hERG-related drug toxicity and models for predicting hERG liability and QT prolongation

Targeting decaprenylphosphoryl-β-D-ribose 2'-epimerase for Innovative Drug Development Against Mycobacterium Tuberculosis Drug-Resistant Strains

Tuberculosis (TB) remains a global health challenge with the emergence of drug-resistant Mycobacterium tuberculosis variants, necessitating innovative drug molecules. One potential target is the cell wall synthesis enzyme decaprenylphosphoryl-β-D-ribose 2'-epimerase (DprE1), crucial for virulence and survival. This study employed virtual screening of 111 Protein Data Bank (PDB) database molecules known for their inhibitory biological activity against DprE1 with known IC50 values. Six compounds, PubChem ID: 390820, 86287492, 155294899, 155522922, 162651615, and 162665075, exhibited promising attributes as drug candidates and validated against clinical trial inhibitors BTZ043, TBA-7371, PBTZ169, and OPC-167832. Concurrently, this research focused on DprE1 mutation effects using molecular dynamic simulations. Among the 10 mutations tested, C387N significantly influenced protein behavior, leading to structural alterations observed through root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), radius of gyration (Rg), and solvent-accessible surface area (SASA) analysis. Ligand 2 (ID: 390820) emerged as a promising candidate through ligand-based pharmacophore analysis, displaying enhanced binding compared with reference inhibitors. Molecular dynamic simulations highlighted ligand 2's interaction with the C387N mutation, reducing fluctuations, augmenting hydrogen bonding, and influencing solvent accessibility. These collective findings emphasize ligand 2's efficacy, particularly against severe mutations, in enhancing protein-ligand complex stability. Integrated computational and pharmacophore methodologies offer valuable insights into drug candidates and their interactions within intricate protein environments. This research lays a strategic foundation for targeted interventions against drug-resistant TB, highlighting ligand 2's potential for advanced drug development strategies.

Carbazole and tetrahydro-carboline derivatives as dopamine D3 receptor antagonists with the multiple antipsychotic-like properties

Dopamine D3 receptor (D3R) is implicated in multiple psychotic symptoms. Increasing the D3R selectivity over dopamine D2 receptor (D2R) would facilitate the antipsychotic treatments. Herein, novel carbazole and tetrahydro-carboline derivatives were reported as D3R selective ligands. Through a structure-based virtual screen, ZLG-25 (D3R Ki = 685 nmol/L; D2R Ki > 10,000 nmol/L) was identified as a novel D3R selective bitopic ligand with a carbazole scaffold. Scaffolds hopping led to the discovery of novel D3R-selective analogs with tetrahydro-β-carboline or tetrahydro-γ-carboline core. Further functional studies showed that most derivatives acted as hD3R-selective antagonists. Several lead compounds could dose-dependently inhibit the MK-801-induced hyperactivity. Additional investigation revealed that 23j and 36b could decrease the apomorphine-induced climbing without cataleptic reaction. Furthermore, 36b demonstrated unusual antidepressant-like activity in the forced swimming tests and the tail suspension tests, and alleviated the MK-801-induced disruption of novel object recognition in mice. Additionally, preliminary studies confirmed the favorable PK/PD profiles, no weight gain and limited serum prolactin levels in mice. These results revealed that 36b provided potential opportunities to new antipsychotic drugs with the multiple antipsychotic-like properties.

Selective Non-toxics Inhibitors Targeting DHFR for Tuberculosis and Cancer Therapy: Pharmacophore Generation and Molecular Dynamics Simulation

Dihydrofolate reductase (DHFR) is a crucial enzyme that catalyzes the conversion of folic acid. Its reserved properties and significance in both human (h-DHFR) and mycobacterium (mt-DHFR) make it a challenging target for developing drugs against cancer and bacterial infections. Although methotrexate (MTX) is commonly used for cancer therapy and bacterial infections, it has a toxic profile. In this study, we aimed to identify selective and non-toxic inhibitors against h-DHFR and mt-DHFR using an in silico approach. From a data set of 8 412 inhibitors, 11 compounds passed the toxicity and drug-likeness tests, and their interaction with h-DHFR and mt-DHFR was studied by performing molecular docking. To evaluate the inhibitory activity of the compounds against mt-DHFR, five known reference ligands and the natural ligand (dihydrofolate) were used to generate a pharmacophoric map. Two potential selective inhibitors for mt-DHFR and h-DHFR were selected for further investigation using molecular dynamics for 100 ns. As a result, BDBM18226 was identified as the best compound selective for mt-DHFR, non-toxic, with five features listed in the map, with a binding energy of -9.6 kcal/mol. BDBM50145798 was identified as a non-toxic selective compound with a better affinity than MTX for h-DHFR. Molecular dynamics of the two best ligands suggest that they provide more stable, compact, and hydrogen bond interactions with the protein. Our findings could significantly expand the chemical space for new mt-DHFR inhibitors and provide a non-toxic alternative toward h-DHFR for the respective treatment of tuberculosis and cancer therapy.

Facing Antitubercular Resistance: Identification of Potential Direct Inhibitors Targeting InhA Enzyme and Generation of 3D-pharmacophore Model by in silico Approach

Purpose

The enoyl-acyl carrier protein reductase (InhA) is one of the important key enzymes employed in mycolic acids biosynthesis pathway and an important component of mycobacterial cell walls. This enzyme has also been identified as major target of isoniazid drug, except that isoniazid needs to be activated first by the catalase peroxidase (KatG) protein to form the isonicotinoyl-NAD (INH-NAD) adduct that inhibits the action of InhA enzyme. However, this activation becomes more difficult and unreachable with the problem of mutation-related resistance caused mainly by acquired mutations in KatG and InhA protein. Our main interest in this study is to identify direct InhA inhibitors using computer-aided drug design.

Methods

Computer-aided drug design was used to solve this problem by applying three different approaches including mutation impact modelling, virtual screening and 3D-pharmacophore search.

Results

A total of 15 mutations were collected from the literature, then a 3D model was generated for each of them and their impact was predicted. Of the 15 mutations, 10 were found to be deleterious and have a direct effect on flexibility, stability and SASA of the protein. In virtual screening, from 1,000 similar INH-NAD analogues obtained by the similarity search method, 823 compounds passed toxicity filter and drug likeness rules, which were then docked to the wild-type of InhA protein. Subsequently, 34 compounds with binding energy score better than that of INH-NAD were selected and docked against the 10 generated mutated models of InhA. Only three leads showed a lower binding affinity better than the reference. The 3D-pharmacophore model approach was used to identify the common features between those three compounds by generating a pharmacophoric map.

Conclusion

The result of this study may pave the way to develop more potent mutant-specific inhibitors to overcome this resistance.

Ensemble of structure and ligand-based classification models for hERG liability profiling

Drug-induced cardiotoxicity represents one of the most critical safety concerns in the early stages of drug development. The blockade of the human ether-à-go-go-related potassium channel (hERG) is the most frequent cause of cardiotoxicity, as it is associated to long QT syndrome which can lead to fatal arrhythmias. Therefore, assessing hERG liability of new drugs candidates is crucial to avoid undesired cardiotoxic effects. In this scenario, computational approaches have emerged as useful tools for the development of predictive models able to identify potential hERG blockers. In the last years, several efforts have been addressed to generate ligand-based (LB) models due to the lack of experimental structural information about hERG channel. However, these methods rely on the structural features of the molecules used to generate the model and often fail in correctly predicting new chemical scaffolds. Recently, the 3D structure of hERG channel has been experimentally solved enabling the use of structure-based (SB) strategies which may overcome the limitations of the LB approaches. In this study, we compared the performances achieved by both LB and SB classifiers for hERG-related cardiotoxicity developed by using Random Forest algorithm and employing a training set containing 12789 hERG binders. The SB models were trained on a set of scoring functions computed by docking and rescoring calculations, while the LB classifiers were built on a set of physicochemical descriptors and fingerprints. Furthermore, models combining the LB and SB features were developed as well. All the generated models were internally validated by ten-fold cross-validation on the TS and further verified on an external test set. The former revealed that the best performance was achieved by the LB model, while the model combining the LB and the SB attributes displayed the best results when applied on the external test set highlighting the usefulness of the integration of LB and SB features in correctly predicting unseen molecules. Overall, our predictive models showed satisfactory performances providing new useful tools to filter out potential cardiotoxic drug candidates in the early phase of drug discovery.

Recent Advances of DprE1 Inhibitors against Mycobacterium tuberculosis: Computational Analysis of Physicochemical and ADMET Properties

Decaprenylphosphoryl-β-d-ribose 2'-epimerase (DprE1) is a critical flavoenzyme in Mycobacterium tuberculosis, catalyzing a vital step in the production of lipoarabinomannan and arabinogalactan, both of which are essential for cell wall biosynthesis. Due to its periplasmic localization, DprE1 is a susceptible target, and several compounds with diverse scaffolds have been discovered that inhibit this enzyme, covalently or noncovalently. We evaluated a total of ∼1519 DprE1 inhibitors disclosed in the literature from 2009 to April 2022 by performing an in-depth analysis of physicochemical descriptors and absorption, distribution, metabolism, excretion, and toxicity (ADMET), to gain new insights into these properties in DprE1 inhibitors. Several molecular properties that should facilitate the design and optimization of future DprE1 inhibitors are described, allowing for the development of improved analogues targeting M. tuberculosis.

Toward Novel [18F]Fluorine-Labeled Radiotracers for the Imaging of α-Synuclein Fibrils

The accumulation of α-synuclein aggregates (α-syn) in the human brain is an occurrence common to all α-synucleinopathies. Non-invasive detection of these aggregates in a living brain with a target-specific radiotracer is not yet possible. We have recently discovered that the inclusion of a methylenedioxy group in the structure of diarylbisthiazole (DABTA)-based tracers improves binding affinity and selectivity to α-syn. Subsequently, complementary in silico modeling and machine learning (ML) of tracer–protein interactions were employed to predict surface sites and structure–property relations for the binding of the ligands. Based on this observation, we developed a small focused library of DABTAs from which 4-(benzo[d][1,3]dioxol-5-yl)-4′-(3-[¹⁸F]fluoro-4-methoxyphenyl)-2,2′-bithiazole [¹⁸F]d₂, 6-(4′-(3-[¹⁸F]fluoro-4-methoxyphenyl)-[2,2′-bithiazol]-4-yl)-[1,3]dioxolo[4,5-b]pyridine [¹⁸F]d₄, 4-(benzo [d][1,3]dioxol-5-yl)-4′-(6-[¹⁸F]fluoropyridin-3-yl)-2,2′-bithiazole [¹⁸F]d₆, and 6-(4′-(6-[¹⁸F]fluoropyridin-3-yl)-[2,2′-bithiazol]-4-yl)-[1,3]dioxolo[4,5-b]pyridine [¹⁸F]d₈ were selected based on their high binding affinity to α-syn and were further evaluated. Binding assay experiments carried out with the non-radioactive versions of the above tracers d₂, d₄, d₆, and d₈ showed high binding affinity of the ligands to α-syn: 1.22, 0.66, 1.21, and 0.10 nM, respectively, as well as excellent selectivity over β-amyloid plaques (Aβ) and microtubular tau aggregates (>200-fold selectivity). To obtain the tracers, their precursors were radiolabeled either via an innovative ruthenium-mediated (S_NAr) reaction ([¹⁸F]d₂ and [¹⁸F]d₄) or typical S_NAr reaction ([¹⁸F]d₆ and [¹⁸F]d₈) with moderate-to-high radiochemical yields (13% – 40%), and high molar activity > 60 GBq/μmol. Biodistribution experiments carried out with the tracers in healthy mice revealed that [¹⁸F]d₂ and [¹⁸F]d₄ showed suboptimal brain pharmacokinetics: 1.58 and 4.63 %ID/g at 5 min post-injection (p.i.), and 1.93 and 3.86 %ID/g at 60 min p.i., respectively. However, [¹⁸F]d₆ and [¹⁸F]d₈ showed improved brain pharmacokinetics: 5.79 and 5.13 %ID/g at 5 min p.i.; 1.75 and 1.07 %ID/g at 60 min p.i.; and 1.04 and 0.58 %ID/g at 120 min p.i., respectively. The brain uptake kinetics of [¹⁸F]d₆ and [¹⁸F]d₈ were confirmed in a dynamic PET study. Both tracers also showed no brain radiometabolites at 20 min p.i. in initial in vivo stability experiments carried out in healthy mice. [¹⁸F]d₈ seems very promising based on its binding properties and in vivo stability, thus encouraging further validation of its usefulness as a radiotracer for the in vivo visualization of α-syn in preclinical and clinical settings. Additionally, in silico and ML-predicted values correlated with the experimental binding affinity of the ligands.

Computational Simulations Highlight the IL2Rα Binding Potential of Polyphenol Stilbenes from Fenugreek

Widely used in global households, fenugreek is well known for its culinary and medicinal uses. The various reported medicinal properties of fenugreek are by virtue of the different natural phytochemicals present in it. Regarded as a promising target, interleukin 2 receptor subunit alpha (IL2Rα) has been shown to influence immune responses. In the present research, using in silico techniques, we have demonstrated the potential IL2Rα binding properties of three polyphenol stilbenes (desoxyrhaponticin, rhaponticin, rhapontigenin) from fenugreek. As the first step, molecular docking was performed to assess the binding potential of the fenugreek phytochemicals with IL2Rα. All three phytochemicals demonstrated interactions with active site residues. To confirm the reliability of our molecular docking results, 100 ns molecular dynamics simulations studies were undertaken. As discerned by the RMSD and RMSF analyses, IL2Rα in complex with the desoxyrhaponticin, rhaponticin, and rhapontigenin indicated stability. The RMSD analysis of the phytochemicals alone also demonstrated no significant structural changes. Based on the stable molecular interactions and comparatively slightly better MM/PBSA binding free energy, rhaponticin seems promising. Additionally, ADMET analysis performed for the stilbenes indicated that all of them obey the ADMET rules. Our computational study thus supports further in vitro IL2Rα binding studies on these stilbenes, especially rhaponticin.

Discovery of a new class of multi-target heterocycle piperidine derivatives as potential antipsychotics with pro-cognitive effect

A series of benzoisoxazoleylpiperidine derivatives were synthesized by using the multi-target strategies and their potent affinities for dopamine (DA), serotonin (5-HT) and human histamine H₃ receptors have been evaluated. Of these compounds, the promising candidate 4w displayed high affinities for D₂, D₃, 5-HT_1A, 5-HT_2A and H₃, a moderate affinity for 5-HT₆, negligible effects on the human ether-a-go-go-related gene (hERG) channel, low affinities for off-target receptors (5-HT_2C, adrenergic α₁ and H₁). In addition, the animal behavioral study revealed that, compared to risperidone, compound 4w significantly inhibited apomorphine-induced climbing and MK-801-induced movement behaviors with a high threshold for catalepsy and low liabilities for weight gain and hyperprolactinemia. Results from the conditioned avoidance response test and novel object recognition task demonstrated that 4w had pro-cognitive effects. Thus, the antipsychotic drug-like activities of 4w indicate that it may be a potential polypharmacological antipsychotic candidate drug.

Synthesis and biological evaluation of a new class of multi-target heterocycle piperazine derivatives as potential antipsychotics

In this study, we designed and synthesized a novel series of multi-receptor ligands as polypharmacological antipsychotic agents by using a multi-receptor affinity strategy. Among them, 3w combines a multi-receptor mechanism with high mixed affinities for D₂, 5-HT_1A, 5-HT_2A and H₃ receptors, and low efficacy at the off-target receptors (5-HT_2C, H₁ and α₁ receptor) and human ether-à-go-go-related gene (hERG) channel. In addition, compound 3w exhibits favorable antipsychotic drug-like activities in in vivo assessment. An animal behavioral study revealed that compound 3w significantly reverses apomorphine-induced climbing and MK-801-induced hyperactivity, and avoidance behavior in the CAR test, with a high threshold for catalepsy. Moreover, compound 3w demonstrates memory enhancement in a novel object recognition task and low liabilities for weight gain and hyperprolactinemia in a long-term metabolic adverse effects model. Thus, 3w was selected as an antipsychotic candidate for further development.

In this study, we designed and synthesized a novel series of multi-receptor ligands as polypharmacological antipsychotic agents by using a multi-receptor affinity strategy.

The Acid/Base Characterization of Molecules with Epigenetic Activity

The acidic and basic functional groups in a molecule strongly influence its physicochemical properties, affinity for a macromolecule, pharmacokinetics, and toxicity. For instance, basicity has been correlated with molecular promiscuity, hERG blockade, and phospholipidosis. Nonetheless, no systematic characterization of the acid/base profile of epigenomic databases has been reported. This study describes an analysis of the acidic ionization constant distribution of a library of 7820 compounds with reported activity against epigenetic targets. Furthermore, the epigenomics database's acid/base profile was compared to the reference libraries of food chemicals, natural products, and approved drugs. It was found that the acid/base profile of histone lysine demethylase ligands is more similar to previously approved drugs, and histone acetyltransferase ligands have acidic and basic functional groups largely found in food chemicals and natural products; this support the potential of these libraries for finding new epigenetic inhibitors.

Accumulation of TB-Active Compounds in Murine Organs Relevant to Infection by Mycobacterium tuberculosis

Tuberculosis (TB), the leading cause of death due to an infectious agent, requires prolonged and costly drug treatments. With the rise in incidence of MDR and XDR TB, newer more efficacious treatments which are better able to permeate into the deeper recesses of the human lung where bacteria reside are urgently required. To this end, two new promising drug candidates, the decoquinate derivative RMB041 and the phenoxazine PhX1, were assessed for their abilities to permeate into specific murine organs. In particular, PhX1 permeation into the lungs and heart was notably efficient, as reflected in the high relative AUC values of 9669 ± 120.2 min/nmol/mg and 12450 ± 45.2 min/nmol/mg for lung and heart tissue, respectively. However, neither compound maintained a free concentration in the lung which exceeded the compound’s respective MIC₉₀ values, indicating the importance of correcting for organ specific binding.

Synthesis and Antimicrobial Properties of a Ciprofloxacin and PAMAM-dendrimer Conjugate

Infections caused by bacteria resistant to antibiotics are an increasing problem. Multivalent antibiotics could be a solution. In the present study, a covalent conjugate between Ciprofloxacin and a G0-PAMAM dendrimer has been synthesized and tested against clinically relevant Gram-positive and Gram-negative bacteria. The conjugate has antimicrobial activity and there is a positive dendritic effect compared to Ciprofloxacin itself.

Synthesis and Biological Evaluation of Fused Tricyclic Heterocycle Piperazine (Piperidine) Derivatives As Potential Multireceptor Atypical Antipsychotics

Herein, a novel series of multireceptor ligands was developed as polypharmacological antipsychotic agents using the designed multiple ligand approach between dopamine receptors and serotonin receptors. Among them, compound 47 possessed unique pharmacological features, exhibiting high affinities for D₂, D₃, 5-HT_1A, 5-HT_2A, and 5-HT₆ receptors and low efficacy at the off-target receptors (5-HT_2C, histamine H₁, and adrenergic α₁ receptor). Compound 47 showed dose-dependent inhibition of apomorphine- and MK-801-induced motor behavior, and the conditioned avoidance response with low cataleptic effect. Moreover, compound 47 resulted nonsignificantly serum prolactin levels and weight gain change compared with risperidone. Additionally, compound 47 possessed a favorable pharmacokinetic profile with oral bioavailability of 58.8% in rats. Furthermore, compound 47 displayed procognition properties in a novel object recognition task in rats. Taken together, compound 47 may constitute a novel class of atypical antipsychotic drugs for schizophrenia.

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.

Computational analysis of calculated physicochemical and ADMET properties of protein-protein interaction inhibitors

The modulation of PPIs by low molecular weight chemical compounds, particularly by orally bioavailable molecules, would be very valuable in numerous disease indications. However, it is known that PPI inhibitors (iPPIs) tend to have properties that are linked to poor Absorption, Distribution, Metabolism, Excretion and Toxicity (ADMET) and in some cases to poor clinical outcomes. Previously reported in silico analyses of iPPIs have essentially focused on physicochemical properties but several other ADMET parameters would be important to assess. In order to gain new insights into the ADMET properties of iPPIs, computations were carried out on eight datasets collected from several databases. These datasets involve compounds targeting enzymes, GPCRs, ion channels, nuclear receptors, allosteric modulators, oral marketed drugs, oral natural product-derived marketed drugs and iPPIs. Several trends are reported that should assist the design and optimization of future PPI inhibitors, either for drug discovery endeavors or for chemical biology projects.

A k-nearest neighbor classification of hERG K(+) channel blockers

A series of 172 molecular structures that block the hERG K⁺ channel were used to develop a classification model where, initially, eight types of PaDEL fingerprints were used for k-nearest neighbor model development. A consensus model constructed using Extended-CDK, PubChem and Substructure count fingerprint-based models was found to be a robust predictor of hERG activity. This consensus model demonstrated sensitivity and specificity values of 0.78 and 0.61 for the internal dataset compounds and 0.63 and 0.54 for the external (PubChem) dataset compounds, respectively. This model has identified the highest number of true positives (i.e. 140) from the PubChem dataset so far, as compared to other published models, and can potentially serve as a basis for the prediction of hERG active compounds. Validating this model against FDA-withdrawn substances indicated that it may even be useful for differentiating between mechanisms underlying QT prolongation.

Multi-Organ toxicity demonstration in a functional human in vitro system composed of four organs

We report on a functional human model to evaluate multi-organ toxicity in a 4-organ system under continuous flow conditions in a serum-free defined medium utilizing a pumpless platform for 14 days. Computer simulations of the platform established flow rates and resultant shear stress within accepted ranges. Viability of the system was demonstrated for 14 days as well as functional activity of cardiac, muscle, neuronal and liver modules. The pharmacological relevance of the integrated modules were evaluated for their response at 7 days to 5 drugs with known side effects after a 48 hour drug treatment regime. The results of all drug treatments were in general agreement with published toxicity results from human and animal data. The presented phenotypic culture model exhibits a multi-organ toxicity response, representing the next generation of in vitro systems, and constitutes a step towards an in vitro "human-on-a-chip" assay for systemic toxicity screening.

Investigation of miscellaneous hERG inhibition in large diverse compound collection using automated patch-clamp assay

AIM

hERG potassium channels display miscellaneous interactions with diverse chemical scaffolds. In this study we assessed the hERG inhibition in a large compound library of diverse chemical entities and provided data for better understanding of the mechanisms underlying promiscuity of hERG inhibition.

METHODS

Approximately 300 000 compounds contained in Molecular Library Small Molecular Repository (MLSMR) library were tested. Compound profiling was conducted on hERG-CHO cells using the automated patch-clamp platform-IonWorks Quattro(™).

RESULTS

The compound library was tested at 1 and 10 μmol/L. IC50 values were predicted using a modified 4-parameter logistic model. Inhibitor hits were binned into three groups based on their potency: high (IC50<1 μmol/L), intermediate (1 μmol/L< IC50<10 μmol/L), and low (IC50>10 μmol/L) with hit rates of 1.64%, 9.17% and 16.63%, respectively. Six physiochemical properties of each compound were acquired and calculated using ACD software to evaluate the correlation between hERG inhibition and the properties: hERG inhibition was positively correlative to the physiochemical properties ALogP, molecular weight and RTB, and negatively correlative to TPSA.

CONCLUSION

Based on a large diverse compound collection, this study provides experimental evidence to understand the promiscuity of hERG inhibition. This study further demonstrates that hERG liability compounds tend to be more hydrophobic, high-molecular, flexible and polarizable.

microRNAs as pharmacogenomic biomarkers for drug efficacy and drug safety assessment

Much evidence has documented that microRNAs (miRNAs) play an important role in the modulation of interindividual variability in the production of drug metabolizing enzymes and transporters (DMETs) and nuclear receptors (NRs) through multidirectional interactions involving environmental stimuli/stressors, the expression of miRNA molecules and genetic polymorphisms. MiRNA expression has been reported to be affected by drugs and miRNAs themselves may affect drug metabolism and toxicity. In cancer research, miRNA biomarkers have been identified to mediate intrinsic and acquired resistance to cancer therapies. In drug safety assessment, miRNAs have been found associated with cardiotoxicity, hepatotoxicity and nephrotoxicity. This review article summarizes published studies to show that miRNAs can serve as early biomarkers for the evaluation of drug efficacy and drug safety.

A systematic review of the cardiotoxicity of methadone

Methadone is one of the most popular synthetic opioids in the world with some favorable properties making it useful both in the treatment of moderate to severe pain and for opioid addiction. Increased use of methadone has resulted in an increased prevalence of its toxicity, one aspect of which is cardiotoxicity. In this paper, we review the effects of methadone on the heart as well as cardiac concerns in some special situations such as pregnancy and childhood.

METHODS

We searched for the terms methadone, toxicity, poisoning, cardiotoxicity, heart, dysrhythmia, arrhythmia, QT interval prolongation, torsade de pointes, and Electrocardiogram (ECG) in bibliographical databases including TUMS digital library, PubMed, Scopus, and Google Scholar. This review includes relevant articles published between 2000 and 2013. The main cardiac effects of methadone include prolongation of QT interval and torsade de pointes. Other effects include changes in QT dispersion, pathological U waves, Taku-Tsubo syndrome (stress cardiomyopathy), Brugada-like syndrome, and coronary artery diseases. The aim of this paper is to inform physicians and health care staff about these adverse effects. Effectiveness of methadone in the treatment of pain and addiction should be weighed against these adverse effects and physicians should consider the ways to lessen such undesirable effects. This article presents some recommendations to prevent heart toxicity in methadone users.

Computer-based prediction of the drug proarrhythmic effect: problems, issues, known and suspected challenges

It is likely that computer modelling and simulations will become an element of comprehensive cardiac safety testing. Their role would be primarily the integration and the interpretation of previously gathered data. There are still unanswered questions and issues which we list and describe below. They include sources of data used for the development of the models as well as data utilized as input information, which can come from the in vitro studies and the quantitative structure-activity relationship models. The pharmacokinetics of the drugs in question play a crucial role as their active concentration should be considered, yet the question remains where is the right place to assess it. The pharmacodynamic angle includes complications coming from multiple drugs (i.e. active metabolites) acting in parallel as well as the type of interaction with (potentially) multiple affected channels. Once established, the model and the methodology of its use should be further validated, optimistically against individual data reported at the clinical level as the physiological, anatomical, and genetic parameters play a crucial role in the drug-triggered arrhythmia induction. All the abovementioned issues should be at least considered and-hopefully-resolved, to properly utilize the mathematical models for a cardiac safety assessment.

Nonclinical Safety and Toxicology

Nonclinical safety pharmacology and toxicology testing of drug candidates assess the potential adverse effects caused by the drug in relation to its intended use in humans. Hazards related to a drug have to be identified and the potential risks at the intended exposure have to be evaluated in comparison to the potential benefit of the drug. Preclinical safety is thus an integral part of drug discovery and drug development. It still causes significant attrition during drug development.Therefore, there is a need for smart selection of drug candidates in drug discovery including screening of important safety endpoints. In the recent years,there was significant progress in computational and in vitro technology allowing in silico assessment as well as high-throughput screening of some endpoints at very early stages of discovery. Despite all this progress, in vivo evaluation of drug candidates is still an important part to safety testing. The chapter provides an overview on the most important areas of nonclinical safety screening during drug discovery of small molecules.

Structural insight into the transmembrane segments 3 and 4 of the hERG potassium channel

The hERG (human ether-a-go-go related gene) potassium channel is a voltage-gated potassium channel containing an N-terminal domain, a voltage-sensor domain, a pore domain and a C-terminal domain. The transmembrane segment 4 (S4) is important for sensing changes of membrane potentials through positively charge residues. A construct containing partial S2-S3 linker, S3, S4 and the S4-S5 linker of the hERG channel was purified into detergent micelles. This construct exhibits good quality NMR spectrum when it was purified in lyso-myristoyl phosphatidylglycerol (LMPG) micelles. Structural study showed that S3 contains two short helices with a negatively charged surface. The S4 and S4-S5 linker adopt helical structures. The six positively charged residues in S4 localize at different sides, suggesting that they may have different functions in channel gating. Relaxation studies indicated that S3 is more flexible than S4. The boundaries of S3-S4 and S4-S4-S5 linker were identified. Our results provided structural information of the S3 and S4, which will be helpful to understand their roles in channel gating.

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

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

Experimentally validated HERG pharmacophore models as cardiotoxicity prediction tools

The goal of this study was to design, experimentally validate, and apply a virtual screening workflow to identify novel hERG channel blockers. The hERG channel is an important antitarget in drug development since cardiotoxic risks remain as a major cause of attrition. A ligand-based pharmacophore model collection was developed and theoretically validated. The seven most complementary and suitable models were used for virtual screening of in-house and commercially available compound libraries. From the hit lists, 50 compounds were selected for experimental validation through bioactivity assessment using patch clamp techniques. Twenty compounds inhibited hERG channels expressed in HEK 293 cells with IC50 values ranging from 0.13 to 2.77 μM, attesting to the suitability of the models as cardiotoxicity prediction tools in a preclinical stage.

Selective serotonin reuptake inhibitors and torsade de pointes: new concepts and new directions derived from a systematic review of case reports

OBJECTIVE

In the light of the recent United States Food and Drug Administration (FDA) warning to clinicians on using previously approved doses of citalopram because of the purported higher risk of torsade de pointes (TdP), we pursued the broader question: are selective serotonin reuptake inhibitor (SSRI) antidepressant agents as a group unsafe because they might induce QTc interval prolongation and TdP?

METHOD

We reviewed the literature and found only 15 case reports (6 of fluoxetine, 1 of sertraline and 8 of citalopram) of SSRI-associated QTc interval prolongation linking to TdP.

RESULTS

A total of 13 cases contained sufficient information for analysis. In the setting of TdP, QTc interval prolongation does not clearly relate to SSRI dose.

CONCLUSION

Applying conventional statistics as the FDA does may not be the best tool to study this phenomenon because SSRI-associated TdP is a very rare event and hence best understood as an 'extreme outlier'. Despite the limitations inherent in case report material, case reports on drug-associated QTc interval prolongation and TdP provide valuable information that should be considered along with other sources of information for clinical guidance.

Novel Bayesian classification models for predicting compounds blocking hERG potassium channels

AIM

A large number of drug-induced long QT syndromes are ascribed to blockage of hERG potassium channels. The aim of this study was to construct novel computational models to predict compounds blocking hERG channels.

METHODS

Doddareddy's hERG blockage data containing 2644 compounds were used, which divided into training (2389) and test (255) sets. Laplacian-corrected Bayesian classification models were constructed using Discovery Studio. The models were internally validated with the training set of compounds, and then applied to the test set for validation. Doddareddy's experimentally validated dataset with 60 compounds was used for external test set validation.

RESULTS

A Bayesian classification model considering the effects of four molecular properties (Mw, PPSA, ALogP and pKa_basic) as well as extended-connectivity fingerprints (ECFP_14) exhibited a global accuracy (91%), parameter sensitivity (90%) and specificity (92%) in the test set validation, and a global accuracy (58%), parameter sensitivity (61%) and specificity (57%) in the external test set validation.

CONCLUSION

The novel model is better than those in the literatures for predicting compounds blocking hERG channels, and can be used for large-scale prediction.

Lubiprostone: pharmacokinetic, pharmacodynamic, safety and regulatory aspects in the treatment of constipation-predominant irritable bowel syndrome

INTRODUCTION

Lubiprostone acts locally (apical membrane of human intestinal epithelial cells) as a highly selective type-2 chloride channel activator. It was approved in the USA for chronic idiopathic constipation (January 2006) and in women aged ≥ 18 years suffering from irritable bowel syndrome with constipation (IBS-C) (April 2008). So far, the only other pro-secretory medication approved in IBS-C and currently available in USA and Europe (since August and November 2012, respectively) is linaclotide.

AREAS COVERED

This review outlines the regulatory history, pharmacokinetic, pharmacodynamic and safety data in the treatment of IBS-C with a European perspective. It is based on publicly available data, namely, published literature, drug labels and the FDA's spontaneous reporting system.

EXPERT OPINION

Although interesting pharmacodynamic data suggest that lubiprostone may have additional mechanisms of action, its beneficial effects in IBS-C must be confirmed in the actual clinical scenario taking into account the new version of European Medicines Agency's guideline. This is especially important with regard to duration of studies (recommended to be at least 6 months) to adequately assess long-term sustained efficacy, withdrawal, rebound and safety. Further research is warranted in uncertain areas (i.e., males, pediatric and elderly patients). On the basis of current data, it is still too early to draw definite conclusions on the overall risk-benefit balance for IBS-C.

Stem cells and stem cell-derived tissues and their use in safety assessment

Toxicology has long relied on animal models in a tedious approach to understanding risk of exposure to an uncharacterized molecule. Stem cell-derived tissues can be made in high purity, quality, and quantity to enable a new approach to this problem. Currently, stem cell-derived tissues are primarily "generic" genetic backgrounds; the future will see the integration of various genetic backgrounds and complex three-dimensional models to create truly unique in vitro organoids. This minireview focuses on the state of the art of a number of stem cell-derived tissues and details their application in toxicology.

Antipsychotics and torsadogenic risk: signals emerging from the US FDA Adverse Event Reporting System database

Background

Drug-induced torsades de pointes (TdP) and related clinical entities represent a current regulatory and clinical burden.

Objective

As part of the FP7 ARITMO (Arrhythmogenic Potential of Drugs) project, we explored the publicly available US FDA Adverse Event Reporting System (FAERS) database to detect signals of torsadogenicity for antipsychotics (APs).

Methods

Four groups of events in decreasing order of drug-attributable risk were identified: (1) TdP, (2) QT-interval abnormalities, (3) ventricular fibrillation/tachycardia, and (4) sudden cardiac death. The reporting odds ratio (ROR) with 95 % confidence interval (CI) was calculated through a cumulative analysis from group 1 to 4. For groups 1+2, ROR was adjusted for age, gender, and concomitant drugs (e.g., antiarrhythmics) and stratified for AZCERT drugs, lists I and II (http://www.azcert.org, as of June 2011). A potential signal of torsadogenicity was defined if a drug met all the following criteria: (a) four or more cases in group 1+2; (b) significant ROR in group 1+2 that persists through the cumulative approach; (c) significant adjusted ROR for group 1+2 in the stratum without AZCERT drugs; (d) not included in AZCERT lists (as of June 2011).

Results

Over the 7-year period, 37 APs were reported in 4,794 cases of arrhythmia: 140 (group 1), 883 (group 2), 1,651 (group 3), and 2,120 (group 4). Based on our criteria, the following potential signals of torsadogenicity were found: amisulpride (25 cases; adjusted ROR in the stratum without AZCERT drugs = 43.94, 95 % CI 22.82–84.60), cyamemazine (11; 15.48, 6.87–34.91), and olanzapine (189; 7.74, 6.45–9.30).

Conclusions

This pharmacovigilance analysis on the FAERS found 3 potential signals of torsadogenicity for drugs previously unknown for this risk.

Electronic supplementary material

The online version of this article (doi:10.1007/s40264-013-0032-z) contains supplementary material, which is available to authorized users.

Preclinical safety profile of trastuzumab emtansine (T-DM1): mechanism of action of its cytotoxic component retained with improved tolerability

Trastuzumab emtansine (T-DM1) is the first antibody-drug conjugate (ADC) approved for patients with human epidermal growth factor receptor 2 (HER2)-positive metastatic breast cancer. The therapeutic premise of ADCs is based on the hypothesis that targeted delivery of potent cytotoxic drugs to tumors will provide better tolerability and efficacy compared with non-targeted delivery, where poor tolerability can limit efficacious doses. Here, we present results from preclinical studies characterizing the toxicity profile of T-DM1, including limited assessment of unconjugated DM1. T-DM1 binds primate ErbB2 and human HER2 but not the rodent homolog c-neu. Therefore, antigen-dependent and non-antigen-dependent toxicity was evaluated in monkeys and rats, respectively, in both single- and repeat-dose studies; toxicity of DM1 was assessed in rats only. T-DM1 was well tolerated at doses up to 40 mg/kg (~4400 μg DM1/m(2)) and 30 mg/kg (~ 6000 μg DM1/m(2)) in rats and monkeys, respectively. In contrast, DM1 was only tolerated up to 0.2mg/kg (1600 μg DM1/m(2)). This suggests that at least two-fold higher doses of the cytotoxic agent are tolerated in T-DM1, supporting the premise of ADCs to improve the therapeutic index. In addition, T-DM1 and DM1 safety profiles were similar and consistent with the mechanism of action of DM1 (i.e., microtubule disruption). Findings included hepatic, bone marrow/hematologic (primarily platelet), lymphoid organ, and neuronal toxicities, and increased numbers of cells of epithelial and phagocytic origin in metaphase arrest. These adverse effects did not worsen with chronic dosing in monkeys and are consistent with those reported in T-DM1-treated patients to date.

Methadone, QTc interval prolongation and torsade de pointes: Case reports offer the best understanding of this problem

We reviewed the literature and found 31 adult cases and 1 newborn case of methadone-associated QTc interval prolongation and/or torsade de pointes (TdP). Parametric statistics may not be useful in studying this issue because methadone-associated TdP is a very rare event and, hence, "an extreme outlier" consistent with scalable randomness. We may have to rely upon narrative medicine in the form of case reports with all its limitations and hazards to provide our best understanding. We report risk factors for methadone-associated QTc interval prolongation and TdP based on review of published case reports. We believe both drug manufacturers and the FDA would better serve our patients and inform clinicians if they more readily reported drug-induced outliers such as methadone-associated TdP using a case report format.

A chemogenomic analysis of ionization constants--implications for drug discovery

Chemogenomics methods seek to characterize the interaction between drugs and biological systems and are an important guide for the selection of screening compounds. The acid/base character of drugs has a profound influence on their affinity for the receptor, on their absorption, distribution, metabolism, excretion and toxicity (ADMET) profile and the way the drug can be formulated. In particular, the charge state of a molecule greatly influences its lipophilicity and biopharmaceutical characteristics. This study investigates the acid/base profile of human small-molecule drugs, chemogenomics datasets and screening compounds including a natural products set. We estimate the acid-ionization constant (pK(a)) values of these compounds and determine the identity of the ionizable functional groups in each set. We find substantial differences in acid/base profiles of the chemogenomic classes. In many cases, these differences can be linked to the nature of the target binding site and the corresponding functional groups needed for recognition of the ligand. Clear differences are also observed between the acid/base characteristics of drugs and screening compounds. For example, the proportion of drugs containing a carboxylic acid was 20 %, in stark contrast to a value of 2.4 % for the screening set sample. The proportion of aliphatic amines was 27 % for drugs and only 3.4 % for screening compounds. This suggests that there is a mismatch between commercially available screening compounds and the compounds that are likely to interact with a given chemogenomic target family. Our analysis provides a guide for the selection of screening compounds to better target specific chemogenomic families with regard to the overall balance of acids, bases and pK(a) distributions.

The significance of acid/base properties in drug discovery

While drug discovery scientists take heed of various guidelines concerning drug-like character, the influence of acid/base properties often remains under-scrutinised. Ionisation constants (pK(a) values) are fundamental to the variability of the biopharmaceutical characteristics of drugs and to underlying parameters such as logD and solubility. pK(a) values affect physicochemical properties such as aqueous solubility, which in turn influences drug formulation approaches. More importantly, absorption, distribution, metabolism, excretion and toxicity (ADMET) are profoundly affected by the charge state of compounds under varying pH conditions. Consideration of pK(a) values in conjunction with other molecular properties is of great significance and has the potential to be used to further improve the efficiency of drug discovery. Given the recent low annual output of new drugs from pharmaceutical companies, this review will provide a timely reminder of an important molecular property that influences clinical success.

The promiscuous binding of pharmaceutical drugs and their transporter-mediated uptake into cells: what we (need to) know and how we can do so

A recent paper in this journal sought to counter evidence for the role of transport proteins in effecting drug uptake into cells, and questions that transporters can recognize drug molecules in addition to their endogenous substrates. However, there is abundant evidence that both drugs and proteins are highly promiscuous. Most proteins bind to many drugs and most drugs bind to multiple proteins (on average more than six), including transporters (mutations in these can determine resistance); most drugs are known to recognise at least one transporter. In this response, we alert readers to the relevant evidence that exists or is required. This needs to be acquired in cells that contain the relevant proteins, and we highlight an experimental system for simultaneous genome-wide assessment of carrier-mediated uptake in a eukaryotic cell (yeast).

Purification and structural characterization of the voltage-sensor domain of the hERG potassium channel

The hERG (human ether à go-go related gene) potassium channel is a voltage-gated potassium channel playing important roles in the heart by controlling the rapid delayed rectifier potassium current. The hERG protein contains a voltage-sensor domain (VSD) that is important for sensing voltage changes across the membrane. Mutations in this domain contribute to serious heart diseases. To study the structure of the VSD, it was over-expressed in Escherichia coli and purified into detergent micelles. Lyso-myristoyl phosphatidylglycerol (LMPG) was shown to be a suitable detergent for VSD purification and folding. Secondary structural analysis using circular dichroism (CD) spectroscopy indicated that the purified VSD in LMPG micelles adopted α-helical structures. Purified VSD in LMPG micelles produced dispersed cross-peaks in a (15)N-HSQC spectrum. Backbone resonance assignments for residues from transmembrane segments S3 and S4 of VSD also confirmed the presence of α-helical structures in this domain. Our results demonstrated that structure of VSD can be investigated using NMR spectroscopy.

Multiple Kernel Learning for Drug Discovery

The support vector machine (SVM) methodology has become a popular and well-used component of present chemometric analysis. We assess a relatively recent development of the algorithm, multiple kernel learning (MKL), on published structure-property relationship (SPR) data. The MKL algorithm learns a weighting across multiple kernel-based representations of the data during supervised classifier creation and, thereby, may be used to describe the influence of distinct groups of structural descriptors upon a single structure-property classifier without explicitly omitting any of them. We observe a statistically significant performance improvement over a conventional, single kernel SVM on all three SPR data sets analysed. Furthermore, MKL output is observed to provide useful information regarding the relative influence of five distinct descriptor subsets present in each data set.