From NMR to AI: Designing a Novel Chemical Representation to Enhance Machine Learning Predictions of Physicochemical Properties.

A novel approach to the utilization of nuclear magnetic resonance (NMR) spectroscopy data in the prediction of logD through machine learning algorithms is shown. In the analysis, a data set of 754 chemical compounds, organized into 30 clusters, was evaluated using advanced machine learning models, such as Support Vector Regression (SVR), Gradient Boosting, and AdaBoost, and comprehensive validation and testing methods were employed, including 10-fold cross-validation, bootstrapping, and leave-one-out. The study revealed the superior performance of the Bucket Integration method for dimensionality reduction, consistently yielding the lowest root mean square error (RMSE) across all data sets and normalization schemes. The SVR prediction models demonstrated remarkable computational efficiency and low cost, with the best RMSE value reaching 0.66. Our best model outperformed existing tools like JChem Suite's logD Predictor (0.91) and CplogD (1.27), and a comparison with traditional molecular representations yielded a comparable RMSE (0.50), emphasizing the robustness of our NMR data integration. The widespread availability of NMR data in pharmaceutical and industrial research presents an untapped resource for predictive modeling, highlighting the need for accessible methodologies like ours that complement the analytical toolbox beyond conventional 2D approaches. Our approach, designed to leverage the rich spatial data from NMR spectroscopy, provides additional insights and enriches drug discovery and computational chemistry with a freely accessible tool.

The Pivotal Distinction between Antagonists' and Agonists' Binding into Dopamine D4 Receptor-MD and FMO/PIEDA Studies.

The dopamine D4 receptor (D4R) is a promising therapeutic target in widespread diseases, and the search for novel agonists and antagonists appears to be clinically relevant. The mechanism of binding to the receptor (R) for antagonists and agonists varies. In the present study, we conducted an in-depth computational study, teasing out key similarities and differences in binding modes, complex dynamics, and binding energies for D4R agonists and antagonists. The dynamic network method was applied to investigate the communication paths between the ligand (L) and G-protein binding site (GBS) of human D4R. Finally, the fragment molecular orbitals with pair interaction energy decomposition analysis (FMO/PIEDA) scheme was used to estimate the binding energies of L-R complexes. We found that a strong salt bridge with D3.32 initiates the inhibition of the dopamine D4 receptor. This interaction also occurs in the binding of agonists, but the change in the receptor conformation to the active state starts with interaction with cysteine C3.36. Such a mechanism may arise in the case of agonists unable to form a hydrogen bond with the serine S5.46, considered, so far, to be crucial in the activation of GPCRs. The energy calculations using the FMO/PIEDA method indicate that antagonists show higher residue occupancy of the receptor binding site than agonists, suggesting they could form relatively more stable complexes. Additionally, antagonists were characterized by repulsive interactions with S5.46 distinguishing them from agonists.

Synthesis, computational simulations and biological evaluation of new dual 5HT1A/5HT7 receptor ligands based on purine-2,6-dione scaffold.

The new dual 5HT1A/5HT7 receptor ligands were designed based on the purine-2,6-dione scaffold with the fluorine atom. Twenty-one new derivatives were synthesized, and their structure-activity relationship was summarized. Compound 11 (7-(2-(3-fluorophenyl)-2-oxoethyl)-8-((4-(4-(2-methoxyphenyl)piperazin-1-yl)butyl)amino)-1,3-dimethyl-3,7-dihydro-1H-purine-2,6-dione) showed the highest affinity to 5HT1AR and 5HT7R, and was the most potent antagonist of 5-HT1AR (Kb = 0.26 ± 0.1 nM) which activity can be to reference compound NAN-190 (Kb = 0.26 ± 0.1 nM). The experimentally established physicochemical parameters of compound 11 showed that compound, as slightly ionized in the blood, could penetrate the blood-brain barrier. A molecular docking study showed that the fluorine substitution introduces additional stabilization effects on binding to 5HT1A/5HT7Rs. In animal assays of depression and anxiety, compound 11 revealed activity in terms of dosage compared to marketed psychotropics such as fluoxetine, citalopram, and sertraline.

Isomeric Activity Cliffs-A Case Study for Fluorine Substitution of Aminergic G Protein-Coupled Receptor Ligands.

Currently, G protein-coupled receptors (GPCRs) constitute a significant group of membrane-bound receptors representing more than 30% of therapeutic targets. Fluorine is commonly used in designing highly active biological compounds, as evidenced by the steadily increasing number of drugs by the Food and Drug Administration (FDA). Herein, we identified and analyzed 898 target-based F-containing isomeric analog sets for SAR analysis in the ChEMBL database-FiSAR sets active against 33 different aminergic GPCRs comprising a total of 2163 fluorinated (1201 unique) compounds. We found 30 FiSAR sets contain activity cliffs (ACs), defined as pairs of structurally similar compounds showing significant differences in affinity (≥50-fold change), where the change of fluorine position may lead up to a 1300-fold change in potency. The analysis of matched molecular pair (MMP) networks indicated that the fluorination of aromatic rings showed no clear trend toward a positive or negative effect on affinity. Additionally, we propose an in silico workflow (including induced-fit docking, molecular dynamics, quantum polarized ligand docking, and binding free energy calculations based on the Generalized-Born Surface-Area (GBSA) model) to score the fluorine positions in the molecule.

Tuning the Biological Activity of PI3Kδ Inhibitor by the Introduction of a Fluorine Atom Using the Computational Workflow.

As a member of the class I PI3K family, phosphoinositide 3-kinase δ (PI3Kδ) is an important signaling biomolecule that controls immune cell differentiation, proliferation, migration, and survival. It also represents a potential and promising therapeutic approach for the management of numerous inflammatory and autoimmune diseases. We designed and assessed the biological activity of new fluorinated analogues of CPL302415, taking into account the therapeutic potential of our selective PI3K inhibitor and fluorine introduction as one of the most frequently used modifications of a lead compound to further improve its biological activity. In this paper, we compare and evaluate the accuracy of our previously described and validated in silico workflow with that of the standard (rigid) molecular docking approach. The findings demonstrated that a properly fitted catalytic (binding) pocket for our chemical cores at the induced-fit docking (IFD) and molecular dynamics (MD) stages, along with QM-derived atomic charges, can be used for activity prediction to better distinguish between active and inactive molecules. Moreover, the standard approach seems to be insufficient to score the halogenated derivatives due to the fixed atomic charges, which do not consider the response and indictive effects caused by fluorine. The proposed computational workflow provides a computational tool for the rational design of novel halogenated drugs.

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.

An exit beyond the pharmacophore model for 5-HT6R agents - a new strategy to gain dual 5-HT6/5-HT2A action for triazine derivatives with procognitive potential.

This research allowed us to find the first highly potent 5-HT6/5-HT2A receptor (5-HT6/5-HT2AR) dual antagonists in a group of 1,3,5-triazine compounds as a result of an exit beyond the hydrophobic feature of the pharmacophore model for 5-HT6R antagonists. Design and synthesis of the series (2-16) of new O- and S-containing ether derivatives of 1,3,5-triazines with the double-ring aromatic region have been performed. The new compounds were examined within the comprehensive pharmacological screening, including: radioligand binding assays, functional and ADMET studies in vitro as well as behavioral tests in rats. Crystallographic aspects and computer-aided structure-activity relationship were analyzed, as well. The comprehensive approach led to selection of compound 12 (4-(4-methylpiperazin-1-yl)-6-(2-(naphthalen-2-ylthio)propan-2-yl)-1,3,5-triazin-2-amine) with the most significant dual 5-HT6/5-HT2AR antagonistic action (5-HT6R Ki = 11 nM, 5-HT2AR Ki = 39 nM). Moreover, the compound 12 has satisfactory ADMETox properties in vitro, i.e.: the high permeability through biological membranes, high metabolic stability, neither mutagenic nor hepatotoxic effects, and moderate ability to inhibit CYP3A4. Above all, 12 showed ability to reverse the pharmacologically-induced (MK-801) memory impairment at low doses (1-3 mg/kg) in Novel Object Recognition (NOR) test in rats. Our results indicate a promising potency of dual 5-HT6/5-HT2AR antagonism in the search for novel strategy to fight Alzheimer's disease, which remains an unmet clinical need.

Hydrogen Bonds with Fluorine in Ligand-Protein Complexes-the PDB Analysis and Energy Calculations.

Fluorine is a common substituent in medicinal chemistry and is found in up to 50% of the most profitable drugs. In this study, a statistical analysis of the nature, geometry, and frequency of hydrogen bonds (HBs) formed between the aromatic and aliphatic C-F groups of small molecules and biological targets found in the Protein Data Bank (PDB) repository was presented. Interaction energies were calculated for those complexes using three different approaches. The obtained results indicated that the interaction energy of F-containing HBs is determined by the donor-acceptor distance and not by the angles. Moreover, no significant relationship between the energies of HBs with fluorine and the donor type was found, implying that fluorine is a weak HB acceptor for all types of HB donors. However, the statistical analysis of the PDB repository revealed that the most populated geometric parameters of HBs did not match the calculated energetic optima. In a nutshell, HBs containing fluorine are forced to form due to the stronger ligand-receptor neighboring interactions, which make fluorine the "donor's last resort".

Fast and Noninvasive Hair Test for Preliminary Diagnosis of Mood Disorders.

The main objective of this study was to develop a test for the fast and noninvasive prediagnosis of mood disorders based on the noninvasive analysis of hair samples. The database included 75 control subjects (who were not diagnosed with depression) and 40 patients diagnosed with mood disorders such as depression or bipolar disorder. Both women and men, aged 18-65 years, participated in the research. After taking the hair samples, they were washed (methanol-water-methanol by shaking in a centrifuge for two min) and air-dried in a fume hood. Each hair collection was analyzed using Fourier transform infrared spectroscopy attenuated total reflection (ATR-FTIR) spectroscopy. Subsequently, the results obtained were analyzed based on chemometric methods: hierarchical cluster analysis (HCA) and principal component analysis (PCA). As a results of the research conducted, potential differences were noticed. There was a visible change in the spectra intensity at around 2800-3100 cm-1 and smaller differences around 1460 cm-1; the bands can be assigned to protein vibrations. However, these are preliminary studies that provide a good basis for the development of a test for the initial diagnosis of mood disorders.

Influence of Fluorine Substitution on Nonbonding Interactions in Selected Para-Halogeno Anilines.

A series of 4-halogeno aniline derivatives was studied employing combined theoretical and experimental methods (i. e. crystal structure analysis and vibrational spectroscopies). This simplified model system was selected to shed light on the impact of fluorine substitution on the formation of noncovalent interactions such as halogen bonds (XBs) and hydrogen bonds (HBs), which are key interactions in fluorinated/halogenated drug-protein complex formation. Comparative analysis of three previously reported and five newly determined crystal structures indicated that, in most cases, 2-fluoro and 2,6-difluoro substitution of 4-X anilines increases the ability of adjacent amine to form strong N-H⋅⋅⋅N HBs. Additionally, fluorine substituents in the difluorinated derivatives are competitive and attractive HB and XB acceptors and increase the probability of halogen-halogen contacts. A peculiar observation was made for 4-iodoaniline and 2,6-difluoro-4-iodoaniline, which form distinct interaction patterns compared to the corresponding 4-Cl and 4-Br analogs. The observed intramolecular N-H⋅⋅⋅F interactions lead to additional NH bands in the FT-IR spectra.

Pharmacoprint: A Combination of a Pharmacophore Fingerprint and Artificial Intelligence as a Tool for Computer-Aided Drug Design.

Structural fingerprints and pharmacophore modeling are methodologies that have been used for at least 2 decades in various fields of cheminformatics, from similarity searching to machine learning (ML). Advances in in silico techniques consequently led to combining both these methodologies into a new approach known as the pharmacophore fingerprint. Herein, we propose a high-resolution, pharmacophore fingerprint called Pharmacoprint that encodes the presence, types, and relationships between pharmacophore features of a molecule. Pharmacoprint was evaluated in classification experiments by using ML algorithms (logistic regression, support vector machines, linear support vector machines, and neural networks) and outperformed other popular molecular fingerprints (i.e., ECFP4, Estate, MACCS, PubChem, Substructure, Klekota-Roth, CDK, Extended, and GraphOnly) and the ChemAxon pharmacophoric features fingerprint. Pharmacoprint consisted of 39 973 bits; several methods were applied for dimensionality reduction, and the best algorithm not only reduced the length of the bit string but also improved the efficiency of the ML tests. Further optimization allowed us to define the best parameter settings for using Pharmacoprint in discrimination tests and for maximizing statistical parameters. Finally, Pharmacoprint generated for three-dimensional (3D) structures with defined hydrogens as input data was applied to neural networks with a supervised autoencoder for selecting the most important bits and allowed us to maximize the Matthews correlation coefficient up to 0.962. The results show the potential of Pharmacoprint as a new, perspective tool for computer-aided drug design.

Mutual Support of Ligand- and Structure-Based Approaches-To What Extent We Can Optimize the Power of Predictive Model? Case Study of Opioid Receptors.

The process of modern drug design would not exist in the current form without computational methods. They are part of every stage of the drug design pipeline, supporting the search and optimization of new bioactive substances. Nevertheless, despite the great help that is offered by in silico strategies, the power of computational methods strongly depends on the input data supplied at the stage of the predictive model construction. The studies on the efficiency of the computational protocols most often focus on global efficiency. They use general parameters that refer to the whole dataset, such as accuracy, precision, mean squared error, etc. In the study, we examined machine learning predictions obtained for opioid receptors (mu, kappa, delta) and focused on cases for which the predictions were the most accurate and the least accurate. Moreover, by using docking, we tried to explain prediction errors. We attempted to develop a rule of thumb, which can help in the prediction of compound activity towards opioid receptors via docking, especially those that have been incorrectly predicted by machine learning. We found out that although the combination of ligand- and structure-based path can be beneficial for the prediction accuracy, there still remain cases that cannot be reliably predicted by any available modeling method. In addition to challenging ligand- and structure-based predictions, we also examined the role of the application of machine-learning methods in comparison to simple statistical methods for both standard ligand-based representations (molecular fingerprints) and interaction fingerprints. All approaches were confronted in both classification (where compounds were assigned to the group of active and inactive group constructed on the basis of Ki values) and regression (where exact Ki value was predicted) experiments.

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.

Theoretical Investigations on Interactions of Arylsulphonyl Indazole Derivatives as Potential Ligands of VEGFR2 Kinase.

Vascular endothelial growth factor receptor 2 (VEGFR2) is a key receptor in the angiogenesis process. The VEGFR2 expression is upregulated in many cancers so this receptor is an important target for anticancer agents. In the present paper, we analyse interactions of several dimeric indazoles, previously investigated for anticancer activity, with the amino acids present in the VEGFR2 binding pocket. Using the docking method and MD simulations as well as theoretical computations (SAPT0, PIEDA, semi-empirical PM7), we confirmed that these azoles can efficiently bind into the kinase pocket and their poses can be stabilised by the formation of hydrogen bonds, π-π stacking, π-cation, and hybrid interactions with some amino acids of the kinase cavity like Ala866, Lys868, Glu885, Thr916, Glu917, and Phe918.

Synthesis and computer-aided analysis of the role of linker for novel ligands of the 5-HT6 serotonin receptor among substituted 1,3,5-triazinylpiperazines.

A series of 2-amino-4-(4-methylpiperazin-1-yl)-1,3,5-triazines was designed based on previously published 2-amino-4-benzyl-(4-methylpiperazin-1-yl)-1,3,5-triazines in order to evaluate the role of a linker between the triazine moiety and an aromatic substituent for the human serotonin 5-HT6 receptor affinity. As new linkers two carbon atoms (ethyl or ethenyl) or an oxyalkyl chain (methoxy, 2-ethoxy, 2-propoxy) were introduced. Affinities of the compounds for the 5-HT6R as the main target, and for the 5-HT1AR, 5-HT7R and D2R as competitive ones, were determined in the radioligand binding assays. Docking to the 5-HT6R homology model was performed to support SAR analysis. Results showed that the branching of the methoxyl linker increased affinity for the human 5-HT6R whereas an unsaturated bond within the linker dramatically reduced desirable activity. Both experimental and theoretical studies confirmed the previously postulated beneficial role of the aromatic size for interaction with the 5-HT6R. Thus, the largest naphthyl moiety yielded the highest activity. In particular, 4-(4-methylpiperazin-1-yl)-6-(1-(naphthalen-1-yloxy)ethyl)-1,3,5-triazin-2-amine (24), the most potent 5-HT6R agent found (Ki = 23 nM), can be a new lead structure for further search and development.

The Significance of Halogen Bonding in Ligand-Receptor Interactions: The Lesson Learned from Molecular Dynamic Simulations of the D4 Receptor.

Recently, a computational approach combining a structure-activity relationship library containing pairs of halogenated ligands and their corresponding unsubstituted ligands (called XSAR) with QM-based molecular docking and binding free energy calculations was developed and used to search for amino acids frequently targeted by halogen bonding, also known as XB hot spots. However, the analysis of ligand-receptor complexes with halogen bonds obtained by molecular docking provides a limited ability to study the role and significance of halogen bonding in biological systems. Thus, a set of molecular dynamics simulations for the dopamine D4 receptor, recently crystallized with the antipsychotic drug nemonapride (5WIU), and the five XSAR sets were performed to verify the identified hot spots for halogen bonding, in other words, primary (V5x40), and secondary (S5x43, S5x461 and H6x55). The simulations confirmed the key role of halogen bonding with V5x40 and H6x55 and supported S5x43 and S5x461. The results showed that steric restrictions and the topology of the molecular core have a crucial impact on the stabilization of the ligand-receptor complex by halogen bonding.

Are the Hydantoin-1,3,5-triazine 5-HT6R Ligands a Hope to a Find New Procognitive and Anti-Obesity Drug? Considerations Based on Primary In Vivo Assays and ADME-Tox Profile In Vitro.

Though the 5-HT6 serotonin receptor is an important target giving both agonists and antagonists similar therapeutic potency in the treatment of topic CNS-diseases, no 5-HT6R ligand has reached the pharmaceutical market yet due to the too narrow chemical space of the known 5-HT6R agents and insufficient "drugability." Recently, a new group of non-indole and non-sulfone hydantoin-triazine 5-HT6R ligands was found, where 3-((4-amino-6-(4-methylpiperazin-1-yl)-1,3,5-triazin-2-yl)methyl)-5-methyl-5-(naphthalen-2-yl)imidazolidine-2,4-dione (KMP-10) was the most active member. This study is focused on wider pharmacological and "druglikeness" characteristics for KMP-10. A computer-aided insight into molecular interactions with 5-HT6R has been performed. "Druglikeness" was examined using an eight-test panel in vitro, i.e., a parallel artificial membrane permeability assay (PAMPA), and Caco-2 permeability-, P-glycoprotein (Pgp) affinity-, plasma protein binding-, metabolic stability- and drug-drug interaction-assays, as well as mutagenicity- and HepG2-hepatotoxicity risk tests. Behavioral studies in vivo, i.e., elevated plus-maze (EPM) and novel object recognition (NOR) tests, were performed. Extended studies on the influence of KMP-10 on rats' metabolism, including biochemical tests, were conducted in vivo. Results indicated significant anxiolytic and precognitive properties, as well as some anti-obesity properties in vivo, and it was found to satisfy the "druglikeness" profile in vitro for KMP-10. The compound seems to be a good lead-structure and candidate for wider pharmacological studies in search for new CNS-drugs acting via 5-HT6R.

Salt Bridge in Ligand-Protein Complexes-Systematic Theoretical and Statistical Investigations.

Although the salt bridge is the strongest among all known noncovalent molecular interactions, no comprehensive studies have been conducted to date to examine its role and significance in drug design. Thus, a systematic study of the salt bridge in biological systems is reported herein, with a broad analysis of publicly available data from Protein Data Bank, DrugBank, ChEMBL, and GPCRdb. The results revealed the distance and angular preferences as well as privileged molecular motifs of salt bridges in ligand-receptor complexes, which could be used to design the strongest interactions. Moreover, using quantum chemical calculations at the MP2 level, the energetic, directionality, and spatial variabilities of salt bridges were investigated using simple model systems mimicking salt bridges in a biological environment. Additionally, natural orbitals for chemical valence (NOCV) combined with the extended-transition-state (ETS) bond-energy decomposition method (ETS-NOCV) were analyzed and indicated a strong covalent contribution to the salt bridge interaction. The present results could be useful for implementation in rational drug design protocols.

Pyrroloquinoline scaffold-based 5-HT6R ligands: Synthesis, quantum chemical and molecular dynamic studies, and influence of nitrogen atom position in the scaffold on affinity.

Based on pyrroloquinoline scaffold bearing 5-HT2C agonists, a series of arylsulfonamide derivatives of 1H-pyrrolo[2,3-f]quinoline and 1H-pyrrolo[3,2-h]quinoline, substituted at position 3 with tetrahydropyridine, were synthesized and evaluated in vitro for their affinity for 5-HT6 receptors. A structure-activity relationship study showed that the 1H-pyrrolo[3,2-h]quinoline scaffold was more favorable for 5-HT6R binding than the 1H-pyrrolo[2,3-f]quinoline one, suggesting dependence upon the type of condensation of the pyrrole and quinoline rings. As revealed by quantum-chemical calculations and molecular dynamic studies, position of the quinoline nitrogen atom in the planar pyrroloquinoline skeleton might affect the spatial orientation of the arylsulfonyl fragment, as a result of structure stabilization by internal hydrogen bonds.

Computer-Aided Studies for Novel Arylhydantoin 1,3,5-Triazine Derivatives as 5-HT6 Serotonin Receptor Ligands with Antidepressive-Like, Anxiolytic and Antiobesity Action In Vivo.

This study focuses on the design, synthesis, biological evaluation, and computer-aided structure-activity relationship (SAR) analysis for a novel group of aromatic triazine-methylpiperazines, with an hydantoin spacer between 1,3,5-traizine and the aromatic fragment. New compounds were synthesized and their affinities for serotonin 5-HT6, 5-HT1A, 5-HT2A, 5-HT7, and dopamine D2 receptors were evaluated. The induced-fit docking (IFD) procedure was performed to explore the 5-HT6 receptor conformation space employing two lead structures. It resulted in a consistent binding mode with the activity data. For the most active compounds found in each modification line, anti-obesity and anti-depressive-like activity in vivo, as well as "druglikeness" in vitro, were examined. Two 2-naphthyl compounds (18 and 26) were identified as the most active 5-HT6R agents within each lead modification line, respectively. The 5-(2-naphthyl)hydantoin derivative 26, the most active one in the series (5-HT6R: Ki = 87 nM), displayed also significant selectivity towards competitive G-protein coupled receptors (6⁻197-fold). Docking studies indicated that the hydantoin ring is stabilized by hydrogen bonding, but due to its different orientation, the hydrogen bonds form with S5.44 and N6.55 or Q6.58 for 18 and 26, respectively. Compound 26 exerted anxiolytic-like and antidepressant-like activities. Importantly, it demonstrated anti-obesity properties in animals fed palatable feed, and did not show toxic effects in vitro.