Interaction of arylpiperazine ligands with the hydrophobic part of the 5-HT1A receptor binding site

Identification of novel dual acting ligands targeting the adenosine A2A and serotonin 5-HT1A receptors

GPCRs are a family of transmembrane receptors that are profoundly linked to various neurological disorders, among which is Parkinson's disease (PD). PD is the second most ubiquitous neurological disorder after Alzheimer's disease, characterized by the depletion of dopamine in the central nervous system due to the impairment of dopaminergic neurons, leading to involuntary movements or dyskinesia. The current standard of care for PD is Levodopa, a dopamine precursor, yet the chronic use of this agent can exacerbate motor symptoms. Recent studies have investigated the effects of combining A2AR antagonist and 5-HT1A agonist on dyskinesia and motor complications in animal models of PD. It has been proved that the drug combination has significantly improved involuntary movements while maintaining motor activity, highlighting as a result new lines of therapy for PD treatments, through the regulation of both receptors. Using a combination of ligand-based pharmacophore modelling, virtual screening, and molecular dynamics simulation, this study intends on identifying potential dual-target compounds from IBScreen. Results showed that the selected models displayed good enrichment metrics with a near perfect receiver operator characteristic (ROC) and Area under the accumulation curve (AUAC) values, signifying that the models are both specific and sensitive. Molecular docking and ADMET analysis revealed that STOCK2N-00171 could be potentially active against A2AR and 5-HT1A. Post-MD analysis confirmed that the ligand exhibits a stable behavior throughout the simulation while maintaining crucial interactions. These results imply that STOCK2N-00171 can serve as a blueprint for the design of novel and effective dual-acting ligands targeting A2AR and 5-HT1A.Communicated by Ramaswamy H. Sarma.

Insights of ligand binding in modeled h5-HT1A receptor: homology modeling, docking, MM-GBSA, screening and molecular dynamics

The pharmacologically characterized receptor subtype of the serotonin family, the 5HT1A receptor is implicated in the pathophysiology and treatment of depression and anxiety-related disorders. Being the most extensively targeted receptor for developing novel antidepressants and anxiolytics, a near-ideal theoretical model can aid in high-throughput screening of promising drug candidates. However, the design of potential drug candidates suffers owing to a lack of complete structural information. In this work, homology models of 5-HT1A receptor are generated using two distinct alignments (CW and PSTA) and model building methods (KB and EB). The developed models are validated for virtual screening using a ligand dataset of agonists and antagonists. The best-suited model was efficient in discriminating agonist/antagonist binding. Correlation plots between pKi and docking (R²_agonist≥ 0.6, R²_antagonist≥ 0.7) and MM-GBSA dG bind values (R²_agonist≥ 0.5, R²_antagonist≥ 0.7) revealed optimum corroboration between in vitro and in silico outcomes, which further suggested the usefulness of the developed model for the design of high-affinity probes for the neurological disorders.Communicated by Ramaswamy H. Sarma.

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.

Design, synthesis and biological evaluation of novel serotonin and dopamine receptor ligands being 6-bromohexyl saccharine derivatives

Due to numerous side effects of current antidepressants, the search for new, safer bioactive compounds is still a valid research topic in medical chemistry. In our research we decided to synthesize and determine SAR for new hexyl arylpiperazines (LACPs) derivated with saccharin moiety. High biological activity has been explained using molecular modelling methods. The compounds obtained show high affinity for the 5-HT_1A (compound 18, K_i = 4 nM - antagonist mode) and D₂ (compound 15, K_i = 7 nM - antagonist mode) receptor, and in some cases also 5-HT₇ receptor (compound 17, K_i = 20 nM). A preliminary ADME analysis showed that the compounds exhibit CNS drugability properties. We have proved that carbon-chain lengthening may have a beneficial effect on increasing the activity towards serotonin and dopamine receptors.

Potentiometric Signal Transduction for Selective Determination of 1-(3-Chlorophenyl)piperazine “Legal Ecstasy” Through Biomimetic Interaction Mechanism

1-(3-chlorophenyl)piperazine (mCPP) is a wide spread new psychoactive substance produces stimulant and hallucinogenic effects similar to those sought from ecstasy. Hence, in the recent years, mCPP has been introduced by the organized crime through the darknet as a part of the illicit ecstasy market with a variable complex profile of pharmacologically active substances that pose problematic risk patterns among people who take these seized products. Accordingly, the design of selective sensors for the determination of mCPP is a very important demand. In this respect, a supramolecular architecture; [Na(15-crown-5)][BPh4] from the assembly of 15-crown-5 and sodium tetraphenylboron has been utilized as an ionophore, for the first time in the selective recognition of mCPP in conjunction with potassium tetrakis(p-chlorophenyl)borate and dioctylphthalate through polymeric membrane ion sensors. The ionophore exhibited a strong binding affinity that resulted in a high sensitivity with a slope closed to the ideal Nernstian value; 58.9 ± 0.43 mV/decade, a larger dynamic range from 10−6 to 10−2 M, a lower limit of detection down to 5.0 × 10−7 M and a fast response time of 5 s. Very important also is it was afforded excellent selectivity towards mCPP over psychoactive substances of major concern, providing a potentially useful system for the determination of mCPP in the illicit market. On comparison with the natural β-cyclodextrin as an ionophore, it exhibited more sensitivity and selectivity estimated to be the superior.

New Serotoninergic Ligands Containing Indolic and Methyl Indolic Nuclei: Synthesis and In Vitro Pharmacological Evaluation

BACKGROUND

Serotonin is an important biogenic amine and is implicated in wideranging physiological and physiopathological processes. Pharmacological manipulation of the serotoninergic system is believed to have a great therapeutic potential.

OBJECTIVES

In order to identify selective ligands for 5-HT1A, 5-HT2A and 5-HT2C receptors two series of 4-substituted piperazine derivatives, bearing indolic or methyl indolic nuclei, were synthesized.

METHODS

All the compounds, synthesized by standard solution methods, were evaluated for 5- HT1A, 5-HT2A and 5-HT2C receptors. The highest affine and selective compounds have been evaluated also on dopaminergic (D1 and D2) and adrenergic (α1A and α2A) receptors.

RESULTS

Several of the newly synthesized molecules showed affinity in the nanomolar range for 5- HT1A, 5-HT2A and 5-HT2C receptors and moderate to no affinity for other relevant receptors (D1, D2, α1A and α2A).

CONCLUSION

Compounds 7f and 10a showed a nanomolar affinity towards 5-HT1A with an in vitro pharmacologic profile compatible with antipsychotic drugs.

From Homology Models to a Set of Predictive Binding Pockets-a 5-HT1A Receptor Case Study

Despite its remarkable importance in the arena of drug design, serotonin 1A receptor (5-HT1A) has been elusive to the X-ray crystallography community. This lack of direct structural information not only hampers our knowledge regarding the binding modes of many popular ligands (including the endogenous neurotransmitter-serotonin), but also limits the search for more potent compounds. In this paper we shed new light on the 3D pharmacological properties of the 5-HT1A receptor by using a ligand-guided approach (ALiBERO) grounded in the Internal Coordinate Mechanics (ICM) docking platform. Starting from a homology template and set of known actives, the method introduces receptor flexibility via Normal Mode Analysis and Monte Carlo sampling, to generate a subset of pockets that display enriched discrimination of actives from inactives in retrospective docking. Here, we thoroughly investigated the repercussions of using different protein templates and the effect of compound selection on screening performance. Finally, the best resulting protein models were applied prospectively in a large virtual screening campaign, in which two new active compounds were identified that were chemically distinct from those described in the literature.

Quantitative Structure-Activity Relationship for High Affinity 5-HT1A Receptor Ligands Based on Norm Indexes

Arylpiperazine derivatives are promising 5-hydroxytryptamine (5-HT) receptor ligands which can inhibit serotonin reuptake effectively. In this work, some norm index descriptors were proposed and further utilized to develop a model for predicting 5-HT1A receptor affinity (pKi) of 88 arylpiperazine derivatives. Results showed that this new model could provide satisfactory predictions with the square of the correction coefficient (R(2)) of 0.8891 and the squared correlation coefficient of cross-validation (Q(2)) of 0.8082, respectively. In addition, the applicability domain of this model was validated by using the leverage approach and results which suggested potential large scale for further utilization of this model. The results of statistical values and validation tests demonstrated that our proposed norm index based model could be successfully applied for predicting the affinity 5-HT1A receptor ligands of arylpiperazine derivatives.

Application of chromatographic data in QSAR Studies of 3-[ω-(4-Arylpiperazin-1-yl)alkyl]pyrimido[5,4-c]quinolin-4(3H)-one derivatives as 5-HT1A receptor ligands

The activity of several 3-[ω-(4-arylpiperazin-1-yl)alkyl]pyrimido[5,4-c]quinolin-4(3H)-ones (LCAPs) with well-defined serotonin 1A (5-HT1A) receptor affinity was described by using chromatographic and calculated physicochemical parameters in quantitative structure-activity relationship analysis. Normal-phase thin-layer chromatography plates impregnated with solutions of L-aspartic acid, L-serine, L-phenylalanine, L-tryptophan, L-tyrosine, L-asparagine, L-threonine and their mixtures (denoted as S1-S11 biochromatographic models) were used with two mobile phases as a model of the interaction between LCAP and 5-HT1A receptors. Molecular descriptors for the investigated compounds were calculated by using HyperChem and ACD/Labs programs. The significant relationship explains that 82% of the variance was successfully validated by leave-one-out and leave-many-out tests. The results demonstrated that this model has significant predictive ability and can be used for the preliminary screening of newly synthesized potential 5-HT1A receptor ligands.

Interactions of N-{[2-(4-phenyl-piperazin-1-yl)-ethyl]-phenyl}-2-aryl-2-yl-acetamides and 1-{[2-(4-phenyl-piperazin-1-yl)-ethyl]-phenyl}-3-aryl-2-yl-ureas with dopamine D2 and 5-hydroxytryptamine 5HT(1A) receptors

It is suggested that the ratio of dopamine D(2) to 5-hydroxytryptamine 5-HT(1A) activity is an important parameter that determines the efficiency of antipsychotic drugs. Here we present the synthesis of N-{[2-(4-phenyl-piperazin-1-yl)-ethyl]-phenyl}-2-aryl-2-yl-acetamides and 1-{[2-(4-phenyl-piperazin-1-yl)-ethyl]-phenyl}-3-aryl-2-yl-ureas and their structure-activity relationship studies on dopamine D(2) and 5-hydrohytryptamine 5-HT(1A) receptors. It was shown that ligand selectivity and affinity strongly depends on their topology and the presence of a pyridyl group in the head of molecules. Molecular modeling studies using homology modeling and docking simulation revealed a rational explanation for the ligand behavior. The observed binding modes and receptor-ligand interactions provided us with a clue for optimizing the optimal selectivity towards 5-HT(1A) receptors.

Synthesis and pharmacological evaluation of carbamic acid 1-phenyl-3-(4-phenyl-piperazine-1-yl)-propyl ester derivatives as new analgesic agents

A series of carbamic acid 1-phenyl-3-(4-phenyl-piperazine-1-yl)-propyl ester derivatives were synthesized through discovery strategies for balancing target-based in vitro screening and phenotypic in vivo screening. All the newly synthesized compounds were screened for their analgesic activities and compared with standard drug morphine. Among them, compound 44r, a potent analgesic agent that has favorable pharmacokinetic properties in rats and most importantly, has a wide safety margin. We demonstrated with in vitro and in vivo functional assays that its analgesic activity might be through 5-HT(2A) antagonism to some extent. Hence, it is concluded that there is ample scope for further study in developing compound 44r as a good lead candidate for an analgesic agent.

Synthesis, docking studies and biological evaluation of benzo[b]thiophen-2-yl-3-(4-arylpiperazin-1-yl)-propan-1-one derivatives on 5-HT1A serotonin receptors

A series of novel benzo[b]thiophen-2-yl-3-(4-arylpiperazin-1-yl)-propan-1-one derivatives 6a-f, 7a-f and their corresponding alcohols 8a-f were synthesized and evaluated for their affinity towards 5-HT(1A) receptors. The influence of arylpiperazine moiety and benzo[b]thiophene ring substitutions on binding affinity was studied. The most promising analogue, 1-(benzo[b]thiophen-2-yl)-3-(4-(pyridin-2-yl)piperazin-1-yl)propan-1-one (7e) displayed micromolar affinity (K(i) = 2.30 μM) toward 5-HT(1A) sites. Docking studies shed light on the relevant electrostatic interactions which could explain the observed affinity for this compound.

Pharmacophore-based 3D QSAR studies on a series of high affinity 5-HT1A receptor ligands

5-HT(1A) receptor antagonists have been employed to treat depression, but the lack of structural information on this receptor hampers the design of specific and selective ligands. In this study, we have performed CoMFA studies on a training set of arylpiperazines (high affinity 5-HT(1A) receptor ligands) and to produce an effective alignment of the data set, a pharmacophore model was produced using Galahad. A statistically significant model was obtained, indicating a good internal consistency and predictive ability for untested compounds. The information gathered from our receptor-independent pharmacophore hypothesis is in good agreement with results from independent studies using different approaches. Therefore, this work provides important insights on the chemical and structural basis involved in the molecular recognition of these compounds.

The influence of dispersive interactions on the binding affinities of ligands with an arylpiperazine moiety to the dopamine D2 receptor

Several isosteric 1,3-dihydro-5-[2-(4-aryl-1-piperazinyl)ethyl]-2H-benzimidazole-2-thiones were used to investigate the interactions of different ligands with the binding site of the D2 receptor. Due to limitations of the simulation methods, docking analysis failed to show precisely the interactions that influence the binding affinity of the ligands. It is presumed that dispersive forces or more precisely edge-to-face interactions play an important role in the binding process, especially for the lipophilic part of the ligands. In order to confirm this hypothesis, ab initio calculations were applied on a model system in order to find the stabilization energies of potential edge-to-face interactions and then to correlate them with the ligand affinity. The obtained results indicate that there is a significant correlation between the strength of dispersive interactions and ligand affinity. It was shown that for the calculation of stabilization energies of modeled receptor-ligand complexes the Becke 'half-and-half' hybrid DFT method can be used, thus speeding up the usually long calculation time and reducing the required computer strength.

An efficient silane-promoted nickel-catalyzed amination of aryl and heteroaryl chlorides

A new silane-promoted nickel-catalyzed amination of aryl chlorides with 0.5 mol % of Ni(acac)2, 1 mol % of 3,5,6,8-tetrabromo-1,10-phenanthroline, and polymethylhydrosiloxane was developed. A broad range of aryl and heteroaryl chlorides can be coupled with secondary amines and anilines to give the desired (het)arylamines in good to excellent yields. The reaction is sensitive to the nature and amount of the silane promoter.

1-Cinnamyl-4-(2-methoxyphenyl)piperazines: Synthesis, Binding Properties, and Docking to Dopamine (D2) and Serotonin (5-HT1A) Receptors

Clinical properties of atypical antipsychotics are based on their interaction with D(2) dopamine receptor and serotonin 5-HT(1A) and 5-HT(2A) receptors. As a part of our research program on new antipsychotics, we synthesized various derivatives of 1-cinnamyl-4-(2-methoxyphenyl)piperazines, and evaluated their affinities for D(2), 5-HT(1A), 5-HT(2A), and adrenergic (alpha(1)) receptors using radioligand-binding assays. In addition, we performed docking analysis using models for the D(2) and 5-HT(1A) receptors. All compounds exhibited low to moderate affinity to 5-HT(1A) and 5-HT(2A) receptors, high affinity to the D(2 )receptor and large variability in affinities for the alpha(1) receptor. Docking analysis indicated that the binding to D(2) and 5-HT(1A) receptors is based on (i) interaction between protonated N1 of the piperazine ring and various aspartate residues, (ii) hydrogen bonds between various moieties of the ligand and the residues of threonine, serine, histidine or tryptophane, and (iii) edge-to-face interactions of the aromatic ring of the arylpiperazine moiety with phenylalanine or tyrosine residues. Docking data for the D(2) receptor can account for the binding properties obtained in binding assays, suggesting that the model is reliable and robust. However, docking data for the 5-HT(1A) receptor cannot account for actual binding properties, suggesting that further refinement of the model is required.

Influence of N-1 substituent properties on binding affinities of arylpiperazines to the binding site of 5-HT1A receptor

Serotonin receptors (5-HTRs), especially the 5-HT1A subtype, have been the subject of intensive research for the past decade, due to their function in human physiology. Several structurally different classes of ligands are known to bind to the 5-HT1A receptor, but arylpiperazine derivatives are among the most important ligands. In the work, docking analyses were used to explain the binding affinities of a series of ligands with different N-1 substituent. All ligands had in common the arylpiperazine structure, while the N-1 subsistent was modified to investigate the influence of ligand structure on its binding affinity. The shape and size, as well as the rigidity of the subsistents were altered to investigate the possible effects on the formation of the receptor - ligand complex.