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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.

To achieve chemical accuracy in free energy calculations, it is necessary to accurately describe the system's potential energy surface and efficiently sample configurations from its Boltzmann distribution. While neural network potentials (NNPs) have shown significantly higher accuracy than classical molecular mechanics (MM) force fields, they have limited range of applicability and are significantly slower than MM potentials, often by orders of magnitude. To address this challenge, Rufa et al suggested a two-stage approach that uses a fast and established MM alchemical energy protocol, followed by reweighting the results using NNPs, known as endstate correction or indirect free energy calculation. In this study, we systematically investigate the accuracy, robustness, and efficiency of free energy calculations between a MM reference and a neural network target potential (ANI-2x) using free energy perturbation (FEP) and non-equilibrium (NEQ) switching simulation in vacuum. We investigate the influence of longer switching lengths and the impact of slow degrees of freedom on outliers in the work distribution. We compare the results to multistage equilibrium free energy calculations (MFES) for an established dataset. Our results demonstrate that free energy calculations between NNPs and MM potentials should not be performed using FEP but require NEQ switching simulations to obtain accurate free energy estimates. NEQ switching simulations between MM and NNPs are highly efficient, robust, and trivial to implement.

International audience; In an effort to provide an overview of the biophysical approaches used to study G-protein-coupled receptors, we chose to consider the adenosine A2A receptor as a model, as it is widely reported in the literature to explore the way GPCRs are studied nowadays. After a brief introduction of the receptor, we gathered descriptions of the various tools used to investigate the pharmacology and structure of the A2A receptor. We began by describing the key developments which have led to successful studies of GPCRs including the cloning, expression and purification of A2A, and the subsequent characterizations including quality control, binding and functional studies that have been necessary for the further understanding of the receptor. Then, we reviewed the reconstitution of A2A into nanodiscs as well as the use of this biological material in structural mass spectrometry, NMR, calorimetry and various other approaches to gain not only information about the structure and function of A2A, but also the dynamics of the receptor and the tools necessary to pursue such investigations. The body of techniques presented herein are applicable to all GPCRs amenable to purification.

Background and Purpose: Many psychotherapeutic drugs, including clozapine, display polypharmacology and act on GABA receptors. Patients with schizophrenia show alterations in function, structure and molecular composition of the hippocampus, and a recent study demonstrated aberrant levels of hippocampal a5 subunit-containing GABA receptors. The purpose of this study is to investigate tricyclic compounds in a5 subunit-containing receptor subtypes. Experimental Approach: Functional studies of effects by seven antipsychotic and antidepressant medications were performed in several GABA receptor subtypes by two‐electrode voltage‐clamp electrophysiology using Xenopus laevis oocytes. Computational structural analysis was employed to design mutated constructs of the a5 subunit, probing a novel binding site. Radioligand displacement data complemented the functional and mutational findings. Key Results: We show that the antipsychotic drugs clozapine and chlorpromazine exert functional inhibition on multiple GABA receptor subtypes, including a5-containing ones. Based on a chlorpromazine binding site observed in a GABA-gated bacterial homologue, we identified a novel site in a5 GABA receptor subunits and demonstrate differential usage of this and the orthosteric sites by these ligands. Conclusion and Implications: Despite high molecular and functional similarities among the tested ligands, they reduce GABA currents by differential usage of allosteric and orthosteric sites. The C C C C C C site we describe here is a new potential target for optimizing antipsychotic medications with beneficial polypharmacology. Further studies in defined subtypes are needed to substantiate mechanistic links between the therapeutic effects of clozapine and its action on certain GABA receptor subtypes.

Worldwide outbreaks of hand, foot, and mouth disease (HFMD) are caused by enterovirus A71 (EV-A71) and coxsackievirus A16 (CV-A16). Since no anti-HFMD drugs are currently available, it is interesting to study potential viral inhibitors. Rupintrivir is a rhinovirus 3C protease (3Cpro) inhibitor with apparent inhibitory activity against HFMD. This study constructs pharmacophore models of the EV-A71 and CV-A16 3Cpro complexed with rupintrivir using molecular dynamics (MD) simulations. Both models had similar pharmacophore features, including hydrogen bond donors and acceptors and hydrophobic interactions. These pharmacophore models were then used as a template to screen 39 flavonoid compounds as potential novel inhibitors. Diosmin, epigallocatechin gallate (EGCG), and RTH-011 showed high binding affinities for EV-A71 and CV-A16 3Cpro. They formed hydrogen bonds with important surrounding residues in both proteins, including H40, L127, T142, A144, T145, H161, I162, G163, and G164. In addition, their effective concentrations against rhabdomyosarcoma (RD) cell infection by EV-A71 and CV-A16 were determined. EGCG had the highest half maximal effective concentration (EC50) of 12.86 ± 1.30 µM for EV-A71 and 15.54 ± 1.50 µM for CV-A16, while diosmin had EC50 of 21.01 ± 1.57 µM for EV-A71 and 30.68 ± 3.25 µM for CV-A16. Both compounds were non-toxic in RD cells, with 50% cytotoxic concentrations of > 100 µM for EGCG and > 500 µM for diosmin. In addition, MD simulation analysis showed that EGCG had a higher binding affinity than diosmin, supported by its significantly lower solvated binding free energies and greater numbers of contact atoms and key binding residues. Moreover, previous studies reported EGCG’s inhibitory effect on other viruses, such as severe acute respiratory syndrome coronavirus 2. Therefore, our findings suggest that EGCG can effectively inhibit the EV-A71 and CV-A16 3Cpro.

The androgen receptor (AR) plays a crucial role in the growth of prostate cancer, and has long been considered the cancer’s primary strategic therapeutic target. However, despite the early suscepti...

Aging-related neurological deficits negatively impact mental health, productivity, and social interactions leading to a pronounced socioeconomic burden. Since declining brain dopamine signaling during aging is associated with the onset of neurological impairments, we produced a selective dopamine transporter (DAT) inhibitor to restore endogenous dopamine levels and improve cognitive function. We describe the synthesis and pharmacological profile of (S,S)-CE-158, a highly specific DAT inhibitor, which increases dopamine levels in brain regions associated with cognition. We find both a potentiation of neurotransmission and coincident restoration of dendritic spines in the dorsal hippocampus, indicative of reinstatement of dopamine-induced synaptic plasticity in aging rodents. Treatment with (S,S)-CE-158 significantly improved behavioral flexibility in scopolamine-compromised animals and increased the number of spontaneously active prefrontal cortical neurons, both in young and aging rodents. In addition, (S,S)-CE-158 restored learning and memory recall in aging rats comparable to their young performance in a hippocampus-dependent hole board test. In sum, we present a well-tolerated, highly selective DAT inhibitor that normalizes the age-related decline in cognitive function at a synaptic level through increased dopamine signaling.

The worldwide re-emerge of the Chikungunya virus (CHIKV), the high morbidity associated with it, and the lack of an available vaccine or antiviral treatment make the development of a potent CHIKV-inhibitor highly desirable. Therefore, an extensive lead optimisation was performed based on the previously reported CHVB compound 1b and the reported synthesis route was optimised - improving the overall yield in remarkable shorter synthesis and work-up time. 100 CHVB analogues were designed, synthesised, and investigated for their antiviral activity, physiochemistry, and toxicological profile. An extensive structure-activity relationship study (SAR) was performed, which focused mainly on the combination of scaffold changes and revealed the key chemical features for a high anti-CHIKV inhibition. Further, to investigate the druggability of the compound series, a thorough ADMET investigation was carried out: the compounds were screened for their aqueous solubility, lipophilicity, their toxicity in CaCo-2 cells, and possible hERG channel interactions. Additionally, 55 analogues were assessed for their metabolic stability in human liver microsomes (HLMs) which led to a structure-metabolism relationship study (SMR). The compounds showed an excellent safety profile, favourable physicochemical characteristics, and the required metabolic stability. A cross-resistance study confirmed the viral capping machinery (nsP1) to be the viral target of these second-generation CHVB compounds. This study identified five compounds (31b, 31d, 32d, 34, and 35d) as potent, safe, and stable lead compounds for further development as selective CHIKV inhibitors - with 32d as the most promising candidate. Finally, the collected insight led to a successful scaffold hop (64b) for future antiviral research studies.

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. F.J.M. and S.K. have received sponsorship from the Austrian Science Fund (Project Nr. P_31004). We are also in debt to Michele Santoni for his contributions to biochemistry analyses. F.J.M. and S.K. thank Maureen Cabatic and Marife-Astrid Malabanan for technical support.

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.

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.

The majority of compounds in the drug-like chemical space show flexibility regarding their three-dimensional structure which, in solution, results in an equilibrium of multiple interconvertible conformational states. Knowledge of the putative bound-state conformation of a molecule is an essential prerequisite for the successful application of many computer-aided drug design methods that aim to assess or predict its capability to bind to a particular target receptor of interest. An established approach to predict bioactive conformers in the absence of receptor structure information is to sample the low-energy conformational space of the investigated molecules and derive representative conformer ensembles which can then be expected to comprise members that closely resemble possible bound-state ligand conformations. The high relevance of such conformer generation functionality led to the development of a wide panel of dedicated commercial and open-source software tools throughout the last decades. Several published benchmarking studies have shown that open-source tools lag behind their commercial competitors in many key aspects like accuracy in reproducing bioactive conformations, speed of processing, output ensemble size, range of applicability, stability and user-friendliness. In this work, we introduce the novel open-source conformer ensemble generator CONFORT, which builds upon proven concepts and algorithms and aims at delivering state-of-the-art performance for all types of organic molecules in the drug-like chemical space. The ability of CONFORT, and several well-known commercial and open-source conformer ensemble generators, to reproduce experimental 3D structures as well as their computational efficiency and robustness has been assessed thoroughly both for typical drug-like molecules and macrocyclic structures. For small molecules, CONFORT outperforms all other tested open-source conformer generators and is head-to-head with commercial generators, both in terms of processing speed and accuracy in the reproduction of bioactive conformations. In the case of macrocyclic structures, CONFORT is able to reproduce experimental 3D structures with clearly higher accuracy than all other tested generators. To our knowledge, CONFORT is the first open-source conformer ensemble generator that is able to truly keep up with commercial software in this field and thus represents a valuable addition to the open-source software toolbox for computer-aided drug design.

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 (

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.

Мета . Надати скорочений огляд літературних даних стосовно будови коронавірусу людини SARS-CoV-2, механізму його репродукції та ролі вірусних протеаз у цьому процесі. За допомогою інструментів комп’ютерного моделювання проаналізувати здатність відомих противірусних агентів та de novo синтезованих сполук зв’язувати та пригнічувати головну протеазу коронавірусу. Результати та їх обговорення . Коронавірусна хвороба COVID-19 за останні місяці стала викликом для всього світу. З огляду на швидке поширення та важкий перебіг COVID-19 у значної частини населення існує нагальна потреба в ефективних лікарських засобах і відповідних протоколах лікування, які, на жаль, поки що відсутні. На теперішній час пошук молекул з прийнятним профілем токсичності, здатних пригнічувати та/або припиняти репродукцію коронавірусу SARS-CoV-2 в організмі людини, є вельми актуальним. У представленій роботі на основі даних про будову головної протеази M pro SARS-CoV-2 було проведено віртуальний скринінг та молекулярний докінг як відомих противірусних агентів, так і нових синтезованих сполук. Виявлені в ході дослідження закономірності можуть бути корисними для пошуку та розробки нових противірусних лікарських засобів для боротьби з захворюванням COVID-19 та іншими коронавірусними інфекційними хворобами. Аналіз результатів розрахунків фізико-хімічних характеристик противірусних агентів та визначення сайтів їх зв’язування з головною вірусною протеазою M pro дозволяє дати оптимістичну оцінку можливості створення нових лікарських засобів на основі відомих противірусних лікарських засобів або їх модифікованих аналогів. Експериментальна частина . На основі аналізу новітніх досліджень кристалічної структури головної протеази вірусу M pro у комплексі з різними інгібіторами (Protein Data Bank http://www.rcsb.org/pdb , код структури – 6LU7) проведено віртуальний скринінг та молекулярний докінг 100 відомих противірусних агентів та 50 нових синтезованих сполук. Наведено дані скринінгу in vitro антималярійної активності синтезованих сполук. Для всіх потенційних інгібіторів головної протеази вірусу було розраховано параметри зв’язування та фізико-хімічні параметри взаємодії «ліганд–білок»: показник спорідненості (BAS), енергію зв’язування, ліпофільність (clogP) та топологічний індекс площі поверхні полярних груп молекули ліганду (TPSA). Вивчення структури білка та ліганду проводили за допомогою графічних програмних пакетів Jmol, PyMol та Avogadro. Віртуальний скринінг та молекулярний докінг, а також аналіз отриманих результатів проводили за допомогою програмного комплексу LigandScout 4.4. Дані щодо антималярійної активності 50 синтезованих сполук були отримані в Лабораторії мікробіології, паразитології та гігієни Антверпенського університету (Бельгія). Висновки . За результатами віртуального скринінгу та молекулярного докінгу з білком 6LU7 було встановлено, що низка відомих противірусних лікарських засобів має певну перспективу використання як інгібіторів головної протеази коронавірусу SARS-CoV-2, а такі субстанції, як ремдесивір та ритонавір характеризуються більш високою активністю, ніж референтна сполука з комплексу 6LU7. Молекулярний докінг ряду нових, нещодавно синтезованих сполук з доведеною in vitro антималярійною активністю показав, що сполуки L1 – L6 можуть стати перспективними кандидатами для подальшої модифікації та розробки нових противірусних лікарських засобів для боротьби з коронавірусною інфекцією. Received : 02.04.2020 Revised : 23.05.2020 Accepted : 29.05.2020

The chikungunya virus (CHIKV) is a mosquito-transmitted alphavirus, and it is the causative agent of chikungunya fever (CHIKF). Although it has re-emerged as an epidemic threat, so far there are neither vaccines nor pharmacotherapy available to prevent or treat an infection. Herein, we describe the synthesis and structure-activity relationship studies of a class of novel small molecule inhibitors against CHIKV and the discovery of a new potent inhibitor (compound 6a). The starting point of the optimization process was N-ethyl-6-methyl-2-(4-(4-fluorophenylsulfonyl)piperazine-1-yl)pyrimidine-4-amine (1) with an EC50 of 8.68 μM, a CC50 of 122 μM, and therefore a resulting selectivity index (SI) of 14.2. The optimized compound 6a, however, displays a much lower micromolar antiviral activity (EC50 value of 3.95 μM), considerably better cytotoxic liability (CC50 value of 260 μM) and consequently an improved SI of greater than 61. Therefore, we report the identification of a promising novel compound class that has the potential for further development of antiviral drugs against the CHIKV. ispartof: ACS MEDICINAL CHEMISTRY LETTERS vol:11 issue:5 pages:906-912 ispartof: location:United States status: published

The title compound, a new inhibitor of the Hepatitis B virus (HBV), was prepared via alkyl­ation of 3-(chloro­meth­yl)-5-(pentan-3-yl)-1,2,4-oxa­diazole in anhydrous dioxane in the presence of tri­ethyl­amine., 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.

Enumerating protonation states and calculating microstate pK

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.

Enumerating protonation states and calculating micro-state 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 mico-state 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 micro-state pKa values with high accuracy.

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

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. Until today 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 was put on the development of automated procedures that optimise pharmacophores towards higher discriminatory power, which until today 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.

Background The 2',4'-dihydroxy-6-methoxy-3,5-3-dimethylchalcone (ChalcEA) isolated from Eugenia aquea Burm f. leaves has potential anticancer activity against human breast-adenocarcinoma cell lines (MCF-7) with an IC50 value of 250 µM. However, its apoptotic activity on the T47D breast cancer cell lines which is involving caspase-3 has not been investigated. Materials and methods Therefore, this study aims to evaluate the cytotoxicity of ChalcEA on the T47D cell lines using the 2-(4-iodophenyl)-3-(4-nitrophenyl)-5-(2,4-disulfophenyl)-2H-tetrazolium (WST) method and to predict its possible antagonistic activity on the human estrogen receptor alpha (hERα) using pharmacophore and molecular dynamics (MD) methods. The in vitro test of 10 synthesized ChalcEA derivatives was also performed as an insight into the further development of its structure as an anticancer agent. Results It is shown that ChalcEA has an IC50 of 142.58 ± 4.6 µM against the hERα-overexpressed T47D breast cancer cell lines, indicating its possible mechanism of anticancer activity as an antagonist of hERα. Pharmacophore study showed that ChalcEA shares similar features with the known hERα antagonist, 4-hydroxytamoxifen (4-OHT), which has hydrogen bond donor (HBD), hydrogen bond acceptor (HBA), ring aromaticity (RA), and hydrophobicity (Hy) features. Molecular docking showed that ChalcEA formed hydrogen bonds with Glu353 and Arg394, and hydrophobic interactions in a similar manner with 4-OHT. Moreover, MD simulations showed that ChalcEA destabilized the conformation of His524, a remarkable behavior of a known hERa antagonist, including 4-OHT. Furthermore, the 10 best chalcone derivatives resulted from pharmacophore- and docking-based screening, were tested against the T47D cell lines. None of the derivatives have better activity than ChalcEA. It is suggested that the functional groups at the B-ring of ChalcEA are interesting to be further optimized in the next studies. Conclusion ChalcEA might act as an antagonist toward hERα, thus warranting further investigation as a potential anticancer agent.

Many psychotherapeutic drugs, including clozapine, display polypharmacology and act on GABAFunctional studies of effects by seven antipsychotic and antidepressant medications were performed in several GABAThe antipsychotic drugs clozapine and chlorpromazine exerted functional inhibition on multiple GABADespite high molecular and functional similarities among the tested ligands, they reduce GABA currents by differential usage of allosteric and orthosteric sites. The chlorpromazine site we describe here is a new potential target for optimizing antipsychotic medications with beneficial polypharmacology. Further studies in defined subtypes are needed to substantiate mechanistic links between the therapeutic effects of clozapine and its action on certain GABA

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.

A formal CH2 -CH2 homologation conducted with C1 carbenoids on a carbon electrophile for the obtainment of a four-membered cycle is reported. The logic proposes the consecutive delivery of two single nucleophilic CH2 units to an isothiocyanate-as competent electrophilic partner-resulting in the assembling of a rare imino-thietane cluster. The single synthetic operation procedure documents genuine chemocontrol, as indicated by the tolerance to various reactive elements decorating the starting materials. Significantly, the double homologation protocol is accomplished directly on a carbon electrophile, thus not requiring the installation of heteroatom-centered manifolds (e.g. boron).

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) nonstructural protein 1 (nsP1) harbors the methyltransferase (MTase) and guanylyltransferase (GTase) activities needed for viral RNA capping and represents a promising antiviral drug target. We compared the antiviral efficacies of nsP1 inhibitors belonging to the MADTP, CHVB, and FHNA series (69-fluoro- homoneplanocin A [FHNA], its 39-keto form, and 69-b-fluoro-homoaristeromycin). Cell-based phenotypic cross-resistance assays revealed that the CHVB and MADTP series had similar modes of action that differed from that of the FHNA series. In biochemical assays with purified Semliki Forest virus and CHIKV nsP1, CHVB compounds strongly inhibited MTase and GTase activities, while MADTP-372 had a moderate inhibitory effect. FHNA did not directly inhibit the enzymatic activity of CHIKV nsP1. The first-oftheir- kind molecular-docking studies with the cryo-electron microscopy (cryo-EM) structure of CHIKV nsP1, which is assembled into a dodecameric ring, revealed that the MADTP and CHVB series bind at the S-adenosylmethionine (SAM)-binding site in the capping domain, where they would function as competitive or noncompetitive inhibitors. The FHNA series was predicted to bind at the secondary binding pocket in the ring-aperture membrane-binding and oligomerization (RAMBO) domain, potentially interfering with the membrane binding and oligomerization of nsP1. Our cell-based and enzymatic assays, in combination with molecular docking and mapping of compound resistance mutations to the nsP1 structure, allowed us to group nsP1 inhibitors into functionally distinct classes. This study identified druggable pockets in the nsP1 dodecameric structure and provides a basis for the rational design, optimization, and combination of inhibitors of this unique and promising antiviral drug target., K.K. was supported by the Marie Sklodowska-Curie ETN European Training Network “ANTIVIRALS” (EU grant agreement 642434). M.G.G. was supported by funding from the Oncode Institute, the Netherlands. R.J. and J.R. were supported by the ATIP-Avenir program and the Bettencourt Shueller Foundation. M.-J.P.-P. acknowledges the financial support of AEI (grant PID2019-105117RR-C22).

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.

The Pim-1 enzyme from the serine/threonine protein kinase family is a likely target for the targeted therapy of tumors of hematopoietic and lymphoid tissues. Triazolopyridine is an universal scaffold upon which international scientific programs have been launched to develop potential anticancer agents. Aim. To create a pharmacophore model to find new potential Pim-1 inhibitors; conduct a virtual screening of a simulated base of new 1,2,4-triazolo[4,3-a]pyridine derivatives; develop a method for the synthesis of 1,2,4-triazolo[4,3-a]pyridine-3-methanamines with the 1,2,4-isoxadiazole cycle. Results and discussion. In this study, a ligand-based pharmacophore model for Pim-1 inhibitors was constructed and validated. A virtual screening of the library with 912 compounds resulted in a hit list of 175 compounds. For the synthesis, 15 compounds were selected with the highest pharmacophore-fit score. 15 compounds were synthesized as potential inhibitors of Pim-1 kinase. Experimental part. The synthetic approach has been developed, and systematic series of new amides of (7-(1,2,4-oxadiazol-5-yl)-[1,2,4]triazolo[4,3-a]pyridin-3-yl)methanamine and (8-(1,2,4-oxadiazol-5-yl)-[1,2,4]triazolo[4,3-a]pyridin-3-yl)methanamine have been synthesized. Conclusions. The compounds obtained are potential inhibitors of Pim-1 kinase. Further studies will focus on the determination of the antitumor activity of the compounds synthesized by in vitro and in vivo methods.

Fused heterocyclic 1,2,4-triazoles have provided much attention due to variety of their interesting biological properties. Aim. To develop the method for the synthesis of novel 2-[(1,2,4-oxadiazol-5-yl)-[1,2,4]triazolo[4,3-a]pyridine-3-yl]acetamides and conduct the biological assessment of the compounds synthesized. Results and discussion. A diverse set of acetamides newly synthesized consists of 32 analogs bearing an 1,2,4-oxadiazole cycle in positions 6, 7 and 8. A convenient scheme of the synthesis starts from commercially available 2-chloropyridine-3-, 2-chloropyridine-4-, 2-chloropyridine-5-carboxylic acids with amidoximes to form the corresponding 2-chloro-[3-R1-1,2,4-oxadiazol-5-yl]pyridines, then follows the reaction of hydrazinolysis with an excess of hydrazine hydrate. The process continues via the ester formation with the pyridine ring closure, then the amide formations of the end products are obtained by hydrolysis into acetic acid. Experimental part. A series of new 2-[6-(1,2,4-oxadiazol-5-yl)-, 2-[7-(1,2,4-oxadiazol-5-yl)-, 2-[8-(1,2,4-oxadiazol-5-yl)-[1,2,4]triazolo[4,3-a]pyridine-3-yl]acetamides were obtained in good yields, and their structures were proven by the method of 1H NMR spectroscopy. The prognosis and study of their pharmacological activity were also conducted. Conclusions. The synthetic approach of obtaining the representatives of 2-[(1,2,4-oxadiazol-5-yl)-[1,2,4]triazolo[4,3-a]pyridine-3-yl]acetamides previously unknown can be used as an applicable method for the synthesis of diverse functionalized [1,2,4]triazolo[4,3-a]pyridine derivatives.

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.

High-performance computing (HPC) clusters play a major role in scientific research. However, working with these clusters is often cumbersome, especially for researchers without a formal background in computer science. It requires preparation and transfer of the input data, manual gathering of results, and command-line expertise. Current approaches for improving accessibility to remote HPC clusters are focused on providing web-based graphical front-ends that allow jobs to be submitted to the distributed resource management system running on the cluster. This comes with significant usability benefits over command-line usage but does not circumvent the need for manual handling of the input and output files. With LigandScout Remote, we propose a different solution. Our software enables the seamless integration of HPC resources into the LigandScout desktop application that scientists use also in their day-to-day work. By handling necessary data conversion and network communication transparently to the user, this approach completely evades any HPC usability barriers. We show that the developed software combines the usability of local graphical desktop applications with the performance of HPC clusters.

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. Supplementary Information The online version contains supplementary material available at 10.1186/s13321-021-00537-9.

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.

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&rsquo, 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 &micro, M concentration.

The sequential installation of a carbenoid and a hydride into a carbonyl, furnishing halomethyl alkyl derivatives, is reported. Despite the employment of carbenoids as nucleophiles in reactions with carbon-centered electrophiles, sp3-type alkyl halides remain elusive materials for selective one-carbon homologations. Our tactic levers on using carbonyls as starting materials and enables uniformly high yields and chemocontrol. The tactic is flexible and is not limited to carbenoids. Also, diverse carbanion-like species can act as nucleophiles, thus making it of general applicability.

International audience; Despite the worldwide reemergence of the chikungunya virus (CHIKV) and the high morbidity associated with CHIKV infections, there is no approved vaccine or antiviral treatment available. Here, we aimed to identify the target of a novel class of CHIKV inhibitors, i.e., the CHVB series. CHVB compounds inhibit the in vitro replication of CHIKV isolates with 50% effective concentrations in the low-micromolar range. A CHVB-resistant variant (CHVBres) was selected that carried two mutations in the gene encoding nsP1 (responsible for viral RNA capping), one mutation in nsP2, and one mutation in nsP3. Reverse genetics studies demonstrated that both nsP1 mutations were necessary and sufficient to achieve similar to 18-fold resistance, suggesting that CHVB targets viral mRNA capping. Interestingly, CHVBres was cross-resistant to the previously described CHIKV capping inhibitors from the MADTP series, suggesting they share a similar mechanism of action. In enzymatic assays, CHVB inhibited the methyltransferase and guanylyltransferase activities of alphavirus nsP1 proteins. To conclude, we identified a class of CHIKV inhibitors that targets the viral capping machinery. The potent anti-CHIKV activity makes this chemical scaffold a potential candidate for CHIKV drug 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.

The current pandemic threat of COVID‐19, caused by the novel coronavirus SARS‐CoV‐2, not only gives rise to a high number of deaths around the world but also has immense consequences for the worldwide health systems and global economy. Given the fact that this pandemic is still ongoing and there are currently no drugs or vaccines against this novel coronavirus available, this in silico study was conducted to identify a potential novel SARS‐CoV‐2‐inhibitor. Two different approaches were pursued: 1) The Docking Consensus Approach (DCA) is a novel approach, which combines molecular dynamics simulations with molecular docking. 2) The Common Hits Approach (CHA) in contrast focuses on the combination of the feature information of pharmacophore modeling and the flexibility of molecular dynamics simulations. The application of both methods resulted in the identification of 10 compounds with high coronavirus inhibition potential.

A series of new Luotonin A derivatives with substituents at rings A and E was synthesized, together with some E-ring-unsubstituted derivatives. Subsequently, the compound library was examined in silico for their binding into a previously proposed site in the DNA/topoisomerase I binary complex. Whereas no convincing correlation between docking scores and biological data from in vitro assays could be found, one novel 4,9-diamino Luotonin A derivative had strong antiproliferative activity based on massive G2/M phase arrest. As this biological activity clearly differs from the reference compound Camptothecin, this strongly indicates that at least some Luotonin A derivatives may be potent antiproliferative agents, however with a different mode of action.

Pharmacophore‐based techniques are nowadays an important part of many computer‐aided drug design workflows and have been successfully applied for tasks such as virtual screening, lead optimization and de novo design. Natural products, on the other hand, can serve as a valuable source for unconventional molecular scaffolds that stimulate ideas for novel lead compounds in a more diverse chemical space that does not follow the rules of traditional medicinal chemistry. The first part of this review provides a brief introduction to the pharmacophore concept, the methods for pharmacophore model generation, and their applications. The second, concluding part, presents examples for recent, pharmacophore method related research in the field of natural product chemistry. The selected examples show, that pharmacophore‐based methods which get mainly applied on synthetic drug‐like molecules work equally well in the realm of natural products and thus can serve as a valuable tool for researchers in the field of natural product inspired drug design.

The sequential installation of a carbenoid and a hydride into a carbonyl, furnishing halomethyl alkyl derivatives, is reported. Despite the employment of carbenoids as nucleophiles in reactions with carbon-centered electrophiles, sp3-type alkyl halides remain elusive materials for selective one-carbon homologations. Our tactic levers on using carbonyls as starting materials and enables uniformly high yields and chemocontrol. The tactic is flexible and is not limited to carbenoids. Also, diverse carbanion-like species can act as nucleophiles, thus making it of general applicability.

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 &mu, M, respectively. This new series of compounds may serve as a starting point for future antimalarial drug discovery programs.

Melanogenesis controls the formation of melanin pigment whose overproduction is related to various hyperpigmentary disorders in humans. Tyrosinase is a type-3 copper enzyme involved in the rate limiting step of melanin synthesis, therefore its inhibition could represent an efficient way for the development of depigmenting agents. In this work, a combination of pharmacophore and docking-based studies has been employed to screen two in-house 3D compound databases containing about 2,000 molecules from natural and synthetic sources. As result we selected two "hit compounds" which proved to inhibit tyrosinase activity showing IC50 values in the micromolar range.

As graph neural networks are becoming more and more powerful and useful in the field of drug discovery, many pharmaceutical companies are getting interested in utilizing these methods for their own in-house frameworks. This is especially compelling for tasks such as the prediction of molecular properties which is often one of the most crucial tasks in computer-aided drug discovery workflows. The immense hype surrounding these kinds of algorithms has led to the development of many different types of promising architectures and in this review we try to structure this highly dynamic field of AI-research by collecting and classifying 80 GNNs that have been used to predict more than 20 molecular properties using 48 different datasets.

Atypical dopamine reuptake inhibitors, such as modafinil, are used for the treatment of sleeping disorders and investigated as potential therapeutics against cocaine addiction and for cognitive enhancement. Our continuous effort to find modafinil analogues with higher inhibitory activity on and selectivity toward the dopamine transporter (DAT) has previously led to the promising thiazole-containing derivatives CE-103, CE-111, CE-123, and CE-125. Here, we describe the synthesis and activity of a series of compounds based on these scaffolds, which resulted in several new selective DAT inhibitors and gave valuable insights into the structure-activity relationships. Introduction of the second chiral center and subsequent chiral separations provided all four stereoisomers, whereby the S-configuration on both generally exerted the highest activity and selectivity on DAT. The representative compound of this series was further characterized by in silico, in vitro, and in vivo studies that have demonstrated both safety and efficacy profile of this compound class.