.82 and above 50 μM (not detected), respectively. Determination of the heart rate, pericardial and yolk-sac areas and vascular malformation confirmed the remarkable reduction in the cardiotoxicity of from FD269 to FD268 and to FD274. The IC50s of all three compounds against the hERG channel were tested on the CHO cell line that constitutively expressing hERG channel, which were all higher than 20 μM. The transcriptomic analysis revealed that FD269 and FD268 induced the up-regulation of noxo1b, which encodes a subunit of an NADPH oxidase evoking the oxidative stress. Furthermore, immunohistochemistry tests confirmed the structure-dependent attenuation of the overproduction of ROS and cardiac apoptosis. Our results verified the feasibility of bioisosteric replacement to attenuate the cardiotoxicity of 7-azaindazole-based PI3K inhibitors, suggesting that the screening for PI3K inhibitors with both high potency and low cardiotoxicity from bioisosteres would be a beneficial trial.

EpiMed Coronabank Chemical Collection: Compound selection, ADMET analysis, and utilisation in the context of potential SARS-CoV-2 antivirals

Antiviral drugs are important for the coronavirus disease 2019 (COVID-19) response, as vaccines and antibodies may have reduced efficacy against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants. Antiviral drugs that have been made available for use, albeit with questionable efficacy, include remdesivir (Veklury®), nirmatrelvir-ritonavir (Paxlovid™), and molnupiravir (Lagevrio®). To expand the options available for COVID-19 and prepare for future pandemics, there is a need to investigate new uses for existing drugs and design novel compounds. To support these efforts, we have created a comprehensive library of 750 molecules that have been sourced from in vitro, in vivo, and in silico studies. It is publicly available at our dedicated website (https://epimedlab.org/crl/). The EpiMed Coronabank Chemical Collection consists of compounds that have been divided into 10 main classes based on antiviral properties, as well as the potential to be used for the management, prevention, or treatment of COVID-19 related complications. A detailed description of each compound is provided, along with the molecular formula, canonical SMILES, and U.S. Food and Drug Administration approval status. The chemical structures have been obtained and are available for download. Moreover, the pharmacokinetic properties of the ligands have been characterised. To demonstrate an application of the EpiMed Coronabank Chemical Collection, molecular docking was used to evaluate the binding characteristics of ligands against SARS-CoV-2 nonstructural and accessory proteins. Overall, our database can be used to aid the drug repositioning process, and for gaining further insight into the molecular mechanisms of action of potential compounds of interest.

Hydrophobic tag-based protein degradation: Development, opportunity and challenge

Targeted protein degradation (TPD) has emerged as a promising approach for drug development, particularly for undruggable targets. TPD technology has also been instrumental in overcoming drug resistance. While some TPD molecules utilizing proteolysis-targeting chimera (PROTACs) or molecular glue strategies have been approved or evaluated in clinical trials, hydrophobic tag-based protein degradation (HyT-PD) has also gained significant attention as a tool for medicinal chemists. The increasing number of reported HyT-PD molecules possessing high efficiency in degrading protein and good pharmacokinetic (PK) properties, has further fueled interest in this approach. This review aims to present the design rationale, hydrophobic tags in use, and diverse mechanisms of action of HyT-PD. Additionally, the advantages and disadvantages of HyT-PD in protein degradation are discussed. This review may help inspire the development of more HyT-PDs with superior drug-like properties for clinical evaluation.

Discovery of carboxyl-containing heteroaryldihydropyrimidine derivatives as novel HBV capsid assembly modulators with significantly improved metabolic stability

Interfering with the assembly of hepatitis B virus (HBV) capsid is a promising approach for treating chronic hepatitis B (CHB). In order to enhance the metabolic stability and reduce the strong hERG inhibitory effect of HBV capsid assembly modulator (CAM) GLS4, we rationally designed a series of carboxyl-containing heteroaryldihydropyrimidine (HAP) derivatives based on structural biology information combined with medicinal chemistry strategies. The results from biological evaluation demonstrated that compound 6a-25 (EC50 = 0.020 μM) exhibited greater potency than the positive drug lamivudine (EC50 = 0.09 μM), and was comparable to the lead compound GLS4 (EC50 = 0.007 μM). Furthermore, it was observed that 6a-25 reduced levels of core protein (Cp) and capsid in cells. Preliminary assessment of drug-likeness revealed that 6a-25 exhibited superior water solubility (pH 2.0: 374.81 μg mL-1; pH 7.0: 6.85 μg mL-1; pH 7.4: 25.48 μg mL-1), liver microsomal metabolic stability (t1/2 = 108.2 min), and lower hERG toxicity (10 μM inhibition rate was 72.66%) compared to the lead compound GLS4. Overall, compound 6a-25 holds promise for further investigation.

Identification of [1,2,4]Triazolo[4,3-a]pyrazine PARP1 inhibitors with overcome acquired resistance activities

Poly(ADP-ribose) polymerase 1 (PARP1) inhibitors can selectively kill homologous recombination (HR) deficient cancer cells and elicit anticancer effect through a mechanism of synthetic lethality. In this study, we designed, synthesized and pharmacologically evaluated a series of [1,2,4]triazolo[4,3-a]pyrazine derivatives as a class of potent PARP1 inhibitors. Among them, compounds 17m, 19a, 19c, 19e, 19i and 19k not only displayed more potent inhibitory activities (IC50s < 4.1 nM) than 9 and 1 against PARP1, but also exhibited nanomolar range of antiproliferative effects against MDA-MB-436 (BRCA1-/-, IC50s < 1.9 nM) and Capan-1 (BRCA2-/-, IC50s < 21.6 nM) cells. Notably, 19k significantly inhibited proliferation of resistant Capan-1 cells (IC50s < 0.3 nM). Collectively, the newly discovered PARP1 inhibitors act as a useful pharmacological tool for investigating the mechanism of acquired resistance to PARP1 inhibitors, and may also represent promising therapeutic agents for the treatment of HR deficient cancers with the potential to overcome the acquired resistance.

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.

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

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

Discovery of 2-Aminopyrimidine Derivatives as Potent Dual FLT3/CHK1 Inhibitors with Significantly Reduced hERG Inhibitory Activities

FLT3 inhibitors as single agents have limited effects because of acquired and adaptive resistance and the cardiotoxicity related to human ether-a-go-go-related gene (hERG) channel blockade further impedes safe drugs to the market. Inhibitors having potential to overcome resistance and reduce hERG affinity are highly demanded. Here, we reported a dual FLT3/CHK1 inhibitor 18, which displayed potencies to overcome varying acquired resistance in BaF3 cells with FLT3-TKD and FLT3-ITD-TKD mutations. Moreover, 18 displayed high selectivity over c-KIT more than 1700-fold and greatly reduced hERG affinity, with an IC50 value of 58.4 μM. Further mechanistic studies demonstrated 18 can upregulate p53 and abolish the outgrowth of adaptive resistant cells. In the in vivo studies, 18 demonstrated favorable PK profiles and good safety, suppressed the tumor growth in the MV-4-11 cell inoculated mouse xenograft model, and prolonged the survival in the Molm-13 transplantation model, supporting its further development.

Chemico-pharmacological and computational studies of Ophiorrhiza fasciculata D. Don and Psychotria silhetensis Hook. f. focusing cytotoxic, thrombolytic, anti-inflammatory, antioxidant, and antibacterial properties

The current study sought to examine the pharmacological potentials of crude methanolic extracts of Ophiorrhiza fasciculata and Psychotria silhetensis, as well as their various solvent fractionates, with a focus on cytotoxic, thrombolytic, membrane stabilizing, antioxidant, and antibacterial activities via in vitro and in silico approaches. The extensive chromatographic and spectroscopic analyses confirmed and characterized two compounds as (±)-licarin B (1) and stigmasterol (2) from O. fasciculata and P. silhetensis, respectively. Petroleum ether soluble fraction of O. fasciculata and the aqueous soluble fraction of P. silhetensis showed the lowest 50% lethal concentrations (1.41 and 1.94 μg/mL, respectively) in brine shrimp bioassay. Likewise, petroleum ether soluble fraction of O. fasciculata and aqueous soluble fraction of P. silhetensis showed the highest thrombolytic activity with 46.66% and 50.10% lyses of the clot, respectively. The methanol and dichloromethane soluble fractions of O. fasciculata reduced erythrocyte hemolysis by 64.03% and 37.08%, respectively, under hypotonic and heat-induced conditions, compared to 81.97% and 42.12% for standard acetylsalicylic acid. In antioxidant activity test, aqueous soluble fraction O. fasciculata (IC50 = 7.22 μg/mL) revealed promising antioxidant potentialities in comparison to standard butylated hydroxytoluene (IC50 = 21.20 μg/mL). In antibacterial screening, chloroform, and dichloromethane soluble fractions of P. silhetensis showed a mild antibacterial activity compared with the standard drug ciprofloxacin. Additionally, the molecular docking study corroborated the current in vitro findings, and the isolated two constituents had higher binding affinities toward epidermal growth factor receptor, tissue plasminogen activator, vFLIP-IKK gamma stapled peptide dimer, glutathione reductase, and dihydrofolate reductase enzyme than their corresponding standard drugs. In addition, the both isolated compounds exerted favorable pharmacokinetics (absorption, distribution, metabolism, excretion) and toxicological profiles with drug-like qualities in computational-based ADMET and drug likeliness analyses. The current research suggests that both plants have potential as a natural treatment for treating thrombosis, inflammation, and oxidative stress. However, more thorough research is required to thoroughly screen for phytochemicals and pinpoint the precise mechanisms of action of the bioactive metabolites derived from these plants against a broad range of molecular targets.

Discovery of , a First-in-Class and Orally Bioavailable PROTAC Degrader of the Androgen Receptor Targeting N-Terminal Domain for the Treatment of Prostate Cancer

We report small molecular PROTAC compounds targeting the androgen receptor N-terminal domain (AR-NTD), which were obtained by tethering AR-NTD antagonists and different classes of E3 ligase ligands through chemical linkers. A representative compound, BWA-522, effectively induces degradation of both AR-FL and AR-V7 and is more potent than the corresponding antagonist against prostate cancer (PC) cells in vitro. We have shown that the degradation of AR-FL and AR-V7 proteins by BWA-522 can suppress the expression of AR downstream proteins and induce PC cell apoptosis. BWA-522 achieves 40.5% oral bioavailability in mice and 69.3% in beagle dogs. In a LNCaP xenograft model study, BWA-522 was also proved to be an efficacious PROTAC degrader, resulting in 76% tumor growth inhibition after oral administration of a dose of 60 mg/kg. This study indicates that BWA-522 is a promising AR-NTD PROTAC for the treatment of AR-FL- and AR-V7-dependent tumors.

2B Determined: The Future of the Serotonin Receptor 2B in Drug Discovery

The cardiotoxicity associated with des-ethyl-dexfenfluramine (norDF) and related agonists of the serotonin receptor 2B (5-HT2B) has solidified the receptor's place as an "antitarget" in drug discovery. Conversely, a growing body of evidence has highlighted the utility of 5-HT2B antagonists for the treatment of pulmonary arterial hypertension (PAH), valvular heart disease (VHD), and related cardiopathies. In this Perspective, we summarize the link between the clinical failure of fenfluramine-phentermine (fen-phen) and the subsequent research on the role of 5-HT2B in disease progression, as well as the development of drug-like and receptor subtype-selective 5-HT2B antagonists. Such agents represent a promising class for the treatment of PAH and VHD, but their utility has been historically understudied due to the clinical disasters associated with 5-HT2B. Herein, it is our aim to examine the current state of 5-HT2B drug discovery, with an emphasis on the receptor's role in the central nervous system (CNS) versus the periphery.

Chemistry-intuitive explanation of graph neural networks for molecular property prediction with substructure masking

Graph neural networks (GNNs) have been widely used in molecular property prediction, but explaining their black-box predictions is still a challenge. Most existing explanation methods for GNNs in chemistry focus on attributing model predictions to individual nodes, edges or fragments that are not necessarily derived from a chemically meaningful segmentation of molecules. To address this challenge, we propose a method named substructure mask explanation (SME). SME is based on well-established molecular segmentation methods and provides an interpretation that aligns with the understanding of chemists. We apply SME to elucidate how GNNs learn to predict aqueous solubility, genotoxicity, cardiotoxicity and blood-brain barrier permeation for small molecules. SME provides interpretation that is consistent with the understanding of chemists, alerts them to unreliable performance, and guides them in structural optimization for target properties. Hence, we believe that SME empowers chemists to confidently mine structure-activity relationship (SAR) from reliable GNNs through a transparent inspection on how GNNs pick up useful signals when learning from data.

Design, synthesis, evaluation and optimization of potent IRAK4 inhibitors alleviating production of inflammatory cytokines in LPS-induced SIRS model

Interleukin-1 receptor associated kinase-4 (IRAK4) has emerged as a therapeutic target for inflammatory and autoimmune diseases. Through reversing the amide of CA-4948 and computer aided structure-activity relationship (SAR) studies, a series of IRAK4 inhibitors with oxazolo[4,5-b]pyridine scaffold were identified. Compound 32 showed improved potency (IC₅₀ = 43 nM) compared to CA-4948 (IC₅₀ = 115 nM), but suffered from hERG inhibition (IC₅₀ = 5.7 μM). Further optimization led to compound 42 with reduced inhibition of hERG (IC₅₀ > 30 μM) and 13-fold higher activity (IC₅₀ = 8.9 nM) than CA-4948. Importantly, compound 42 had favorable in vitro ADME and in vivo pharmacokinetic properties. Furthermore, compound 42 significantly reduced LPS-induced production of serum TNF-α and IL-6 cytokines in the mouse model. The overall profiles of compound 42 support it as a lead for the development of IRAK4 inhibitors for the treatment of inflammatory and autoimmune disorders.

Structural analysis of hERG channel blockers and the implications for drug design

The repolarizing current (I_kr) produced by the hERG potassium channel forms a major component of the cardiac action potential and blocking this current by small molecule drugs can lead to life-threatening cardiotoxicity. Understanding the mechanisms of drug-mediated hERG inhibition is essential to develop a second generation of safe drugs, with minimal cardiotoxic effects. Although various computational tools and drug design guidelines have been developed to avoid binding of drugs to the hERG pore domain, there are many other aspects that are still open for investigation. This includes the use computational modelling to study the implications of hERG mutations on hERG structure and trafficking, the interactions of hERG with hERG chaperone proteins and with membrane-soluble molecules, the mechanisms of drugs that inhibit hERG trafficking and drugs that rescue hERG mutations. The plethora of available experimental data regarding all these aspects can guide the construction of much needed robust computational structural models to study these mechanisms for the rational design of safe drugs.

Fragment Hopping-Based Design of Novel Biphenyl-DAPY Derivatives as Potent Non-Nucleoside Reverse Transcriptase Inhibitors Featuring Significantly Improved Anti-Resistance Efficacy

To enhance the anti-resistance efficacy of our previously reported non-nucleoside reverse transcriptase inhibitor (NNRTI) 4, a series of novel biphenyl-DAPY derivatives were developed using the fragment-hopping strategy. Most of the compounds 8a-v exhibited remarkably improved anti-HIV-1 potency. The most active compound 8r proved to be exceptionally potent against the wild-type HIV-1 (EC₅₀ = 2.3 nM) and five mutant strains, such as K103N (EC₅₀ = 8 nM) and E138K (EC₅₀ = 6 nM), significantly better than 4. The new DAPY analogue was 8-fold less cytotoxic and had a 17-fold higher selectivity index (CC₅₀ = 40.77 μM, SI > 17391) than etravirine and rilpivirine. Also, it displayed favorable pharmacokinetic properties with an oral bioavailability of 31.19% and weak sensitivity toward both CYP and hERG. No apparent acute toxicity (2 g/kg) and tissue damage occurred. These findings will further expand the possibility of successfully identifying biphenyl-DAPY analogues as highly potent, safe, and orally active NNRTIs for HIV treatment.

Picomolar inhibitor of reverse transcriptase featuring significantly improved metabolic stability

Considering the undesirable metabolic stability of our recently identified NNRTI 5 (t_1/2 = 96 min) in human liver microsomes, we directed our efforts to improve its metabolic stability by introducing a new favorable hydroxymethyl side chain to the C-5 position of pyrimidine. This strategy provided a series of novel methylol-biphenyl-diarylpyrimidines with excellent anti-HIV-1 activity. The best compound 9g was endowed with remarkably improved metabolic stability in human liver microsomes (t_1/2 = 2754 min), which was about 29-fold longer than that of 5 (t_1/2 = 96 min). This compound conferred picomolar inhibition of WT HIV-1 (EC₅₀ = 0.9 nmol/L) and low nanomolar activity against five clinically drug-resistant mutant strains. It maintained particularly low cytotoxicity (CC₅₀ = 264 μmol/L) and good selectivity (SI = 256,438). Molecular docking studies revealed that compound 9g exhibited a more stable conformation than 5 due to the newly constructed hydrogen bond of the hydroxymethyl group with E138. Also, compound 9g was characterized by good safety profiles. It displayed no apparent inhibition of CYP enzymes and hERG. The acute toxicity assay did not cause death and pathological damage in mice at a single dose of 2 g/kg. These findings paved the way for the discovery and development of new-generation anti-HIV-1 drugs.

Molecular dynamics, MMGBSA, and docking studies of natural products conjugated to tumor-targeted peptide for targeting BRAF V600E and MERTK receptors

Recent studies have revealed that MERTK and BRAF V600E receptors have been found to be over-expressed in several types of cancers including melanoma, making these receptors targets for drug design. In this study, we have designed novel peptide conjugates with the natural products vanillic acid, thiazole-2-carboxylic acid, cinnamic acid, theanine, and protocatechuic acid. Each of these compounds was conjugated with the tumor targeting peptide sequence TAASGVRSMH, known to bind to NG2 and target tumor neovasculature. We examined their binding affinities and stability with MERTK and BRAF V600E receptors using molecular docking and molecular dynamics studies. Compared to the neat compounds, the peptide conjugates displayed higher binding affinity toward both receptors. In the case of MERTK, the most stable complexes were formed with di-theaninate-peptide, vanillate-peptide, and thiazole-2-amido peptide conjugates and binding occurred in the hinge region. Additionally, it was discovered that the peptide alone also had high binding ability and stability with the MERTK receptor. In the case of BRAF V600E, the peptide conjugates of protocatechuate, vanillate and thiazole-2-amido peptide conjugates showed the formation of the most stable complexes and binding occurred in the ATP binding cleft. Further analysis revealed that the number of hydrogen bonds and hydrophobic interactions played a critical role in enhanced stability of the complexes. Docking studies also revealed that binding affinities for NG2 were similar to MERTK and higher for BRAF V600E. MMGBSA studies of the trajectories revealed that the protocatechuate-peptide conjugate showed the highest binding energy with BRAF V600E while the peptide-TAASGVRSMH showed the highest binding energy with MERTK. ADME studies revealed that each of the compounds showed medium to high permeability toward MDCK cells and were not hERG blockers. Furthermore, the conjugates were not CYP inhibitors or substrates, but they were found to be Pgp substrates. Our results indicated that the protocatechuate-TAASGVRSMH, thiazole-2-amido-TAASGVRSMH, and vanillate-TAASGVRSMH conjugates may be furthered developed for in vitro and in vivo studies as novel tumor targeting compounds for tumor cells over-expressing BRAF V600E, while di-theaninate-amido-TAASGVRSMH and thiazole-2-amido-TAASGVRSMH conjugates may be developed for targeting MERTK receptors. These studies provide insight into the molecular interactions of natural product-peptide conjugates and their potential for binding to and targeting MERTK and BRAF V600E receptors in developing new therapeutics for targeting cancer.

Physicochemical QSAR analysis of hERG inhibition revisited: towards a quantitative potency prediction

In an earlier study (Didziapetris R & Lanevskij K (2016). J Comput Aided Mol Des. 30:1175-1188) we collected a database of publicly available hERG inhibition data for almost 6700 drug-like molecules and built a probabilistic Gradient Boosting classifier with a minimal set of physicochemical descriptors (log P, pK_a, molecular size and topology parameters). This approach favored interpretability over statistical performance but still achieved an overall classification accuracy of 75%. In the current follow-up work we expanded the database (provided in Supplementary Information) to almost 9400 molecules and performed temporal validation of the model on a set of novel chemicals from recently published lead optimization projects. Validation results showed almost no performance degradation compared to the original study. Additionally, we rebuilt the model using AFT (Accelerated Failure Time) learning objective in XGBoost, which accepts both quantitative and censored data often reported in protein inhibition studies. The new model achieved a similar level of accuracy of discerning hERG blockers from non-blockers at 10 µM threshold, which can be conceived as close to the performance ceiling for methods aiming to describe only non-specific ligand interactions with hERG. Yet, this model outputs quantitative potency values (IC₅₀) and is not tied to a particular classification cut-off. pIC₅₀ from patch-clamp measurements can be predicted with R² ≈ 0.4 and MAE < 0.5, which enables ligand ranking according to their expected potency levels. The employed approach can be valuable for quantitative modeling of various ADME and drug safety endpoints with a high prevalence of censored data.

P-Glycoprotein-Mediated Pharmacokinetic Interactions Increase Pimozide hERG Channel Inhibition

Pimozide, an antipsychotic drug, is a potent inhibitor of the hERG channel. A case of death due to cardiac arrest has been reported in a boy who received pimozide together with sertraline and aripiprazole. In this study, we focused on drug-drug interactions and investigated the relationships between transporter-mediated intracellular accumulation and the hERG inhibitory effect of pimozide. The accumulation of pimozide in cardiomyocyte-derived AC16 cells was significantly increased by sertraline and aripiprazole, which are thought to have a P-glycoprotein (P-gp) inhibitory effect, and under P-gp siRNA conditions. These results suggest P-gp inhibition increases pimozide accumulation in AC16 cells. We introduced the hERG plasmid into AC16 cells and investigated the concentration-dependent hERG inhibitory effect of pimozide from within AC16 cells. Addition of 10 nM or more pimozide significantly inhibited the hERG current with concentration dependence. These results indicate P-gp-mediated pharmacokinetic interaction increases pimozide accumulation in AC16 cells, and the subsequent elevated pimozide levels within the cells may result in an increased risk of hERG channel inhibition. Our present study calls attention to the risks associated with the combined use of cardiotoxic P-gp substrate(s) and P-gp inhibitory medicines.

Novel TYK2 Inhibitors with an N-(Methyl-d 3)pyridazine-3-carboxamide Skeleton for the Treatment of Autoimmune Diseases

Tyrosine kinase 2 (TYK2) mediates the interleukin-23 (IL-23), IL-12, and type I interferon (IFN)-driven signal responses that are critical in autoimmune diseases. Here, a series of novel derivatives with an N-(methyl-d 3)pyridazine-3-carboxamide skeleton that bind to the TYK2 pseudokinase domain were designed, synthesized, and evaluated. Among them, compound 30 demonstrated more excellent inhibitory potency against STAT3 phosphorylation than the positive control deucravacitinib. In addition to JAK isoform selectivity, compound 30 exhibited good in vivo and in vitro pharmacokinetic properties. Furthermore, compound 30 was orally highly effective in both IL-23-driven acanthosis and anti-CD40-induced colitis models. Together, these findings support compound 30 as a promising candidate for therapeutic applications in autoimmune diseases.

Ligand-based prediction of hERG-mediated cardiotoxicity based on the integration of different machine learning techniques

Drug-induced cardiotoxicity is a common side effect of drugs in clinical use or under postmarket surveillance and is commonly due to off-target interactions with the cardiac human-ether-a-go-go-related (hERG) potassium channel. Therefore, prioritizing drug candidates based on their hERG blocking potential is a mandatory step in the early preclinical stage of a drug discovery program. Herein, we trained and properly validated 30 ligand-based classifiers of hERG-related cardiotoxicity based on 7,963 curated compounds extracted by the freely accessible repository ChEMBL (version 25). Different machine learning algorithms were tested, namely, random forest, K-nearest neighbors, gradient boosting, extreme gradient boosting, multilayer perceptron, and support vector machine. The application of 1) the best practices for data curation, 2) the feature selection method VSURF, and 3) the synthetic minority oversampling technique (SMOTE) to properly handle the unbalanced data, allowed for the development of highly predictive models (BAMAX = 0.91, AUCMAX = 0.95). Remarkably, the undertaken temporal validation approach not only supported the predictivity of the herein presented classifiers but also suggested their ability to outperform those models commonly used in the literature. From a more methodological point of view, the study put forward a new computational workflow, freely available in the GitHub repository (https://github.com/PDelre93/hERG-QSAR), as valuable for building highly predictive models of hERG-mediated cardiotoxicity.

hERG Blockade Prediction by Combining Site Identification by Ligand Competitive Saturation and Physicochemical Properties

Human ether-a-go-go-related gene (hERG) potassium channel is well-known contributor to drug-induced cardiotoxicity and therefore an extremely important target when performing safety assessments of drug candidates. Ligand-based approaches in connection with quantitative structure active relationships (QSAR) analyses have been developed to predict hERG toxicity. Availability of the recent published cryogenic electron microscopy (cryo-EM) structure for the hERG channel opened the prospect for using structure-based simulation and docking approaches for hERG drug liability predictions. In recent time, the idea of combining structure- and ligand-based approaches for modeling hERG drug liability has gained momentum offering improvements in predictability when compared to ligand-based QSAR practices alone. The present article demonstrates uniting the structure-based SILCS (site-identification by ligand competitive saturation) approach in conjunction with physicochemical properties to develop predictive models for hERG blockade. This combination leads to improved model predictability based on Pearson's R and percent correct (represents rank-ordering of ligands) metric for different validation sets of hERG blockers involving diverse chemical scaffold and wide range of pIC50 values. The inclusion of the SILCS structure-based approach allows determination of the hERG region to which compounds bind and the contribution of different chemical moieties in the compounds to blockade, thereby facilitating the rational ligand design to minimize hERG liability.

Development of fluorine-substituted NH2-biphenyl-diarylpyrimidines as highly potent non-nucleoside reverse transcriptase inhibitors: Boosting the safety and metabolic stability

Our recent studies for nonnucleoside reverse transcriptase inhibitors identified a highly potent compound JK-4b against WT HIV-1 (EC₅₀ = 1.0 nmol/L), but the poor metabolic stability in human liver microsomes (t _1/2 = 14.6 min) and insufficient selectivity (SI = 2059) with high cytotoxicity (CC₅₀ = 2.08 μmol/L) remained major issues associated with JK-4b. The present efforts were devoted to the introduction of fluorine into the biphenyl ring of JK-4b, leading to the discovery of a novel series of fluorine-substituted NH₂-biphenyl-diarylpyrimidines with noticeable inhibitory activity toward WT HIV-1 strain (EC₅₀ = 1.8-349 nmol/L). The best compound 5t in this collection (EC₅₀ = 1.8 nmol/L, CC₅₀ = 117 μmol/L) was 32-fold in selectivity (SI = 66,443) compared to JK-4b and showed remarkable potency toward clinically multiple mutant strains, such as L100I, K103N, E138K, and Y181C. The metabolic stability of 5t was also significantly improved (t _1/2 = 74.52 min), approximately 5-fold higher than JK-4b in human liver microsomes (t _1/2 = 14.6 min). Also, 5t possessed good stability in both human and monkey plasma. No significant in vitro inhibition effect toward CYP enzyme and hERG was observed. The single-dose acute toxicity test did not induce mice death or obvious pathological damage. These findings pave the way for further development of 5t as a drug candidate.

Application of Pharmacokinetic Prediction Platforms in the Design of Optimized Anti-Cancer Drugs

Cancer is the second most common cause of death in the United States, accounting for 602,350 deaths in 2020. Cancer-related death rates have declined by 27% over the past two decades, partially due to the identification of novel anti-cancer drugs. Despite improvements in cancer treatment, newly approved oncology drugs are associated with increased toxicity risk. These toxicities may be mitigated by pharmacokinetic optimization and reductions in off-target interactions. As such, there is a need for early-stage implementation of pharmacokinetic (PK) prediction tools. Several PK prediction platforms exist, including pkCSM, SuperCypsPred, Pred-hERG, Similarity Ensemble Approach (SEA), and SwissADME. These tools can be used in screening hits, allowing for the selection of compounds were reduced toxicity and/or risk of attrition. In this short commentary, we used PK prediction tools in the optimization of mitogen activated extracellular signal-related kinase kinase 1 (MEK1) inhibitors. In doing so, we identified MEK1 inhibitors with retained activity and optimized predictive PK properties, devoid of hERG inhibition. These data support the use of publicly available PK prediction platforms in early-stage drug discovery to design safer drugs.

New Phenylglycinamide Derivatives with Hybrid Structure as Candidates for New Broad-Spectrum Anticonvulsants

In the present study, a focused combinatorial chemistry approach was applied to merge structural fragments of well-known TRPV1 antagonists with a potent anticonvulsant lead compound, KA-104, that was previously discovered by our group. Consequently, a series of 22 original compounds has been designed, synthesized, and characterized in the in vivo and in vitro assays. The obtained compounds showed robust in vivo antiseizure activity in the maximal electroshock (MES) test and in the 6 Hz seizure model (using both 32 and 44 mA current intensities). The most potent compounds 53 and 60 displayed the following pharmacological profile: ED₅₀ = 89.7 mg/kg (MES), ED₅₀ = 29.9 mg/kg (6 Hz, 32 mA), ED₅₀ = 68.0 mg/kg (6 Hz, 44 mA), and ED₅₀ = 73.6 mg/kg (MES), ED₅₀ = 24.6 mg/kg (6 Hz, 32 mA), and ED₅₀ = 56.3 mg/kg (6 Hz, 44 mA), respectively. Additionally, 53 and 60 were effective in the ivPTZ seizure threshold and had no influence on the grip strength and body temperature in mice. The in vitro binding and functional assays indicated a multimodal mechanism of action for 53 and 60. These molecules, beyond TRPV1 antagonism, inhibited calcium currents and fast sodium currents in patch-clamp assays. Further studies proved beneficial in vitro ADME-Tox properties for 53 and 60 (i.e., high metabolic stability, weak influence on CYPs, no neurotoxicity, etc.). Overall, 53 and 60 seem to be interesting candidates for future preclinical development in epilepsy and pain indications due to their interaction with the TRPV1 channel.

Structure-Based Discovery of Novel NH2-Biphenyl-Diarylpyrimidines as Potent Non-Nucleoside Reverse Transcriptase Inhibitors with Significantly Improved Safety: From NH2-Naphthyl-Diarylpyrimidine to NH2-Biphenyl-Diarylpyrimidine

Results from recently completed studies suggested that the NH₂-naphthyl-diarylpyrimidine JX-7 displayed remarkable inhibitory activity against wild-type HIV-1 (EC₅₀ = 5 nM) and numerous clinically observed variants in MT-4 cells; however, its high cytotoxicity (CC₅₀ = 19 μM) precluded its further development as a clinical candidate. One approach we took to improve the safety involved replacing the naphthyl of JX-7 with biphenyl to provide a series of novel NH₂-biphenyl-DAPYs. Investigation of the structure-activity relationships (SARs) led to the identification of 4ab, a potent NNRTI with significantly reduced cytotoxicity (CC₅₀ = 120 μM), approximately 6-fold lower than JX-7, which maintained remarkable anti-HIV-1 activity against wild-type HIV-1 (EC₅₀ = 1.9 nM) and multiple mutant strains simultaneously. Also, 4ab displayed weak CYP sensitivity, little inhibition of hERG, and no apparent in vivo acute toxicity. These promising results demonstrate that 4ab can be used as a drug candidate for HIV-1 therapy.

Structure-based design of CDC42 effector interaction inhibitors for the treatment of cancer

CDC42 family GTPases (RHOJ, RHOQ, CDC42) are upregulated but rarely mutated in cancer and control both the ability of tumor cells to invade surrounding tissues and the ability of endothelial cells to vascularize tumors. Here, we use computer-aided drug design to discover a chemical entity (ARN22089) that has broad activity against a panel of cancer cell lines, inhibits S6 phosphorylation and MAPK activation, activates pro-inflammatory and apoptotic signaling, and blocks tumor growth and angiogenesis in 3D vascularized microtumor models (VMT) in vitro. Additionally, ARN22089 has a favorable pharmacokinetic profile and can inhibit the growth of BRAF mutant mouse melanomas and patient-derived xenografts in vivo. ARN22089 selectively blocks CDC42 effector interactions without affecting the binding between closely related GTPases and their downstream effectors. Taken together, we identify a class of therapeutic agents that influence tumor growth by modulating CDC42 signaling in both the tumor cell and its microenvironment.

High-Throughput Chemical Screening and Structure-Based Models to Predict hERG Inhibition

Simple Summary

Cardiovascular disease is the leading cause of death for people of most ethnicities in the United States. The human ether-a-go-go-related gene (hERG) potassium channel plays a pivotal role in cardiac rhythm regulation, and cardiotoxicity associated with hERG inhibition by drug molecules and environmental chemicals is a major public health concern. An evaluation of the effect of environmental chemicals on hERG channel function can help inform the potential public health risks of these compounds. To assess the cardiotoxic effect of diverse drugs and environmental compounds, the Tox21 federal research program has screened a collection of 9667 chemicals for inhibitory activity against the hERG channel. A set of molecular descriptors covering physicochemical and structural properties of chemicals, self-organizing maps, and hierarchical clustering were applied to characterize the chemicals inhibiting hERG. Machine learning approaches were applied to build robust statistical models that can predict the probability of any new chemical to cause cardiotoxicity via this mechanism.

Abstract

Chemical inhibition of the human ether-a -go-go-related gene (hERG) potassium channel leads to a prolonged QT interval that can contribute to severe cardiotoxicity. The adverse effects of hERG inhibition are one of the principal causes of drug attrition in clinical and pre-clinical development. Preliminary studies have demonstrated that a wide range of environmental chemicals and toxicants may also inhibit the hERG channel and contribute to the pathophysiology of cardiovascular (CV) diseases. As part of the US federal Tox21 program, the National Center for Advancing Translational Science (NCATS) applied a quantitative high throughput screening (qHTS) approach to screen the Tox21 library of 10,000 compounds (~7871 unique chemicals) at 14 concentrations in triplicate to identify chemicals perturbing hERG activity in the U2OS cell line thallium flux assay platform. The qHTS cell-based thallium influx assay provided a robust and reliable dataset to evaluate the ability of thousands of drugs and environmental chemicals to inhibit hERG channel protein, and the use of chemical structure-based clustering and chemotype enrichment analysis facilitated the identification of molecular features that are likely responsible for the observed hERG activity. We employed several machine-learning approaches to develop QSAR prediction models for the assessment of hERG liabilities for drug-like and environmental chemicals. The training set was compiled by integrating hERG bioactivity data from the ChEMBL database with the Tox21 qHTS thallium flux assay data. The best results were obtained with the random forest method (~92.6% balanced accuracy). The data and scripts used to generate hERG prediction models are provided in an open-access format as key in vitro and in silico tools that can be applied in a translational toxicology pipeline for drug development and environmental chemical screening.

Molecular modeling in cardiovascular pharmacology: Current state of the art and perspectives

Molecular modeling in pharmacology is a promising emerging tool for exploring drug interactions with cellular components. Recent advances in molecular simulations, big data analysis, and artificial intelligence (AI) have opened new opportunities for rationalizing drug interactions with their pharmacological targets. Despite the obvious utility and increasing impact of computational approaches, their development is not progressing at the same speed in different fields of pharmacology. Here, we review current in silico techniques used in cardiovascular diseases (CVDs), cardiological drug discovery, and assessment of cardiotoxicity. In silico techniques are paving the way to a new era in cardiovascular medicine, but their use somewhat lags behind that in other fields.

TSSF-hERG: A machine-learning-based hERG potassium channel-specific scoring function for chemical cardiotoxicity prediction

The human ether-à-go-go-related gene (hERG) encodes the Kv11.1 voltage-gated potassium ion (K⁺) channel that conducts the rapidly activating delayed rectifier current (I_Kr) in cardiomyocytes to regulate the repolarization process. Some drugs, as blockers of hERG potassium channels, cannot be marketed due to prolonged QT intervals, as well known as cardiotoxicity. Predetermining the binding affinity values between drugs and hERG through in silico methods can greatly reduce the time and cost required for experimental verification. In this study, we collected 9,215 compounds with AutoDock Vina's docking structures as training set, and collected compounds from four references as test sets. A series of models for predicting the binding affinities of hERG blockers were built based on five machine learning algorithms and combinations of interaction features and ligand features. The model built by support vector regression (SVR) using the combination of all features achieved the best performance on both tenfold cross-validation and external verification, which was selected and named as TSSF-hERG (target-specific scoring function for hERG). TSSF-hERG is more accurate than the classic scoring function of AutoDock Vina and the machine-learning-based generic scoring function RF-Score, with a Pearson's correlation coefficient (Rp) of 0.765, a Spearman's rank correlation coefficient (Rs) of 0.757, a root-mean-square error (RMSE) of 0.585 in a tenfold cross-validation study. All results demonstrated that TSSF-hERG would be useful for improving the power of binding affinity prediction between hERG and compounds, which can be further used for prediction or virtual screening of the hERG-related cardiotoxicity of drug candidates.

Path4Drug: Data Science Workflow for Identification of Tissue-Specific Biological Pathways Modulated by Toxic Drugs

The early prediction of drug adverse effects is of great interest to pharmaceutical research, as toxicity is one of the leading reasons for drug attrition. Understanding the cell signaling and regulatory pathways affected by a drug candidate is crucial to the study of drug toxicity. In this study, we present a computational technique that employs the propagation of drug-protein interactions to connect compounds to biological pathways. Target profiles for drugs were built by retrieving drug target proteins from public repositories such as ChEMBL, DrugBank, IUPHAR, PharmGKB, and TTD. Subsequent enrichment test of the protein pool using Reactome revealed potential pathways affected by the drugs. Furthermore, an optional tissue filter utilizing the Human Protein Atlas was applied to identify tissue-specific pathways. The analysis pipeline was implemented in an open-source KNIME workflow called Path4Drug to allow automated data retrieval and reconstruction for any given drug present in ChEMBL. The pipeline was applied to withdrawn drugs and cardio- and hepatotoxic drugs with black box warnings to identify biochemical pathways they affect and to find pathways that can be potentially connected to the toxic events. To complement this approach, drugs used in cardiac therapy without any record of toxicity were also analyzed. The results provide already known associations as well as a large amount of additional potential connections. Consequently, our approach can link drugs to biological pathways by leveraging big data available in public resources. The developed tool is openly available and modifiable to support other systems biology analyses.

Structure-Based Prediction of hERG-Related Cardiotoxicity: A Benchmark Study

Drug-induced blockade of the human ether-à-go-go-related gene (hERG) channel is today considered the main cause of cardiotoxicity in postmarketing surveillance. Hence, several ligand-based approaches were developed in the last years and are currently employed in the early stages of a drug discovery process for in silico cardiac safety assessment of drug candidates. Herein, we present the first structure-based classifiers able to discern hERG binders from nonbinders. LASSO regularized support vector machines were applied to integrate docking scores and protein–ligand interaction fingerprints. A total of 396 models were trained and validated based on: (i) high-quality experimental bioactivity information returned by 8337 curated compounds extracted from ChEMBL (version 25) and (ii) structural predictor data. Molecular docking simulations were performed using GLIDE and GOLD software programs and four different hERG structural models, namely, the recently published structures obtained by cryoelectron microscopy (PDB codes: 5VA1 and 7CN1) and two published homology models selected for comparison. Interestingly, some classifiers return performances comparable to ligand-based models in terms of area under the ROC curve (AUC_MAX = 0.86 ± 0.01) and negative predictive values (NPV_MAX = 0.81 ± 0.01), thus putting forward the herein proposed computational workflow as a valuable tool for predicting hERG-related cardiotoxicity without the limitations of ligand-based models, typically affected by low interpretability and a limited applicability domain. From a methodological point of view, our study represents the first example of a successful integration of docking scores and protein–ligand interaction fingerprints (IFs) through a support vector machine (SVM) LASSO regularized strategy. Finally, the study highlights the importance of using hERG structural models accounting for ligand-induced fit effects and allowed us to select the best-performing protein conformation (made available in the Supporting Information, SI) to be employed for a reliable structure-based prediction of hERG-related cardiotoxicity.

Discovery of Novel Dihydrothiopyrano[4,3-d]pyrimidine Derivatives as Potent HIV-1 NNRTIs with Significantly Reduced hERG Inhibitory Activity and Improved Resistance Profiles

Enlightened by the available structural biology information, a novel series of dihydrothiopyrano[4,3-d]pyrimidine derivatives were rationally designed via scaffold hopping and molecular hybridization strategies. Notably, compound 20a yielded exceptionally potent antiviral activities (EC50 = 4.44-54.5 nM) against various HIV-1 strains and improved resistance profiles (RF = 0.5-5.6) compared to etravirine and rilpivirine. Meanwhile, 20a exhibited reduced cytotoxicity (CC50 = 284 μM) and higher SI values (SI = 5210-63992). Molecular dynamics simulations were performed to rationalize the distinct resistance profiles. Besides, 20a displayed better solubility (sol. = 12.8 μg/mL) and no significant inhibition of the main CYP enzymes. Furthermore, 20a was characterized for prominent metabolic stability and in vivo safety properties. Most importantly, the hERG inhibition profile of 20a (IC50 = 19.84 μM) was a remarkable improvement. Overall, 20a possesses huge potential to serve as a promising drug candidate due to its excellent potency, low toxicity, and favorable drug-like properties.

Quinazolinone dimers as a potential new class of safer Kv1 inhibitors: Overcoming hERG, sodium and calcium channel affinities

The discovery of more selective and safer voltage-gated potassium channel blockers is an extremely demanding approach. Designing selective Kv1.5 inhibitors is very challenging as only limited data is available on this target due to a lacking crystal structure for this ion channel receptor. Herein, we synthesized a series of 21 novel quinazolinone dimers 3a-i, 5a-i and 10a-c. We tried to avoid structural features responsible for non-selectivity and for most potassium channel blockers' side effects in our design. In contrast to other works, which lack investigation over wide ranges of potassium and sodium channels, we screened the inhibitory activity of our synthesized compounds over multiple voltage-gated potassium channels, including six different human Kv1 channel subtypes Kv1.1, Kv1.2, Kv1.3, Kv1.4, Kv1.5 and Kv1.6 channels as well as Kv2.1, Kv3.1, Kv4.3, Kv7.2, Kv7.3, Kv10.1, hERG, and Shaker IR. Moreover, these compounds' selectivity was investigated on sodium channels Nav1.2, Nav1.4 and Nav1.5 and calcium channels Cav3.1-Cav3.3. The results revealed two compounds (3a and 3e) with low micromolar Kv1.5 inhibition activity with EC₅₀ values of 5.1 ± 0.9 µM and 12.5 ± 1.1 µM, respectively. However, at higher concentrations, they also showed inhibitory activity on Kv1.3 and Kv1.1 channels. This might be due to structural similarities between these three Kv1 channel isoforms. Compound 3a shows a slight preference for Kv1.5. Interestingly, they lack any activity on other potassium channels (including hERG), sodium channels, and calcium channels. Our findings recommend quinazolinone dimers with ethylene linker as a potential new class of safer Kv1 inhibitors and a good start for designing more selective and potent Kv1.5 inhibitors.

Molecular Dynamics-Derived Pharmacophore Model Explaining the Nonselective Aspect of KV10.1 Pore Blockers

The K_V10.1 voltage-gated potassium channel is highly expressed in 70% of tumors, and thus represents a promising target for anticancer drug discovery. However, only a few ligands are known to inhibit K_V10.1, and almost all also inhibit the very similar cardiac hERG channel, which can lead to undesirable side-effects. In the absence of the structure of the K_V10.1–inhibitor complex, there remains the need for new strategies to identify selective K_V10.1 inhibitors and to understand the binding modes of the known K_V10.1 inhibitors. To investigate these binding modes in the central cavity of K_V10.1, a unique approach was used that allows derivation and analysis of ligand–protein interactions from molecular dynamics trajectories through pharmacophore modeling. The final molecular dynamics-derived structure-based pharmacophore model for the simulated K_V10.1–ligand complexes describes the necessary pharmacophore features for K_V10.1 inhibition and is highly similar to the previously reported ligand-based hERG pharmacophore model used to explain the nonselectivity of K_V10.1 pore blockers. Moreover, analysis of the molecular dynamics trajectories revealed disruption of the π–π network of aromatic residues F359, Y464, and F468 of K_V10.1, which has been reported to be important for binding of various ligands for both K_V10.1 and hERG channels. These data indicate that targeting the K_V10.1 channel pore is also likely to result in undesired hERG inhibition, and other potential binding sites should be explored to develop true K_V10.1-selective inhibitors as new anticancer agents.

1-Aminomethyl SAR in a novel series of flavagline-inspired eIF4A inhibitors: Effects of amine substitution on cell potency and in vitro PK properties

Flavaglines such as silvestrol (1) and rocaglamide (2) constitute an interesting class of natural products with promising anticancer activities. Their mode of action is based on inhibition of eukaryotic initiation factor 4A (eIF4A) dependent translation through formation of a stable ternary complex with eIF4A and mRNA, thus blocking ribosome scanning. Herein we describe initial SAR studies in a novel series of 1-aminomethyl substituted flavagline-inspired eIF4A inhibitors. We discovered that a variety of N-substitutions at the 1-aminomethyl group are tolerated, making this position pertinent for property and ADME profile tuning. The findings presented herein are relevant to future drug design efforts towards novel eIF4A inhibitors with drug-like properties.

Effect of Voacamine upon inhibition of hypoxia induced fatty acid synthesis in a rat model of methyln-nitrosourea induced mammary gland carcinoma

BACKGROUND

In the present study, fatty acid synthesis is targeted to combat mammary gland carcinoma by activating prolyl hydroxylase-2 with Voacamine alone and in combination with Tamoxifen. It was hypothesized that the activation of prolyl hydroxylase-2 would inhibit the hypoxia-induced fatty acid synthesis and mammary gland carcinoma. Mammary gland carcinoma was induced with a single dose administration of N-methyl-N-nitrosourea (50 mg/kg,i.p.) and treatment with Voacamine and Tamoxifen 15 days after carcinogen administration.

RESULTS

At the end of the study, hemodynamic profiling of animals was recorded to assess the cardiotoxic potential of the drug. Blood serum was separated and subjected to nuclear magnetic resonance spectroscopy. Carmine staining and histopathology of mammary gland tissue were performed to evaluate the anti-angiogenic potential of the drug. The antioxidant potential of the drug was measured with antioxidant markers. Western blotting was performed to study the effect of the drug at the molecular level.

CONCLUSION

Results of the study have shown that Voacamine treatment stopped further decrease in body weight of experimental animals. The hemodynamic study evidenced that Voacamine at a low dose is safe in cardiac patients. Microscopic evaluation of mammary gland tissue documented the anti-angiogenic potential of Voacamine and Tamoxifen therapy. Perturbed serum metabolites were also restored to normal along with antioxidant markers. Immunoblotting of mammary gland tissue also depicted restoration of proteins of the hypoxic and fatty acid pathway. Conclusively, Voacamine and its combination with Tamoxifen activated prolyl hydroxylase-2 to combat mammary gland carcinoma.

Overcoming challenges of HERG potassium channel liability through rational design: Eag1 inhibitors for cancer treatment

Two decades of research have proven the relevance of ion channel expression for tumor progression in virtually every indication, and it has become clear that inhibition of specific ion channels will eventually become part of the oncology therapeutic arsenal. However, ion channels play relevant roles in all aspects of physiology, and specificity for the tumor tissue remains a challenge to avoid undesired effects. Eag1 (K_V 10.1) is a voltage-gated potassium channel whose expression is very restricted in healthy tissues outside of the brain, while it is overexpressed in 70% of human tumors. Inhibition of Eag1 reduces tumor growth, but the search for potent inhibitors for tumor therapy suffers from the structural similarities with the cardiac HERG channel, a major off-target. Existing inhibitors show low specificity between the two channels, and screenings for Eag1 binders are prone to enrichment in compounds that also bind HERG. Rational drug design requires knowledge of the structure of the target and the understanding of structure-function relationships. Recent studies have shown subtle structural differences between Eag1 and HERG channels with profound functional impact. Thus, although both targets' structure is likely too similar to identify leads that exclusively bind to one of the channels, the structural information combined with the new knowledge of the functional relevance of particular residues or areas suggests the possibility of selective targeting of Eag1 in cancer therapies. Further development of selective Eag1 inhibitors can lead to first-in-class compounds for the treatment of different cancers.

Pharmacological corrections of the mutant hERG channels by posaconazole

Properties of mutant human ether-à-go-go-related gene (hERG) channels can be modified by some antibiotics. However, the pharmacological effects of posaconazole on cardiomyocyte hERG channels remain unclear. Whole-cell patch clamping, western blotting and laser confocal scanning microscopy were used to evaluate the effects of posaconazole on wild-type (WT)-, A561V- and L539 fs/47-hERG channels expressed in human embryonic kidney (HEK) 293 cells. In electrophysiological experiments, HEK 293 cells were transiently co-transfected with equal amounts of WT-hERG, WT+A561 V-hERG and WT+L539 fs/47-hERG plasmids to mimic a heterozygous genotype. Posaconazole (30 μM) increased tail currents in cells expressing WT-hERG, WT+A561 V-hERG and WT+L539 fs/47-hERG by 82.65%, 147.72% and 134.73%, respectively, compared to controls. Posaconazole increased hERG protein expression in cells expressing WT-hERG, WT+A561 V-hERG and WT+L539 fs/47-hERG compared to controls condition as well as their trafficking to the cell membrane. To our knowledge, this is the first study to show that antifungal agent posaconazole rescues the mutant A561 V-hERG and L539 fs/47-hERG channels by altering the gating kinetics, enhancing the expression and trafficking of hERG channels. The results demonstrate that posaconazole could be a promising candidate for the prevention and treatment of long QT syndrome and other arrhythmia-related diseases.