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The title compound, C30H33N4O2F, can be obtained via a two-step synthetic scheme involving 1-benzyl-6-fluoro-4-oxo-7-(piperidin-1-yl)-1,4-dihydroquinoline-3-carbonitrile as a starting compound that undergoes substitution with hydroxylamine and subsequent cyclization with 4-methylcyclohexane-1-carboxylic acid. It crystallizes from 2-propanol in the triclinic space group P\overline{1} with a molecule of the title compound and one of 2-propanol in the asymmetric unit. After the molecular structure was clarified using NMR and LC/MS, the molecular and crystalline arrangements were defined with SC-XRD. A Hirshfeld surface analysis was performed for a better understanding of the intermolecular interactions. One strong (O—H...O) and three weak [C—H...F (intramolecular) and two C—H...O] hydrogen bonds were found. The contributions of short contacts to the Hirshfeld surface were estimated using two-dimensional fingerprint plots showing that O...H/H...O, C...H/H...C and C...C contacts are the most significant for the title compound and O...H for the 2-propanol. The crystal structure appears to have isotropically packed tetramers containing two molecules of the title compound and two molecules of 2-propanol as the building unit according to analysis of the distribution of pairwise interaction energies. A molecular docking study was carried out to evaluate the interactions of the title compound with the active centers of macromolecules corresponding to viral targets, namely, anti-hepatitis B activity [HBV, capsid Y132A mutant (VCID 8772) PDB ID: 5E0I] and anti-COVID-19 main protease activity (PDB ID: 6LU7). The data obtained revealed a noticeable affinity towards them that exceeded that of the reference ligands.

S-CE-123, a novel dopamine transporter inhibitor, has emerged as a potential candidate for cognitive enhancement. The objective of this study was to compare the tissue distribution profiles, with a specific focus on central nervous system distribution and metabolism, of S-CE-123 and R-modafinil. To address this objective, a precise liquid chromatography–high resolution mass spectrometry method was developed and partially validated. Neuropharmacokinetic parameters were assessed using the Combinatory Mapping Approach. Our findings reveal distinct differences between the two compounds. Notably, S-CE-123 demonstrates a significantly superior extent of transport across the blood–brain barrier (BBB), with an unbound brain-to-plasma concentration ratio (Kp,uu,brain) of 0.5, compared to R-modafinil’s Kp,uu,brain of 0.1. A similar pattern was observed for the transport across the blood–spinal cord barrier. Concerning the drug transport across cellular membranes, we observed that S-CE-123 primarily localizes in the brain interstitial space, whereas R-modafinil distributes more evenly across both sides of the plasma membrane of the brain’s parenchymal cells (Kp,uu,cell). Furthermore, our study highlights the substantial differences in hepatic metabolic stability, with S-CE-123 having a 9.3-fold faster metabolism compared to R-modafinil. In summary, the combination of improved BBB transport and higher affinity of S-CE-123 to dopamine transporters in comparison to R-modafinil makes S-CE-123 a promising candidate for further testing for the treatment of cognitive decline.

The high structural similarity, especially in transmembrane regions, of dopamine, norepinephrine, and serotonin transporters, as well as the lack of all crystal structures of human isoforms, make the specific targeting of individual transporters rather challenging. Ligand design itself is also rather limited, as many chemists, fully aware of the synthetic and analytical challenges, tend to modify lead compounds in a way that reduces the number of chiral centers and hence limits the potential chemical space of synthetic ligands. We have previously shown that increasing molecular complexity by introducing additional chiral centers ultimately leads to more selective and potent dopamine reuptake inhibitors. Herein, we significantly extend our structure-activity relationship of dopamine transporter-selective ligands and further demonstrate how stereoisomers of defined absolute configuration may fine-tune and direct the activity towards distinct targets. From the pool of active compounds, using the examples of stereoisomers 7h and 8h, we further showcase how in vitro activity significantly differs in in vivo drug efficacy experiments, calling for proper validation of individual stereoisomers in animal studies. Furthermore, by generating a large library of compounds with defined absolute configurations, we lay the groundwork for computational chemists to further optimize and rationally design specific monoamine transporter reuptake inhibitors.

Abstract The lack of novel cognitive enhancer drugs in the clinic highlights the prediction problems of animal assays. The objective of the current study was to test a putative cognitive enhancer in a rodent cognitive test system with improved translational validity and clinical predictivity. Cognitive profiling was complemented with post mortem proteomic analysis. Twenty-seven male Lister Hooded rats (26 months old) having learned several cognitive tasks were subchronically treated with S-CE-123 (CE-123) in a randomized blind experiment. Rats were sacrificed after the last behavioural procedure and plasma and brains were collected. A label-free quantification approach was used to characterize proteomic changes in the synaptosomal fraction of the prefrontal cortex. CE-123 markedly enhanced motivation which resulted in superior performance in a new-to-learn operant discrimination task and in a cooperation assay of social cognition, and mildly increased impulsivity. The compound did not affect attention, spatial and motor learning. Proteomic quantification revealed 182 protein groups significantly different between treatment groups containing several proteins associated with aging and neurodegeneration. Bioinformatic analysis showed the most relevant clusters delineating synaptic vesicle recycling, synapse organisation and antioxidant activity. The cognitive profile of CE-123 mapped by the test system resembles that of modafinil in the clinic showing the translational validity of the test system. The findings of modulated synaptic systems are paralleling behavioral results and are in line with previous evidence for the role of altered synaptosomal protein groups in mechanisms of cognitive function.

Abstract QSAR methods are widely applied in the drug discovery process, both in the hit‐to‐lead and lead optimization phase, as well as in the drug-approval process. Most QSAR algorithms are limited to using molecules as input and disregard pharmacophores or pharmacophoric features entirely. However, due to the high level of abstraction, pharmacophore representations provide some advantageous properties for building quantitative SAR models. The abstract depiction of molecular interactions avoids a bias towards overrepresented functional groups in small datasets. Furthermore, a well‐crafted quantitative pharmacophore model can generalise to underrepresented or even missing molecular features in the training set by using pharmacophoric interaction patterns only. This paper presents a novel method to construct quantitative pharmacophore models and demonstrates its applicability and robustness on more than 250 diverse datasets. fivefold cross-validation on these datasets with default settings yielded an average RMSE of 0.62, with an average standard deviation of 0.18. Additional cross-validation studies on datasets with 15–20 training samples showed that robust quantitative pharmacophore models could be obtained. These low requirements for dataset sizes render quantitative pharmacophores a viable go-tomethod for medicinal chemists, especially in the lead-optimisation stage of drug discovery projects.

Enumerating protonation states and calculating microstate pKa values of small molecules is an important yet challenging task for lead optimization and molecular modeling. Commercial and non-commercial solutions have notable limitations such as restrictive and expensive licenses, high CPU/GPU hour requirements, or the need for expert knowledge to set up and use. We present a graph neural network model that is trained on 714,906 calculated microstate pKa predictions from molecules obtained from the ChEMBL database. The model is fine-tuned on a set of 5,994 experimental pKa values significantly improving its performance on two challenging test sets. Combining the graph neural network model with Dimorphite-DL, an open-source program for enumerating ionization states, we have developed the open-source Python package pkasolver, which is able to generate and enumerate protonation states and calculate pKa values with high accuracy.

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

The worldwide increase in cognitive decline, both in aging and with psychiatric disorders, warrants a search for pharmacological treatment. Although dopaminergic treatment approaches represent a major step forward, current dopamine transporter (DAT) inhibitors are not sufficiently specific as they also target other transporters and receptors, thus showing unwanted side effects. Herein, we describe an enantiomerically pure, highly specific DAT inhibitor, S-CE-123, synthetized in our laboratory. Following binding studies to DAT, NET and SERT, GPCR and kinome screening, pharmacokinetics and a basic neurotoxic screen, S-CE-123 was tested for its potential to enhance and/or rescue cognitive functions in young and in aged rats in the non-invasive reward-motivated paradigm of a hole-board test for spatial learning. In addition, an open field study with young rats was carried out. We demonstrated that S-CE-123 is a low-affinity but highly selective dopamine reuptake inhibitor with good bioavailability. S-CE-123 did not induce hyperlocomotion or anxiogenic or stereotypic behaviour in young rats. Our compound improved the performance of aged but not young rats in a reward-motivated task. The well-described impairment of the dopaminergic system in aging may underlie the age-specific effect. We propose S-CE-123 as a possible candidate for developing a tentative therapeutic strategy for age-related cognitive decline and cognitive dysfunction in psychiatric disorders.

Aim. To provide a brief literature review regarding the structure of the human coronavirus SARS-CoV-2, the mechanism of its replication and the role of viral proteases in this process; to analyze the ability of the known antiviral agents and compounds synthesized de novo in order to bind and inhibit the coronavirus main protease using computer simulation tools. Results and discussion. COVID-19 coronavirus has become a worldwide challenge in recent months. Taking into account the rapid spread and severity of COVID-19 among a significant part of the population there is an urgent need to develop effective medicines and appropriate treatment protocols, which, unfortunately, are not yet available. Currently, the search for molecules with an acceptable toxicity profile that are able to inhibit and/or stop coronavirus SARS-CoV-2 replication in the human body is very relevant. In this study, the virtual screening and molecular docking of both antiviral agents known and new compounds synthesized have been performed based on the structure of the main protease Mpro of SARS-CoV-2. The regularities identified during our study can be useful for searching and developing new antiviral drugs to control COVID-19 and other coronavirus infections. The analysis of the results of calculations of physicochemical characteristics of antiviral agents, as well as the determination of their binding sites with the main viral protease Mpro gives an optimistic assessment of the possibility to develop new drugs based on the structures of the known antiviral drugs or their modified analogs. Experimental part. Based on recent studies of the crystal structure of the virus main protease Mpro in the complex with various inhibitors (Protein Data Bank http://www.rcsb.org/pdb, the structure code – 6LU7) the virtual screening and molecular docking of 100 known antiviral agents and 50 novel compounds synthesized were performed. The screening data for the in vitro antimalarial activity of the compounds synthesized were presented. The following binding and physicochemical parameters of the ligand–protein interaction for all virus main protease potential inhibitors were calculated: binding affinity score (BAS), binding energy, lipophilicity (clogP) and topological polar surface area (TPSA). The protein and ligand structures were studied using Jmol, PyMol, and Avogadro graphics software packages. The virtual screening and molecular docking, as well as the analysis of the results were performed using a LigandScout 4.4 software package. Data on the antimalarial activity of 50 compounds synthesized were obtained from the Laboratory of Microbiology, Parasitology and Hygiene of theUniversity ofAntwerp (Belgium). Conclusions. According to the results of the virtual screening and molecular docking with protein 6LU7 it has been found that a number of the known antiviral drugs have a certain potential for their use as inhibitors of SARS-CoV-2 coronavirus main protease. Remdesivir and ritonavir substances have shown higher activity than the reference compound of the 6LU7 complex. The molecular docking of a series of compounds recently synthesized with the proven in vitro antimalarial activity has revealed that L1 – L6 compounds are promising candidates for further modification and development of new antiviral drugs to control coronavirus infection.

The title compound, C15H22N4O5S, was prepared via alkylation of 3-(chloromethyl)-5-(pentan-3-yl)-1,2,4-oxadiazole in anhydrous dioxane in the presence of triethylamine. The thiadiazine ring has an envelope conformation with the S atom displaced by 0.4883 (6) Å from the mean plane through the other five atoms. The planar 1,2,4-oxadiazole ring is inclined to the mean plane of the thiadiazine ring by 77.45 (11)°. In the crystal, molecules are linked by C—H...N hydrogen bonds, forming chains propagating along the b-axis direction. Hirshfeld surface analysis and two-dimensional fingerprint plots have been used to analyse the intermolecular contacts present in the crystal. Molecular docking studies were use to evaluate the title compound as a potential system that interacts effectively with the capsid of the Hepatitis B virus (HBV), supported by an experimental in vitro HBV replication model.

SARS-CoV-2 causes the current global pandemic coronavirus disease 2019. Widely-available effective drugs could be a critical factor in halting the pandemic. The main protease (3CLpro) plays a vital role in viral replication; therefore, it is of great interest to find inhibitors for this enzyme. We applied the combination of virtual screening based on molecular docking derived from the crystal structure of the peptidomimetic inhibitors (N3, 13b, and 11a), and experimental verification revealed FDA-approved drugs that could inhibit the 3CLpro of SARS-CoV-2. Three drugs were selected using the binding energy criteria and subsequently performed the 3CLpro inhibition by enzyme-based assay. In addition, six common drugs were also chosen to study the 3CLpro inhibition. Among these compounds, lapatinib showed high efficiency of 3CLpro inhibition (IC50 value of 35 ± 1 μM and Ki of 23 ± 1 μM). The binding behavior of lapatinib against 3CLpro was elucidated by molecular dynamics simulations. This drug could well bind with 3CLpro residues in the five subsites S1', S1, S2, S3, and S4. Moreover, lapatinib's key chemical pharmacophore features toward SAR-CoV-2 3CLpro shared important HBD and HBA with potent peptidomimetic inhibitors. The rational design of lapatinib was subsequently carried out using the obtained results. Our discovery provides an effective repurposed drug and its newly designed analogs to inhibit SARS-CoV-2 3CLpro.

The ubiquitin-proteasome pathway (UPP) is the major proteolytic system in the cytosol and nucleus of all eukaryotic cells. The role of proteasome inhibitors (PIs) as critical agents for regulating cancer cell death has been established. Aziridine derivatives are well-known alkylating agents employed against cancer. However, to the best of our knowledge, aziridine derivatives showing inhibitory activity towards proteasome have never been described before. Herein we report a new class of selective and nonPIs bearing an aziridine ring as a core structure. In vitro cell-based assays (two leukemia cell lines) also displayed anti-proliferative activity for some compounds. In silico studies indicated non-covalent binding mode and drug-likeness for these derivatives. Taken together, these results are promising for developing more potent PIs.

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

Dopamine (DA), the most abundant human brain catecholaminergic neurotransmitter, modulates key behavioral and neurological processes in young and senescent brains, including motricity, sleep, attention, emotion, learning and memory, and social and reward-seeking behaviors. The DA transporter (DAT) regulates transsynaptic DA levels, influencing all these processes. Compounds targeting DAT (e.g., cocaine and amphetamines) were historically used to shape mood and cognition, but these substances typically lead to severe negative side effects (tolerance, abuse, addiction, and dependence). DA/DAT signaling dysfunctions are associated with neuropsychiatric and progressive brain disorders, including Parkinson’s and Alzheimer diseases, drug addiction and dementia, resulting in devastating personal and familial concerns and high socioeconomic costs worldwide. The development of low-side-effect, new/selective medicaments with reduced abuse-liability and which ameliorate DA/DAT-related dysfunctions is therefore crucial in the fields of medicine and healthcare. Using the rat as experimental animal model, the present work describes the synthesis and pharmacological profile of (S)-MK-26, a new modafinil analogue with markedly improved potency and selectivity for DAT over parent drug. Ex vivo electrophysiology revealed significantly augmented hippocampal long-term synaptic potentiation upon acute, intraperitoneally delivered (S)-MK-26 treatment, whereas in vivo experiments in the hole-board test showed only lesser effects on reference memory performance in aged rats. However, in effort-related FR5/chow and PROG/chow feeding choice experiments, (S)-MK-26 treatment reversed the depression-like behavior induced by the dopamine-depleting drug tetrabenazine (TBZ) and increased the selection of high-effort alternatives. Moreover, in in vivo microdialysis experiments, (S)-MK-26 significantly increased extracellular DA levels in the prefrontal cortex and in nucleus accumbens core and shell. These studies highlight (S)-MK-26 as a potent enhancer of transsynaptic DA and promoter of synaptic plasticity, with predominant beneficial effects on effort-related behaviors, thus proposing therapeutic potentials for (S)-MK-26 in the treatment of low-effort exertion and motivational dysfunctions characteristic of depression and aging-related disorders.

The muscarinic acetylcholine receptor family is a highly sought-after target in drug and molecular imaging discovery efforts aimed at neurological disorders. Hampered by the structural similarity of the five subtypes’ orthosteric binding pockets, these efforts largely failed to deliver subtype-selective ligands. Building on our recent successes with arecaidine-derived ligands targeting M1, herein we report the synthesis of a related series of 11 hydroxylated arecaidine esters. Their physicochemical property profiles, expressed in terms of their computationally calculated CNS MPO scores and HPLC-logD values, point towards blood–brain barrier permeability. By means of a competitive radioligand binding assay, the binding affinity values towards each of the individual human mAChR subtypes hM1–hM5 were determined. The most promising compound of this series 17b was shown to have a binding constant towards hM1 in the single-digit nanomolar region (5.5 nM). Similar to our previously reported arecaidine-derived esters, the entire series was shown to act as hM1R antagonists in a calcium flux assay. Overall, this study greatly expanded our understanding of this recurring scaffolds’ structure–activity relationship and will guide the development towards highly selective mAChRs ligands.

Due to their important role in mediating a broad range of physiological functions, muscarinic acetylcholine receptors (mAChRs) have been a promising target for therapeutic and diagnostic applications alike; however, the list of truly subtype-selective ligands is scarce. Within this work, we have identified a series of twelve 4,4’-difluorobenzhydrol carbamates through a rigorous docking campaign leveraging commercially available amine databases. After synthesis, these compounds have been evaluated for their physico–chemical property profiles, including characteristics such as HPLC-logD, tPSA, logBB, and logPS. For all the synthesized carbamates, these characteristics indicate the potential for BBB permeation. In competitive radioligand binding experiments using Chinese hamster ovary cell membranes expressing the individual human mAChR subtype hM1-hM5, the most promising compound 2 displayed a high binding affinitiy towards hM1R (1.2 nM) while exhibiting modest-to-excellent selectivity versus the hM2-5R (4–189-fold). All 12 compounds were shown to act in an antagonistic fashion towards hM1R using a dose-dependent calcium mobilization assay. The structural eligibility for radiolabeling and their pharmacological and physico–chemical property profiles render compounds 2, 5, and 7 promising candidates for future position emission tomography (PET) tracer development.

Lipids play a major role for several brain functions, including cognition and memory. There is a series of work on individual lipids showing involvement in memory mechanisms, a concise lipidome was not reported so far. Moreover, there is no evidence for age-related memory decline and there is only work on brain of young vs. aging animals. Aging animals, however, are not a homogeneous group with respect to memory impairments, thus animals with impaired and unimpaired memory can be discriminated. Following recent studies of hippocampal lipid profiles and hypothalamus controlled hormone profiles, the aim of this study was to compare hypothalamic, lipidomic changes in male Sprague-Dawley rats between young (YM), old impaired (OMI) and old unimpaired (OMU) males. Grouping criterions for aged rats were evaluated by testing them in a spatial memory task, the hole-board. YMs were also tested. Subsequently brains were removed, dissected and hypothalami were kept at −80°C until sample preparation and analysis on liquid chromatography / mass spectrometry (LC-MS). Significant differences in the amounts of a series of lipids from several classes could be detected between young and aged and between OMI and OMU. A large number of lipids were increased in OMI and a smaller number in OMU as compared to young rats. Differences of lipid ratios (log2 of ratio) between OMI and OMU consisted of glycerophosphocholines (aPC 36:2 and 36:3; PC 34:0, 36:1, 36:3 and 40:2); Glycerophosphoethanolamines (aPE 34:2, 38:5 and 40:5; LPE 18:1, 20:1, 20:4, 22:4 and 22:6; PE36:1 and 38:4); glycerophosphoserines (PS 36:1, 40:4, and 40:6); triacylglycerol TG 52:4; ceramide Cer 17:2 and sphingomyelin SM 20:0. Thus, hypothalamic lipid profiles across different lipid classes discriminate aged male animals into OMU and OMI. The underlying mechanisms may be related to different functional networks of lipids in memory mechanisms and differences in metabolic processes. The study underlines the importance of lipidomics in the pathophysiology of age-related cognitive decline. The necessity of evaluating the cognitive status of aged subjects by behavioral tests results in more specific detection of critical lipids in memory decline, on which now can be focused in subsequent memory studies in animals and humans.

A method of 4-fluoro-3-(morpholinosulfonyl)benzo[b]thiophene-2-carboxylate synthesis has been developed and the electronic and spatial structure of a new biologically active molecule has been studied both theoretically and experimentally. The title compound was crystallized from acetonitrile and the single crystal X-ray analysis has revealed that it exists in a monoclinic P21/c space group, with one molecule in the asymmetric part of the unit cell. Hirshfeld surface analysis was used to study intermolecular interactions in the crystal. Molecular docking study evaluates the investigated compound as a new potential inhibitor of hepatitis B. Testing for anti-hepatitis B virus activity has shown that this substance demonstrates in vitro nanomolar inhibitory activity against HBV.

Fyn tyrosine kinase inhibitors are considered potential therapeutic agents for a variety of human cancers. Furthermore, the involvement of Fyn kinase in signalling pathways that lead to severe pathologies, such as Alzheimer’s and Parkinson’s diseases, has also been demonstrated. In this study, starting from 3-(benzo[d][1,3]dioxol-5-ylamino)-6-methyl-1,2,4-triazin-5(2H)-one (VS6), a hit compound that showed a micromolar inhibition of Fyn (IC50 = 4.8 μM), we computationally investigated the binding interactions of the 3-amino-1,2,4-triazin-5(2H)-one scaffold and started a preliminary hit to lead optimisation. This analysis led us to confirm the hypothesised binding mode of VS6 and to identify a new derivative that is about 6-fold more active than VS6 (compound 3, IC50 = 0.76 μM).

There is an increasing interest in developing novel eosinophil peroxidase (EPO) inhibitors, in order to provide new treatment strategies against chronic inflammatory and neurodegenerative diseases caused by eosinophilic disorder. Within this study, a ligand-based pharmacophore model for EPO inhibitors was generated and used for in silico screening of large 3 D molecular structure databases, containing more than 4 million compounds. Hits obtained were clustered and a total of 277 compounds were selected for biological assessment. A class of 2-(phenyl)amino-aceto-hydrazides with different substitution pattern on the aromatic ring was found to contain the most potent EPO inhibitors, exhibiting IC50 values down to 10 nM. The generated pharmacophore model therefore, represents a valuable tool for the selection of compounds for biological testing. The compounds identified as potent EPO inhibitors will serve to initiate a hit to lead and lead optimisation program for the development of new therapeutics against eosinophilic disorders.

Chemical features of small molecules can be abstracted to 3D pharmacophore models, which are easy to generate, interpret, and adapt by medicinal chemists. Three-dimensional pharmacophores can be used to efficiently match and align molecules according to their chemical feature pattern, which facilitates the virtual screening of even large compound databases. Existing alignment methods, used in computational drug discovery and bio-activity prediction, are often not suitable for finding matches between pharmacophores accurately as they purely aim to minimize RMSD or maximize volume overlap, when the actual goal is to match as many features as possible within the positional tolerances of the pharmacophore features. As a consequence, the obtained alignment results are often suboptimal in terms of the number of geometrically matched feature pairs, which increases the false-negative rate, thus negatively affecting the outcome of virtual screening experiments. We addressed this issue by introducing a new alignment algorithm, Greedy 3-Point Search (G3PS), which aims at finding optimal alignments by using a matching-feature-pair maximizing search strategy while at the same time being faster than competing methods.

The accurate prediction of molecular properties, such as lipophilicity and aqueous solubility, are of great importance and pose challenges in several stages of the drug discovery pipeline. Machine learning methods, such as graph-based neural networks (GNNs), have shown exceptionally good performance in predicting these properties. In this work, we introduce a novel GNN architecture, called directed edge graph isomorphism network (D-GIN). It is composed of two distinct sub-architectures (D-MPNN, GIN) and achieves an improvement in accuracy over its sub-architectures employing various learning, and featurization strategies. We argue that combining models with different key aspects help make graph neural networks deeper and simultaneously increase their predictive power. Furthermore, we address current limitations in assessment of deep-learning models, namely, comparison of single training run performance metrics, and offer a more robust solution.

In the last year, the COVID-19 pandemic has highly affected the lifestyle of the world population, encouraging the scientific community towards a great effort on studying the infection molecular mechanisms. Several vaccine formulations are nowadays available and helping to reach immunity. Nevertheless, there is a growing interest towards the development of novel anti-covid drugs. In this scenario, the main protease (Mpro) represents an appealing target, being the enzyme responsible for the cleavage of polypeptides during the viral genome transcription. With the aim of sharing new insights for the design of novel Mpro inhibitors, our research group developed a machine learning approach using the support vector machine (SVM) classification. Starting from a dataset of two million commercially available compounds, the model was able to classify two hundred novel chemo-types as potentially active against the viral protease. The compounds labelled as actives by SVM were next evaluated through consensus docking studies on two PDB structures and their binding mode was compared to well-known protease inhibitors. The best five compounds selected by consensus docking were then submitted to molecular dynamics to deepen binding interactions stability. Of note, the compounds selected via SVM retrieved all the most important interactions known in the literature.

Chikungunya virus (CHIKV) is a mosquito-transmitted alphavirus that has re-emerged in recent decades, causing large-scale epidemics in many parts of the world. CHIKV infection leads to a febrile disease known as chikungunya fever (CHIKF), which is characterised by severe joint pain and myalgia. As many patients develop a painful chronic stage and neither antiviral drugs nor vaccines are available, the development of a potent CHIKV inhibiting drug is crucial for CHIKF treatment. A comprehensive summary of current antiviral research and development of small-molecule inhibitor against CHIKV is presented in this review. We highlight different approaches used for the identification of such compounds and further discuss the identification and application of promising viral and host targets.

The muscarinic cholinergic system regulates peripheral and central nervous system functions, and, thus, their potential as a therapeutic target for several neurodegenerative diseases is undoubted. A clinically applicable positron emission tomography (PET) tracer would facilitate the monitoring of disease progression, elucidate the role of muscarinic acetylcholine receptors (mAChR) in disease development and would aid to clarify the diverse natural functions of mAChR regulation throughout the nervous system, which still are largely unresolved. Still, no mAChR PET tracer has yet found broad clinical application, which demands mAChR tracers with improved imaging properties. This paper reviews strategies of mAChR PET tracer design and summarizes the binding properties and preclinical evaluation of recent mAChR tracer candidates. Furthermore, this work identifies the current major challenges in mAChR PET tracer development and provides a perspective on future developments in this area of research.

Animal studies of effort-based choice behavior are being used to model effort-related motivational dysfunctions in humans. With these procedures, animals are offered a choice between high-effort instrumental actions leading to highly valued reinforcers vs. low effort/low reward options. Several previous studies have shown that dopamine (DA) uptake inhibitors, including GBR12909, lisdexamfetamine, methylphenidate, and PRX-14040, can reverse the effort-related effects of the vesicular monoamine transport blocker tetrabenazine, which inhibits DA storage. Because many drugs that block DA transport act as major stimulants that also release DA, and produce a number of undesirable side effects, there is a need to develop and characterize novel atypical DA transport inhibitors. (S)-CE-123 ((S)-5-((benzhydrylsulfinyl) methyl)thiazole) is a recently developed analog of modafinil with the biochemical characteristics of an atypical DA transport blocker. The present paper describes the enantioselective synthesis and initial chemical characterization of (S)-CE-123, as well as behavioral experiments involving effort-based choice and microdialysis studies of extracellular DA. Rats were assessed using the fixed ratio 5/chow feeding choice test. Tetrabenazine (1.0 mg/kg) shifted choice behavior, decreasing lever pressing and increasing chow intake. (S)-CE-123 was coadministered at doses ranging from 6.0 to 24.0 mg/kg, and the highest dose partially but significantly reversed the effects of tetrabenazine, although this dose had no effect on fixed ratio responding when administered alone. Additional experiments showed that (S)-CE-123 significantly increased lever pressing on a progressive ratio/chow feeding choice task and that the effective dose (24.0 mg/kg) increased extracellular DA in nucleus accumbens core. In summary, (S)-CE-123 has the behavioral and neurochemical profile of a compound that can block DA transport, reverse the effort-related effects of tetrabenazine, and increase selection of high-effort progressive ratio responding. This suggests that (S)-CE-123 or a similar compound could be useful as a treatment for effort-related motivational dysfunction in humans.

KATP channels consist of four Kir6.x pore–forming subunits and four regulatory sulfonylurea receptor (SUR) subunits. These channels couple the metabolic state of the cell to membrane excitability and play a key role in physiological processes such as insulin secretion in the pancreas, protection of cardiac muscle during ischemia and hypoxic vasodilation of arterial smooth muscle cells. Abnormal channel function resulting from inherited gain or loss-of-function mutations in either the Kir6.x and/or SUR subunits are associated with severe diseases such as neonatal diabetes, congenital hyperinsulinism, or Cantú syndrome (CS). CS is an ultra-rare genetic autosomal dominant disorder, caused by dominant gain-of-function mutations in SUR2A or Kir6.1 subunits. No specific pharmacotherapeutic treatment options are currently available for CS. Kir6 specific inhibitors could be beneficial for the development of novel drug therapies for CS, particular for mutations, which lack high affinity for sulfonylurea inhibitor glibenclamide. By applying a combination of computational methods including atomistic MD simulations, free energy calculations and pharmacophore modeling, we identified several novel Kir6.1 inhibitors, which might be possible candidates for drug repurposing. The in silico predictions were confirmed using inside/out patch-clamp analysis. Importantly, Cantú mutation C166S in Kir6.2 (equivalent to C176S in Kir6.1) and S1020P in SUR2A, retained high affinity toward the novel inhibitors. Summarizing, the inhibitors identified in this study might provide a starting point toward developing novel therapies for Cantú disease.

Protein-protein interactions (PPIs) play a pivotal role in the regulation of many physiological processes. The dysfunction of some PPIs interactions led to the alteration of different biological pathways causing various diseases including cancer. In this context, the inhibition of PPIs represents an attractive strategy for the design of new antitumoral agents. In recent years, computational approaches were successfully used to study the interactions between proteins, providing useful hints for the design of small molecules able to modulate PPIs. Targeting PPIs presents several challenges mainly due to the large and flat binding surface that lack the typical binding pockets of traditional drug targets. Despite these hurdles, substantial progress has been made in the last decade resulting in the identification of PPI modulators where some of them even found clinical use. This study focuses on MUC1-CIN85 PPI which is involved in the migration and invasion of cancer cells. Particularly, we investigated the presence of druggable binding sites on the CIN85 surface which provided new insights for the structure-based design of novel MUC1-CIN85 PPI inhibitors as anti-metastatic agents.

For the development of new and potent antimalarial drugs, we designed the virtual library with three points of randomization of novel [1,2,4]triazolo[4,3-a]pyridines bearing a sulfonamide fragment. The library of 1561 compounds has been investigated by both virtual screening and molecular docking methods using falcipain-2 as a target enzyme. 25 chosen hits were synthesized and evaluated for their antimalarial activity in vitro against Plasmodium falciparum. 3-Ethyl-N-(3-fluorobenzyl)-N-(4-methoxyphenyl)-[1,2,4]triazolo[4,3-a]pyridine-6-sulfonamide and 2-(3-chlorobenzyl)-8-(piperidin-1-ylsulfonyl)-[1,2,4]triazolo[4,3-a]pyridin-3(2H)-one showed in vitro good antimalarial activity with inhibitory concentration IC50 = 2.24 and 4.98 μM, respectively. This new series of compounds may serve as a starting point for future antimalarial drug discovery programs.

Consecutive alkylation of 4-hydroxy-2-thioxo-1,2-dihydroquinoline-3-carboxylate by CH3I has been investigated to establish regioselectivity of the reaction for reliable design and synthesis of combinatorial libraries. In the first stage, the product of S-methylation-methyl 4-hydroxy-2-(methylthio)quinoline-3-carboxylate was obtained. The subsequent alkylation with CH3I led to the formation of both O- and N-methylation products mixture-methyl 4-methoxy-2-(methylthio)quinoline-3-carboxylate and methyl 1-methyl-2-(methylthio)-4-oxo-1,4-dihydroquinoline-3-carboxylate with a predominance of O-methylated product. The structure of synthesized compounds was confirmed by means of elemental analysis, 1H-NMR, 13C-NMR, LC/MS, and single-crystal X-ray diffraction. The quantum chemical calculations of geometry and electron structure of methyl 4-hydroxy-2-(methylthio)quinoline-3-carboxylate’s anion were carried out. According to molecular docking simulations, the studied compounds can be considered as potent inhibitors of Hepatitis B Virus replication. Experimental in vitro biological studies confirmed that studied compounds demonstrated high inhibition of HBV replication in 10 µM concentration.

The G protein-coupled bile acid receptor (GPBAR1) has been recognized as a promising new target for the treatment of diverse diseases, including obesity, type 2 diabetes, fatty liver disease and atherosclerosis. The identification of novel and potent GPBAR1 agonists is highly relevant, as these diseases are on the rise and pharmacological unmet therapeutic needs are pervasive. Therefore, the aim of this study was to develop a proficient workflow for the in silico prediction of GPBAR1 activating compounds, primarily from natural sources. A protocol was set up, starting with a comprehensive collection of structural information of known ligands. This information was used to generate ligand-based pharmacophore models in LigandScout 4.08 Advanced. After theoretical validation, the two most promising models, namely BAMS22 and TTM8, were employed as queries for the virtual screening of natural product and synthetic small molecule databases. Virtual hits were progressed to shape matching experiments and physicochemical clustering. Out of 33 diverse virtual hits subjected to experimental testing using a reporter gene-based assay, two natural products, farnesiferol B (27) and microlobidene (28), were confirmed as GPBAR1 activators reaching more than 50% receptor activation at 20 μM with EC50s of 13.53 μM and 13.88 μM, respectively. This activity is comparable to that of the endogenous ligand lithocholic acid (1). Seven further virtual hits showed activity reaching at least 15% receptor activation either at 5 or 20 μM, including new scaffolds from natural and synthetic origin.

Herein we present the algorithm and performance assessment of our newly developed conformer generator iCon that was implemented in LigandScout 4.0. Two data sets of high-quality X-ray structures of drug-like small molecules originating from the Protein Data Bank (200 ligands) and the Cambridge Structural Database (481 molecules) were used to validate iCon's performance in the reproduction of experimental conformations. OpenEye's conformer generator OMEGA was subjected to the same evaluation and served as a reference software in this analysis. We tested several setting patterns in order to identify the most suitable and efficient ones for conformational sampling with iCon; equivalent settings were also tested on OMEGA in order to compare the results obtained from the two programs and better assess iCon's performance. Overall, this study proved that iCon is able to generate reliable representative conformational ensembles of drug-like small molecules, yielding results comparable to those showed by OMEGA, and thus is ready to serve as a valuable tool for computer-aided drug design.

For every lead compound developed in medicinal chemistry research, numerous other inactive or less active candidates are synthetized/isolated and tested. The majority of these compounds will not be selected for further development due to a sub-optimal pharmacological profile. However, some poorly active or even inactive compounds could live a second life if tested against other targets. Thus, new therapeutic opportunities could emerge and synergistic activities could be identified and exploited for existing compounds by sharing information between researchers who are working on different targets. The Mu.Ta.Lig (Multi-Target Ligand) Chemotheca database aims to offer such opportunities by facilitating information exchange among researchers worldwide. After a preliminary registration, users can (a) virtually upload structures and activity data for their compounds with corresponding, and eventually known activity data, and (b) search for other available compounds uploaded by the users community. Each piece of information about given compounds is owned by the user who initially uploaded it and multiple ownership is possible (this occurs if different users uploaded the same compounds or information pertaining to the same compounds). A web-based graphical user interface has been developed to assist compound uploading, compounds searching and data retrieval. Physico-chemical and ADME properties as well as substructure-based PAINS evaluations are computed on the fly for each uploaded compound. Samples of compounds that match a set of search criteria and additional data on these compounds could be requested directly from their owners with no mediation by the Mu.Ta.Lig Chemotheca team. Guest access provides a simplified search interface to retrieve only basic information such as compound IDs and related 2D or 3D chemical structures. Moreover, some compounds can be hidden to Guest users according to an owner's decision. In contrast, registered users have full access to all of the Chemotheca data including the permission to upload new compounds and/or update experimental/theoretical data (e.g., activities against new targets tested) related to already stored compounds. In order to facilitate scientific collaborations, all available data are connected to the corresponding owner's email address (available for registered users only). The Chemotheca web site is accessible at http://chemotheca.unicz.it.

Reduced cognitive abilities are often characterized by an impairment of flexibility, i.e., the ability to switch from learned rules or categories that were important in certain contexts to different new modalities that rule the task. Drugs targeting the dopamine transporter (DAT) are widely used for their potential to enhance cognitive abilities. However, commercially available drugs are of limited specificity for DAT, blocking also noradrenaline and serotonine transporters, that can lead to unwanted side effects in healthy subjects. Therefore, we tested a newly synthetized compound (CE-123) with higher specificity for DAT in male rats in an attentional set-shifting task (ASST), that proves for cognitive flexibility and a 5-choice serial-reaction time task (5-CSRTT) assessing visuospatial attention and impulsivity. Treated rats at a dose of 0.3 and 1.0 but not 0.1 mg/kg bodyweight showed reduced extra-dimensional shifts in the ASST compared to controls indicating increased cognitive flexibility. Rats treated with R-Modafinil, a commercially available DAT inhibitor at a dose of 10 mg/kg bodyweight showed increased premature responses, an indicator of increased impulsivity, during a 10 s but not a 2.5, 5, or 7.5 s intertrial interval when compared to vehicle-treated rats in the 5-CSRTT. This was not found in rats treated with CE-123 at the same dose as for R-Modafinil. Visuospatial attention, except premature responses, did not differ between R-Modafinil and CE-123-treated rats and their respective controls. Thus, CE-123 increased cognitive flexibility with diminished impulsivity.

Modafinil is a wake promoting drug approved for clinical use and also has cognitive enhancing properties. Its enantiomer R-Modafinil (R-MO) is not well studied in regard to cognitive enhancing properties. Hence we studied its effect in a spatial memory paradigm and its possible effects on dentate gyrus long-term potentiation (DG-LTP). Clinically relevant doses of R-MO, vehicle dimethyl sulfoxide (DMSO) or saline were administered for three days during the hole-board test and in in vivo DG-LTP. Synaptic levels of dopamine receptors D1R, D2R, dopamine transporter (DAT), and its phosphorylated form (ph-DAT) in DG tissue 4 h after LTP induction were quantified by western blot analysis. Monoamine reuptake and release assays were performed by using transfected HEK-293 cells. Possible neurotoxic side effects on general behaviour were also studied. R-MO at both doses significantly enhanced spatial reference memory during the last training session and during memory retrieval compared to DMSO vehicle but not when compared to saline treated rats. Similarly, R-MO rescues DG-LTP from impairing effects of DMSO. DMSO reduced memory performance and LTP magnitude when compared to saline treated groups. The synaptic DR1 levels in R-MO groups were significantly decreased compared to DMSO group but were comparable with saline treated animals. We found no effect of R-MO in neurotoxicity tests. Thus, our results support the notion that LTP-like synaptic plasticity processes could be one of the factors contributing to the cognitive enhancing effects of spatial memory traces. D1R may play an important regulatory role in these processes.

A method for the synthesis of 8-fluoro-5-(4-fluorobenzyl)-3-(2-methoxybenzyl)-3,5-dihydro-4H-pyrimido[5,4-b]indol-4-one has been developed and the electronic and spatial structure of a new biologically active molecule has been studied both theoretically and experimentally. The title compound was crystallized from acetonitrile and the single-crystal X-ray analysis has revealed that it exists in a monoclinic P21/n space group, with one molecule in the asymmetric part of the unit cell, a = 16.366(3) Å, b = 6.0295(14) Å, c = 21.358(4) Å, β = 105.21(2)°, V = 2033.7(7) Å3 and Z = 4. Hirshfeld surface analysis was used to study intermolecular interactions in the crystal. Molecular docking studies have evaluated the investigated compound as a new inhibitor of hepatitis B. Testing for anti-hepatitis B virus activity has shown that this substance has in vitro nanomolar inhibitory activity against Hepatitis B virus (HBV).

The large neutral amino acid transporter 1 (LAT1) is a promising anticancer target that is required for the cellular uptake of essential amino acids that serve as building blocks for cancer growth and proliferation. Here, we report a structure-based approach to identify chemically diverse and potent inhibitors of LAT1. First, a homology model of LAT1 that is based on the atomic structures of the prokaryotic homologs was constructed. Molecular docking of nitrogen mustards (NMs) with a wide range of affinity allowed for deriving a common binding mode that could explain the structure−activity relationship pattern in NMs. Subsequently, validated binding hypotheses were subjected to molecular dynamics simulation, which allowed for extracting a set of dynamic pharmacophores. Finally, a library of ~1.1 million molecules was virtually screened against these pharmacophores, followed by docking. Biological testing of the 30 top-ranked hits revealed 13 actives, with the best compound showing an IC50 value in the sub-μM range.

The PHARMINE (“Pharmacy Education in Europe”) project studied pharmacy practice and education in the European Union (EU) member states. The work was carried out using an electronic survey sent to chosen pharmacy representatives. The surveys of the individual member states are now being published as reference documents for students and staff interested in research on pharmacy education in the EU and in mobility. This paper presents the results of the PHARMINE survey on pharmacy practice and education in Austria. In the light of this, we examine the harmonisation of practice and education in Austria with EU norms.

Tamoxifen is the most frequently used anti-estrogen adjuvant treatment for estrogen receptor-positive breast cancer. However, it is associated with an increased risk of several serious side–effects, such as uterine cancer, stroke, and pulmonary embolism. The 2′,4′-dihydroxy-6-methoxy-3,5-dimethylchalcone (ChalcEA) from plant leaves of Eugenia aquea, has been found to inhibit the proliferation of MCF-7 human breast cancer cells in a dose-dependent manner, with an IC50 of 74.5 μg/mL (250 μM). The aim of this work was to study the molecular interactions of new ChalcEA derivatives formed with the Estrogen Receptor α (ERα) using computer aided drug design approaches. Molecular docking using Autodock 4.2 was employed to explore the modes of binding of ChalcEA derivatives with ERα. The 3D structure-based pharmacophore model was derived using LigandScout 4.1 Advanced to investigate the important chemical interactions of the ERα-tamoxifen complex structure. The binding energy and the tamoxifen-pharmacophore fit score of the best ChalcEA derivative (HNS10) were −12.33 kcal/mol and 67.07 kcal/mol, respectively. The HNS10 interacted with Leu346, Thr347, Leu349, Ala350, Glu353, Leu387, Met388, Leu391, Arg394, Met421, and Leu525. These results suggest that the new ChalcEA derivatives could serve as the lead compound for potent ERα inhibitor in the fight against breast cancer.

Bei PharmXplorer handelt es sich um eine hypermediale multifunktionale Studien- und Weiterbildungsplattform, die Studierende, Lehrende und PraktikerInnen bei ihrer problemorientierten, kontextbezogenen und multiperspektivischen Wissens-generierung unterstützt. Die Basis der mediendidaktisch und fachdidaktisch aufbereiteten Inhalte bildet ein nach unterschiedlichen Kriterien abfragbares vernetztes Datenbanksystem, in dem alle pharmazeutisch relevanten Daten der in Österreich zugelassenen Arzneistoffe enthalten sind. 12.02.2005 | Klaus Schweiger, Alexandra Sindler, Norbert Haider & Thierry Langer (Graz)

We report on the impact of pharmacophore-based virtual screening in the field of drug discovery from natural products. Confronted by an increasing number of secondary metabolites and an increasing number of biomolecular targets relevant in the therapy of human disorders, there is clearly the need for efficient data management. Filtering of compounds by virtual screening experiments already showed great effect when dealing with large libraries of potential bioactive molecules. Feature-based 3D pharmacophores have been successfully utilized for database mining in order to retrieve potentially bio-active molecules. However, for the discovery of natural lead candidates, the application of such in silico tools has been so far almost neglected. There seems to be several reasons for this. One concerns the scarce availability of natural product (NP) 3D databases in contrast to synthetic/combinatorial compound libraries; another reason might be the problematic compatibility of NPs with modern robotized high-throughput-screening (HTS) technologies. Additionally, the incalculable availability of pure natural compounds and their often too complex chemistry is claimed to hamper such an approach. Thus, research in this field appears time-consuming, highly complex, expensive, and ineffective. Nevertheless, naturally derived compounds are still among the most favorable sources of new drug candidates. A more rational and economic search for new lead structures originating from nature must therefore be a priority in order to overcome these problems.