Virtual screening-driven discovery of dual 5-HT6/5-HT2A receptor ligands with pro-cognitive properties

Asymmetric Synthesis of Quaternary α-Aryl Stereocentres in Benzofuran-3(2H)-Ones Using Decarboxylative Asymmetric Allylic Alkylation

The Pd-catalysed decarboxylative asymmetric allylic alkylation (DAAA) has been applied to the enantioselective synthesis of sterically hindered benzofuran-3(2H)-one-derived α-aryl-β-keto esters employing the (R,R)-ANDEN phenyl Trost ligand. A range of substrates were synthesised, employing previously developed aryllead triacetate methodology to install various aryl groups. The resulting α-aryl-α-allyl benzofuran-3(2H)-one DAAA products were obtained in moderate to high yields and in enantioselectivities of up to 96 % ee, with the best results observed for substrates containing a di-ortho-substitution pattern on the aryl ring as well as naphthyl-containing substrates.

Discovery and in vitro Evaluation of Novel Serotonin 5-HT2A Receptor Ligands Identified Through Virtual Screening

The 5-HT2A receptor is a molecular target of high pharmacological importance. Ligands of this protein, particularly atypical antipsychotics, are useful in the treatment of numerous mental disorders, including schizophrenia and major depressive disorder. Structure-based virtual screening using a 5-HT2A receptor complex was performed to identify novel ligands for the 5-HT2A receptor, serving as potential antidepressants. From the Enamine screening library, containing over 4 million compounds, 48 molecules were selected for subsequent experimental validation. These compounds were tested against the 5-HT2A receptor in radioligand binding assays. From the tested batch, six molecules were identified as ligands of the main molecular target and were forwarded to a more detailed in vitro profiling. This included radioligand binding assays at 5-HT1A, 5-HT7, and D2 receptors and functional studies at 5-HT2A receptors. These compounds were confirmed to show a binding affinity for at least one of the targets tested in vitro. The success rate for the inactive template-based screening reached 17 %, while it was 9 % for the active template-based screening. Similarity and fragment analysis indicated the structural novelty of the identified compounds. Pharmacokinetics for these molecules was determined using in silico approaches.

Developing a novel benzothiazole-based red-emitting probe for intravital imaging of superoxide anion

Superoxide anion (O2•-), the first generated reactive oxygen species (ROS), is a critical player in cellular signaling network and redox homeostasis. Imaging of O2•-, particularly in vivo, is of concern for further understanding its roles in pathophysiological and pharmacological events. Herein, we designed a novel probe, (E)-4-(5-(2-(benzo[d]thiazol-2-yl)-2-cyanovinyl)furan-2-yl)phenyl trifluoromethane-sulfonate (BFTF), by modifying hydroxyphenyl benzothiazole (a widely used dye scaffold) which includes insertion of both an acrylonitrile unit and a furan ring to extend the total π-conjugation system and to enhance push-pull intramolecular charge transfer process, and utilization of trifluoromethanesulfonate as the response unit. Toward O2•-, the probe features near-infrared fluorescent emission (685 nm), large Stokes shift (135 nm), and deep tissue penetration (300 μm). With its help, we successfully mapped preferential generation of O2•- in HepG2 cells over L02 cells, as well as in A549 over BEAS-2B cells by β-lapachone (an anticancer agent that generates O2•-), and more importantly, visualized overproduction of O2•- in living mice with liver injury induced by acetaminophen (a well-known analgesic and antipyretic drug).

Synthesis and biological evaluation of novel 3-(5-substituted-1H-indol-3-yl)pyrrolidine-2,5-dione derivatives with a dual affinity for serotonin 5-HT1A receptor and SERT

The serotonin 1A (5-HT1A) receptors and serotonin transporter (SERT) are important biological targets in the treatment of diseases of the central nervous system, especially for depression. In this study, new 3-(1H-indol-3-yl)pyrrolidine-2,5-dione derivatives linked with the 3-(1,2,3,6-tetrahydropyridin-4-yl)-1H-indole moiety were synthesised and evaluated for their affinity for 5-HT1A receptor and serotonin reuptake inhibition. Selected compounds were then tested for their affinity for D2, 5-HT2A, 5-HT6 and 5-HT7 receptors, and also in in vitro metabolic stability assays in human microsomes. Finally, in vivo assays allowed us to evaluate the agonist-antagonist properties of pre- and postsynaptic 5-HT1A receptors. 3-(1-(4-(3-(5-methoxy-1H-indol-3-yl)-2,5-dioxopyrrolidin-1-yl)butyl)-1,2,3,6-tetrahydropyridin-4-yl)-1H-indole-5-carbonitrile (4f) emerged as the most promising compound from the series, due to its favourable receptor binding profile (Ki(5-HT1A) = 10.0 nM; Ki(SERT) = 2.8 nM), good microsomal stability and 5-HT1A receptor agonistic activity.

Molecular insights into GPCR mechanisms for drugs of abuse

Substance abuse is on the rise, and while many people may use illicit drugs mainly due to their rewarding effects, their societal impact can range from severe, as is the case for opioids, to promising, as is the case for psychedelics. Common with all these drugs' mechanisms of action are G protein-coupled receptors (GPCRs), which lie at the center of how these drugs mediate inebriation, lethality, and therapeutic effects. Opioids like fentanyl, cannabinoids like tetrahydrocannabinol, and psychedelics like lysergic acid diethylamide all directly bind to GPCRs to initiate signaling which elicits their physiological actions. We herein review recent structural studies and provide insights into the molecular mechanisms of opioids, cannabinoids, and psychedelics at their respective GPCR subtypes. We further discuss how such mechanistic insights facilitate drug discovery, either toward the development of novel therapies to combat drug abuse or toward harnessing therapeutic potential.

Dopamine Receptor Ligand Selectivity-An In Silico/In Vitro Insight

Different dopamine receptor (DR) subtypes are involved in pathophysiological conditions such as Parkinson's Disease (PD), schizophrenia and depression. While many DR-targeting drugs have been approved by the U.S. Food and Drug Administration (FDA), only a very small number are truly selective for one of the DR subtypes. Additionally, most of them show promiscuous activity at related G-protein coupled receptors, thus suffering from diverse side-effect profiles. Multiple studies have shown that combined in silico/in vitro approaches are a valuable contribution to drug discovery processes. They can also be applied to divulge the mechanisms behind ligand selectivity. In this study, novel DR ligands were investigated in vitro to assess binding affinities at different DR subtypes. Thus, nine D2R/D3R-selective ligands (micro- to nanomolar binding affinities, D3R-selective profile) were successfully identified. The most promising ligand exerted nanomolar D3R activity (Ki = 2.3 nM) with 263.7-fold D2R/D3R selectivity. Subsequently, ligand selectivity was rationalized in silico based on ligand interaction with a secondary binding pocket, supporting the selectivity data determined in vitro. The developed workflow and identified ligands could aid in the further understanding of the structural motifs responsible for DR subtype selectivity, thus benefitting drug development in D2R/D3R-associated pathologies such as PD.

Computational Chemistry for the Identification of Lead Compounds for Radiotracer Development

The use of computer-aided drug design (CADD) for the identification of lead compounds in radiotracer development is steadily increasing. Traditional CADD methods, such as structure-based and ligand-based virtual screening and optimization, have been successfully utilized in many drug discovery programs and are highlighted throughout this review. First, we discuss the use of virtual screening for hit identification at the beginning of drug discovery programs. This is followed by an analysis of how the hits derived from virtual screening can be filtered and culled to highly probable candidates to test in in vitro assays. We then illustrate how CADD can be used to optimize the potency of experimentally validated hit compounds from virtual screening for use in positron emission tomography (PET). Finally, we conclude with a survey of the newest techniques in CADD employing machine learning (ML).

Impact of the Substitution Pattern at the Basic Center and Geometry of the Amine Fragment on 5-HT6 and D3R Affinity in the 1H-Pyrrolo[3,2-c]quinoline Series

Salt bridge (SB, double-charge-assisted hydrogen bonds) formation is one of the strongest molecular non-covalent interactions in biological systems, including ligand-receptor complexes. In the case of G-protein-coupled receptors, such an interaction is formed by the conserved aspartic acid (D3.32) residue and the basic moiety of the aminergic ligand. This study aims to determine the influence of the substitution pattern at the basic nitrogen atom and the geometry of the amine moiety at position 4 of 1H-pyrrolo[3,2-c]quinoline on the quality of the salt bridge formed in the 5-HT₆ receptor and D₃ receptor. To reach this goal, we synthetized and biologically evaluated a new series of 1H-pyrrolo[3,2-c]quinoline derivatives modified with various amines. The selected compounds displayed a significantly higher 5-HT₆R affinity and more potent 5-HT₆R antagonist properties when compared with the previously identified compound PZ-1643, a dual-acting 5-HT₆R/D₃R antagonist; nevertheless, the proposed modifications did not improve the activity at D₃R. As demonstrated by the in silico experiments, including molecular dynamics simulations, the applied structural modifications were highly beneficial for the formation and quality of the SB formation at the 5-HT₆R binding site; however, they are unfavorable for such interactions at D₃R.

Discovery of 2-(furan-2-ylmethylene)hydrazine-1-carbothioamide derivatives as novel inhibitors of SARS-CoV-2 main protease

The COVID-19 posed a serious threat to human life and health, and SARS-CoV-2 M^pro has been considered as an attractive drug target for the treatment of COVID-19. Herein, we report 2-(furan-2-ylmethylene)hydrazine-1-carbothioamide derivatives as novel inhibitors of SARS-CoV-2 M^pro developed by in-house library screening and biological evaluation. Similarity search led to the identification of compound F8–S43 with the enzymatic IC₅₀ value of 10.76 μM. Further structure-based drug design and synthetic optimization uncovered compounds F8–B6 and F8–B22 as novel non-peptidomimetic inhibitors of M^pro with IC₅₀ values of 1.57 μM and 1.55 μM, respectively. Moreover, enzymatic kinetic assay and mass spectrometry demonstrated that F8–B6 was a reversible covalent inhibitor of M^pro. Besides, F8–B6 showed low cytotoxicity with CC₅₀ values of more than 100 μM in Vero and MDCK cells. Overall, these novel SARS-CoV-2 M^pro non-peptidomimetic inhibitors provide a useful starting point for further structural optimization.

Identification of Novel Dopamine D2 Receptor Ligands—A Combined In Silico/In Vitro Approach

Diseases of the central nervous system are an alarming global problem showing an increasing prevalence. Dopamine receptor D2 (D2R) has been shown to be involved in central nervous system diseases. While different D2R-targeting drugs have been approved by the FDA, they all suffer from major drawbacks due to promiscuous receptor activity leading to adverse effects. Increasing the number of potential D2R-targeting drug candidates bears the possibility of discovering molecules with less severe side-effect profiles. In dire need of novel D2R ligands for drug development, combined in silico/in vitro approaches have been shown to be efficient strategies. In this study, in silico pharmacophore models were generated utilizing both ligand- and structure-based approaches. Subsequently, different databases were screened for novel D2R ligands. Selected virtual hits were investigated in vitro, quantifying their binding affinity towards D2R. This workflow successfully identified six novel D2R ligands exerting micro- to nanomolar (most active compound KI = 4.1 nM) activities. Thus, the four pharmacophore models showed prospective true-positive hit rates in between 4.5% and 12%. The developed workflow and identified ligands could aid in developing novel drug candidates for D2R-associated pathologies.

Perceiving the Concealed and Unreported Pharmacophoric Features of the 5-Hydroxytryptamine Receptor Using Balanced QSAR Analysis

The 5-hydroxytryptamine receptor 6 (5-HT6) has gained attention as a target for developing therapeutics for Alzheimer’s disease, schizophrenia, cognitive dysfunctions, anxiety, and depression, to list a few. In the present analysis, a larger and diverse dataset of 1278 molecules covering a broad chemical and activity space was used to identify visual and concealed structural features associated with binding affinity for 5-HT6. For this, quantitative structure–activity relationships (QSAR) and molecular docking analyses were executed. This led to the development of a statistically robust QSAR model with a balance of excellent predictivity (R²_tr = 0.78, R²_ex = 0.77), the identification of unreported aspects of known features, and also novel mechanistic interpretations. Molecular docking and QSAR provided similar as well as complementary results. The present analysis indicates that the partial charges on ring carbons present within four bonds from a sulfur atom, the occurrence of sp3-hybridized carbon atoms bonded with donor atoms, and a conditional occurrence of lipophilic atoms/groups from nitrogen atoms, which are prominent but unreported pharmacophores that should be considered while optimizing a molecule for 5-HT6. Thus, the present analysis led to identification of some novel unreported structural features that govern the binding affinity of a molecule. The results could be beneficial in optimizing the molecules for 5-HT6.

In Silico Screening of Natural Compounds for Candidates 5HT6 Receptor Antagonists against Alzheimer's Disease

Alzheimer's disease (AD), a devastating neurodegenerative disease, is the focus of pharmacological research. One of the targets that attract the most attention for the potential therapy of AD is the serotonin 5HT6 receptor, which is the receptor situated exclusively in CNS on glutamatergic and GABAergic neurons. The neurochemical impact of this receptor supports the hypothesis about its role in cognitive, learning, and memory systems, which are of critical importance for AD. Natural products are a promising source of novel bioactive compounds with potential therapeutic potential as a 5HT6 receptor antagonist in the treatment of AD dementia. The ZINC-natural product database was in silico screened in order to find the candidate antagonists of 5-HT6 receptor against AD. A virtual screening protocol that includes both short-and long-range interactions between interacting molecules was employed. First, the EIIP/AQVN filter was applied for in silico screening of the ZINC database followed by 3D QSAR and molecular docking. Ten best candidate compounds were selected from the ZINC Natural Product database as potential 5HT6 Receptor antagonists and were proposed for further evaluation. The best candidate was evaluated by molecular dynamics simulations and free energy calculations.

Overcoming Depression with 5-HT2A Receptor Ligands

Depression is a multifactorial disorder that affects millions of people worldwide, and none of the currently available therapeutics can completely cure it. Thus, there is a need for developing novel, potent, and safer agents. Recent medicinal chemistry findings on the structure and function of the serotonin 2A (5-HT2A) receptor facilitated design and discovery of novel compounds with antidepressant action. Eligible papers highlighting the importance of 5-HT2A receptors in the pathomechanism of the disorder were identified in the content-screening performed on the popular databases (PubMed, Google Scholar). Articles were critically assessed based on their titles and abstracts. The most accurate papers were chosen to be read and presented in the manuscript. The review summarizes current knowledge on the applicability of 5-HT2A receptor signaling modulators in the treatment of depression. It provides an insight into the structural and physiological features of this receptor. Moreover, it presents an overview of recently conducted virtual screening campaigns aiming to identify novel, potent 5-HT2A receptor ligands and additional data on currently synthesized ligands acting through this protein.

Curated Database and Preliminary AutoML QSAR Model for 5-HT1A Receptor

Introduction of a new drug to the market is a challenging and resource-consuming process. Predictive models developed with the use of artificial intelligence could be the solution to the growing need for an efficient tool which brings practical and knowledge benefits, but requires a large amount of high-quality data. The aim of our project was to develop quantitative structure–activity relationship (QSAR) model predicting serotonergic activity toward the 5-HT1A receptor on the basis of a created database. The dataset was obtained using ZINC and ChEMBL databases. It contained 9440 unique compounds, yielding the largest available database of 5-HT1A ligands with specified pKi value to date. Furthermore, the predictive model was developed using automated machine learning (AutoML) methods. According to the 10-fold cross-validation (10-CV) testing procedure, the root-mean-squared error (RMSE) was 0.5437, and the coefficient of determination (R²) was 0.74. Moreover, the Shapley Additive Explanations method (SHAP) was applied to assess a more in-depth understanding of the influence of variables on the model’s predictions. According to to the problem definition, the developed model can efficiently predict the affinity value for new molecules toward the 5-HT1A receptor on the basis of their structure encoded in the form of molecular descriptors. Usage of this model in screening processes can significantly improve the process of discovery of new drugs in the field of mental diseases and anticancer therapy.

Rapid Identification of Potential Drug Candidates from Multi-Million Compounds' Repositories. Combination of 2D Similarity Search with 3D Ligand/Structure Based Methods and In Vitro Screening

Rapid in silico selection of target focused libraries from commercial repositories is an attractive and cost-effective approach in early drug discovery. If structures of active compounds are available, rapid 2D similarity search can be performed on multimillion compounds' databases. This approach can be combined with physico-chemical parameter and diversity filtering, bioisosteric replacements, and fragment-based approaches for performing a first round biological screening. Our objectives were to investigate the combination of 2D similarity search with various 3D ligand and structure-based methods for hit expansion and validation, in order to increase the hit rate and novelty. In the present account, six case studies are described and the efficiency of mixing is evaluated. While sequentially combined 2D/3D similarity approach increases the hit rate significantly, sequential combination of 2D similarity with pharmacophore model or 3D docking enriched the resulting focused library with novel chemotypes. Parallel integrated approaches allowed the comparison of the various 2D and 3D methods and revealed that 2D similarity-based and 3D ligand and structure-based techniques are often complementary, and their combinations represent a powerful synergy. Finally, the lessons we learnt including the advantages and pitfalls of the described approaches are discussed.

N-Skatyltryptamines-Dual 5-HT6R/D2R Ligands with Antipsychotic and Procognitive Potential

A series of N-skatyltryptamines was synthesized and their affinities for serotonin and dopamine receptors were determined. Compounds exhibited activity toward 5-HT1A, 5-HT2A, 5-HT6, and D2 receptors. Substitution patterns resulting in affinity/activity switches were identified and studied using homology modeling. Chosen hits were screened to determine their metabolism, permeability, hepatotoxicity, and CYP inhibition. Several D2 receptor antagonists with additional 5-HT6R antagonist and agonist properties were identified. The former combination resembled known antipsychotic agents, while the latter was particularly interesting due to the fact that it has not been studied before. Selective 5-HT6R antagonists have been shown previously to produce procognitive and promnesic effects in several rodent models. Administration of 5-HT6R agonists was more ambiguous-in naive animals, it did not alter memory or produce slight amnesic effects, while in rodent models of memory impairment, they ameliorated the condition just like antagonists. Using the identified hit compounds 15 and 18, we tried to sort out the difference between ligands exhibiting the D2R antagonist function combined with 5-HT6R agonism, and mixed D2/5-HT6R antagonists in murine models of psychosis.

In Silico Study Examining New Phenylpropanoids Targets with Antidepressant Activity

BACKGROUND

Natural products, such as phenylpropanoids, which are found in essential oils derived from aromatic plants, have been explored during non-clinical psychopharmacology studies, to discover new molecules with relevant pharmacological activities in the central nervous system, especially antidepressant and anxiolytic activities. Major depressive disorder is a highly debilitating psychiatric disorder and is considered to be a disabling public health problem, worldwide, as a primary factor associated with suicide. Current clinically administered antidepressants have late-onset therapeutic actions, are associated with several side effects, and clinical studies have reported that some patients do not respond well to treatment or reach complete remission.

OBJECTIVE

To review important new targets for antidepressant activity and to select phenylpropanoids with antidepressant activity, using Molegro Virtual Docker and Ossis Data Warris, and to verify substances with more promising antidepressant activity.

RESULTS AND CONCLUSION

An in silico molecular modeling study, based on homology, was conducted to determine the three-dimensional structure of the 5-hydroxytryptamine 2A receptor (5- HT2AR), then molecular docking studies were performed and the predisposition for cytotoxicity risk among identified molecules was examined. A model for 5-HT2AR homology, with satisfactory results, was obtained indicating the good stereochemical quality of the model. The phenylpropanoid 4-allyl-2,6-dimethoxyphenol showed the lowest binding energy for 5-HT2AR, with results relevant to the L-arginine/nitric oxide (NO)/cGMP pathway, and showed no toxicity within the parameters of mutagenicity, carcinogenicity, reproductive system toxicity, and skin-tissue irritability, when evaluated in silico; therefore, this molecule can be considered promising for the investigation of antidepressant activity.

Low Basicity as a Characteristic for Atypical Ligands of Serotonin Receptor 5-HT2

Serotonin receptors are extensively examined by academic and industrial researchers, due to their vital roles, which they play in the organism and constituting therefore important drug targets. Up to very recently, it was assumed that the basic nitrogen in compound structure is a necessary component to make it active within this receptor system. Such nitrogen interacts in its protonated form with the aspartic acid from the third transmembrane helix (D3x32) forming a hydrogen bond tightly fitting the ligand in the protein binding site. However, there are several recent studies that report strong serotonin receptor affinity also for compounds without a basic moiety in their structures. In the study, we carried out a comprehensive in silico analysis of the low-basicity phenomenon of the selected serotonin receptor ligands. We focused on the crystallized representatives of the proteins of 5-HT_1B, 5-HT_2A, 5-HT_2B, and 5-HT_2C receptors, and examined the problem both from the ligand- and structure-based perspectives. The study was performed for the native proteins, and for D3x32A mutants. The investigation resulted in the determination of nonstandard structural requirements for activity towards serotonin receptors, which can be used in the design of new nonbasic ligands.

Imidazopyridine-Based 5-HT6 Receptor Neutral Antagonists: Impact of N1-Benzyl and N1-Phenylsulfonyl Fragments on Different Receptor Conformational States

G-protein coupled receptors (GPCRs) exist in an equilibrium of multiple conformational states, including different active states, which depend on the nature of the bound ligand. In consequence, different conformational states can initiate specific signal transduction pathways. The study identified compound 7e, which acts as a potent 5-hydroxytryptamine type 6 receptor (5-HT₆R) neutral antagonist at Gs and does not impact neurite growth (process controlled by Cdk5). MD simulations highlighted receptor conformational changes for 7e and inverse agonist PZ-1444. In cell-based assays, neutral antagonists of the 5-HT₆R (7e and CPPQ), but not inverse agonists (SB-258585, intepirdine, PZ-1444), displayed glioprotective properties against 6-hydroxydopamine-induced and doxorubicin-induced cytotoxicity. These suggest that targeting the activated conformational state of the 5-HT₆R with neutral antagonists implicates the protecting properties of astrocytes. Additionally, 7e prevented scopolamine-induced learning deficits in the novel object recognition test in rats. We propose 7e as a probe for further understanding of the functional outcomes of different states of the 5-HT₆R.

Merging Ligand-Based and Structure-Based Methods in Drug Discovery: An Overview of Combined Virtual Screening Approaches

Virtual screening (VS) is an outstanding cornerstone in the drug discovery pipeline. A variety of computational approaches, which are generally classified as ligand-based (LB) and structure-based (SB) techniques, exploit key structural and physicochemical properties of ligands and targets to enable the screening of virtual libraries in the search of active compounds. Though LB and SB methods have found widespread application in the discovery of novel drug-like candidates, their complementary natures have stimulated continued efforts toward the development of hybrid strategies that combine LB and SB techniques, integrating them in a holistic computational framework that exploits the available information of both ligand and target to enhance the success of drug discovery projects. In this review, we analyze the main strategies and concepts that have emerged in the last years for defining hybrid LB + SB computational schemes in VS studies. Particularly, attention is focused on the combination of molecular similarity and docking, illustrating them with selected applications taken from the literature.

A dual-acting 5-HT6 receptor inverse agonist/MAO-B inhibitor displays glioprotective and pro-cognitive properties

The complex etiology of Alzheimer's disease has initiated a quest for multi-target ligands to address the multifactorial causes of this neurodegenerative disorder. In this context, we designed dual-acting 5-HT₆ receptor (5-HT₆R) antagonists/MAO-B inhibitors using pharmacophore hybridization strategy. Our approach involved linking priviliged scaffolds of 5-HT₆R with aryloxy fragments derived from reversible and irreversible MAO-B inhibitors. The study identified compound 48 that acts as an inverse agonist of 5-HT₆R at G_s signaling and an irreversible MAO-B inhibitor. Compound 48 showed moderate metabolic stability in rat microsomal assay, artificial membrane permeability, no hepatotoxicity, and it was well distributed to the brain. Additionally, 48 showed glioprotective properties in a model of cultured astrocytes using 6-OHDA as the cytotoxic agent. Finally, compound 48 (MED = 1 mg/kg, p.o.) fully reversed memory deficits in the NOR task induced by scopolamine in rats. A better understanding of effects exerted by dual-acting 5-HT₆R/MAO-B modulators may impact the future development of neurodegenerative-directed treatment strategies.