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-HT_1A, 5-HT_2A, 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.     

slate: A method for the superposition of flexible ligands

A novel program for the superposition of flexible molecules, slate, is presented. It uses simulated annealing to minimise the difference between the distance matrices calculated from the hydrogen-bonding and aromatic-ring properties of two ligands. A method for generating a molecular stack using multiple pairwise matches is illustrated. These stacks are used by the program doh to predict the relative positions of receptor atoms that could form hydrogen bonds to two or more ligands in the dataset. The methodology has been applied to ligands binding to dihydrofolate reductase, thermolysin, H₃ histamine receptors, ₂ adrenoceptors and 5-HT_1D receptors. When there are sufficient numbers and diversity of molecules in the dataset, the prediction of receptor-atom positions is applicable to compound design.     

A pharmacophore model for dopamine D4 receptor antagonists

A pharmacophore model for dopamine D₄ antagonists has been developed on the basis of a previously reported dopamine D₂ model. By using exhaustive conformational analyses (MM3^* force field and the GB/SA hydration model) and least-squares molecular superimposition studies, a set of eighteen structurally diverse high affinity D₄ antagonists have successfully been accommodated in the D₄ pharmacophore model. Enantioselectivities may be rationalized by conformational energies required for the enantiomers to adopt their proposed bioactive conformations. The pharmacophore models for antagonists at the D₄ and D₂ receptor subtypes have been compared in order to get insight into molecular properties of importance for D₂/D₄ receptor selectivity. It is concluded that the bioactive conformations of antagonists at the two receptor subtypes are essentially identical. Receptor essential volumes previously identified for the D₂ receptor are shown to be present also in the D₄ receptor. In addition, a novel receptor essential volume in the D₄ receptor, not present in the D₂ receptor, has been identified. This feature may be exploited for the design of D₄ selective antagonists. However, it is concluded that the major determinant for D₂/D₄ selectivity is the nature of the interactions between the receptor and aromatic ring systems. The effects of the electronic properties of these ring systems on the affinities for the two receptor subtypes differ substantially.     

3-D QSAR for intrinsic activity of 5-HT1A receptor ligands by the method of comparative molecular field analysis

The affinity of a ligand for a receptor is usually expressed in terms of the dissociation constant (K_i) of the drug-receptor complex, conveniently measured by the inhibition of radioligand binding. However, a ligand can be an antagonist, a partial agonist, or a full agonist, a property largely independent of its receptor affinity. This property can be quantitated as intrinsic activity (1A), which can range from 0 for a full antagonist to 1 for a full agonist. Although quantitative structure–activity relationship (QSAR) methods have been applied to the prediction of receptor affinity with considerable success, the prediction of IA, even qualitatively, has rarely been attempted. Because most traditional QSAR methods are limited to congeneric series, and there are often major structural differences between agonists and antagonists, this lack of success in predicting IA is understandable. To overcome this limitation, we used the method of comparative molecular field analysis (CoMFA), which, unlike traditional Hansch analysis, permits the inclusion of structurally dissimilar compounds in a single QSAR model. A structurally diverse set of 5-hydroxytryptamine_1A (5-HT_1A) receptor ligands, with literature IA data (determined by the inhibition of 5-HT sensitive forskolin-stimulated adenylate cyclase), was used to develop a 3-D QSAR model correlating intrinsic activity with molecular structure properties of 5HT_1A receptor ligands. This CoMFA model had a crossvalidated r² of 0.481, five components and final conventional r² of 0.943. The receptor model suggests that agonist and antagonist ligands can share parts of a common binding site on the receptor, with a primary agonist binding region that is also occupied by antagonists and a secondary binding site accommodating the excess bulk present in the sidechains of many antagonists and partial agonists. The CoMFA steric field graph clearly shows that agonists tend to be “flatter” (more coplanar) than antagonists, consistent with the difference between the 5-HT_1A agonist and antagonist pharmacophores proposed by Hibert and coworkers. The CoMFA electrostatic field graph suggests that, in the region surrounding the essential protonated aliphatic amino group, the positive molecular electrostatic potential may be weaker in antagonists as compared to agonists. Together, the steric and electrostatic maps suggest that in the secondary binding site region increased hydrophobic binding may enhance antagonist activity. These results demonstrate that CoMFA is capable of generating a statistically crossvalidated 3-D QSAR model that can successfully distinguish between agonist and antagonist 5-HT_1A ligands. To the best of our knowledge, this is the first time this or any other QSAR method has been successfully applied to the correlation of structure with IA rather than potency or affinity. The analysis has suggested various structural features associated with agonist and antagonist behaviors of 5-HT_1A ligands and thus should assist in the future design of drugs that act via 5-HT_1A receptors. © 1993 John Wiley & Sons, Inc.     

Multiconformational composite molecular potential fields in the analysis of drug action. I. Methodology and first evaluation using 5-HT and histamine action as examples

Summary The quality of molecular electrostatic maps generated by non-quantum mechanical methods has been improved using extended electron distributions. Further simplification has been achieved by distilling these maps down to their energy extrema. A new means of defining surface interaction has been added and the resulting composite map has been plotted for a limited number of low-lying conformers of a series of agonists and antagonists of the H₂ and H₃ receptors and 5-HT_1A and 5-HT_1D receptors. The results from the cross-comparison of these maps indicate their ability to distinguish the specific receptor. Interesting consequences of the method are that structural overlay is irrelevant, that several conformations may contribute to the overall binding pattern and that lesser pharmacological activities may be deduced from the results.     

Design and Synthesis of Arylpiperazine Serotonergic/Dopaminergic Ligands with Neuroprotective Properties

Long-chain arylpiperazine scaffold is a versatile template to design central nervous system (CNS) drugs that target serotonin and dopamine receptors. Here we describe the synthesis and biological evaluation of ten new arylpiperazine derivatives designed to obtain an affinity profile at serotonin 5-HT_1A, 5-HT_2A, 5-HT₇ receptor, and dopamine D₂ receptor of prospective drugs to treat the core symptoms of autism spectrum disorder (ASD) or psychosis. Besides the structural features required for affinity at the target receptors, the new compounds incorporated structural fragments with antioxidant properties to counteract oxidative stress connected with ASD and psychosis. All the new compounds showed CNS MultiParameter Optimization score predictive of desirable ADMET properties and cross the blood–brain barrier. We identified compound 12a that combines an affinity profile compatible with antipsychotic activity (5-HT_1A K_i = 41.5 nM, 5-HT_2A K_i = 315 nM, 5-HT₇ K_i = 42.5 nM, D₂ K_i = 300 nM), and compound 9b that has an affinity profile consistent with studies in the context of ASD (5-HT_1A K_i = 23.9 nM, 5-HT_2A K_i = 39.4 nM, 5-HT₇ K_i = 45.0 nM). Both compounds also had antioxidant properties. All compounds showed low in vitro metabolic stability, the only exception being compound 9b, which might be suitable for studies in vivo.     

The Role of Lipids in Allosteric Modulation of Dopamine D2 Receptor—In Silico Study

The dopamine D₂ receptor, belonging to the class A G protein-coupled receptors (GPCRs), is an important drug target for several diseases, including schizophrenia and Parkinson’s disease. The D₂ receptor can be activated by the natural neurotransmitter dopamine or by synthetic ligands, which in both cases leads to the receptor coupling with a G protein. In addition to receptor modulation by orthosteric or allosteric ligands, it has been shown that lipids may affect the behaviour of membrane proteins. We constructed a model of a D₂ receptor with a long intracellular loop (ICL3) coupled with G_iα1 or G_iα2 proteins, embedded in a complex asymmetric membrane, and simulated it in complex with positive, negative or neutral allosteric ligands. In this study, we focused on the influence of ligand binding and G protein coupling on the membrane–receptor interactions. We show that there is a noticeable interplay between the cell membrane, G proteins, D₂ receptor and its modulators.     

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 K_I = 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.     

Time-efficient flexible superposition of medium-sized molecules

We present an efficient algorithm for the structural alignment of medium-sized organic molecules. The algorithm has been developed for applications in 3D QSAR and in receptor modeling. The method assumes one of the molecules, the reference ligand, to be presented in the conformation that it adopts inside the receptor pocket. The second molecule, the test ligand, is considered to be flexible, and is assumed to be given in an arbitrary low-energy conformation. Ligand flexibility is modeled by decomposing the test ligand into molecular fragments, such that ring systems are completely contained in a single fragment. Conformations of fragments and torsional angles of single bonds are taken from a small finite set, which depends on the fragment and bond, respectively. The algorithm superimposes a distinguished base fragment of the test ligand onto a suitable region of the reference ligand and then attaches the remaining fragments of the test ligand in a step-by-step fashion. During this process, a scoring function is optimized that encompasses bonding terms and terms accounting for steric overlap as well as for similarity of chemical properties of both ligands. The algorithm has been implemented in the FLEXS system. To validate the quality of the produced results, we have selected a number of examples for which the mutual superposition of two ligands is experimentally given by the comparison of the binding geometries known from the crystal structures of their corresponding protein–ligand complexes. On more than two-thirds of the test examples the algorithm produces rms deviations of the predicted versus the observed conformation of the test ligand below 1.5 Å. The run time of the algorithm on a single problem instance is a few minutes on a common-day workstation. The overall goal of this research is to drastically reduce run times, while limiting the inaccuracies of the model and the computation to a tolerable level.     

Flexible ligand docking using a genetic algorithm

Summary Two computational techniques have been developed to explore the orientational and conformational space of a flexible ligand within an enzyme. Both methods use the Genetic Algorithm (GA) to generate conformationally flexible ligands in conjunction with algorithms from the DOCK suite of programs to characterize the receptor site. The methods are applied to three enzyme-ligand complexes: dihydrofolate reductase-methotrexate, thymidylate synthase-phenolpthalein and HIV protease-thioketal haloperidol. Conformations and orientations close to the crystallographically determined structures are obtained, as well as alternative structures with low energy. The potential for the GA method to screen a database of compounds is also examined. A collection of ligands is evaluated simultaneously, rather than docking the ligands individually into the enzyme.Abbreviations GA genetic algorithm; dhfr, dihydrofolate reductase - mtx methotrexate - ts thymidylate synthase - fen phenolphalein - HIV human immune deficiency virus - hivp HIV protease - thk thioketal haloperidol     

Molecular docking,dynamics simulations and 3D-QSAR modeling of arylpiperazine derivatives of 3,5-dioxo-(2H,4H)-1,2,4-triazine as 5-HT1AR agonists

Serotonin receptor, 5-HT_1AR, agonists and partial agonists have established drug candidates for psychiatric and neurologic disorders. Recently, we reported the synthesis and evaluation of arylpiperazine derivatives of 3,5-dioxo-(2H,4H)-1,2,4-triazine as 5-HT_1AR ligands. Herein, we generated a homology model of the receptor and docked the ligands against it, predicted the stability of the receptor model and complexes by molecular dynamics and generated a 3D-QSAR model for the arylpiperazine derivatives of 3,5-dioxo-(2H,4H)-1,2,4-triazine. The model suggests the hydrophobic part that arises from the aromatic region and the electron withdrawing parts play a vital role in the agonist activity of the lead molecules.     

A computational model of the 5-HT3 receptor extracellular domain: search for ligand binding sites

A three-dimensional model of the 5-HT₃ receptor extarcellular domain has been derived on the basis of the nicotinic acetylcholine receptor model recently published by Tsigelny et al. Maximum complementarity between the position and characteristics of mutated residues putatively involved in ligand interaction and the pharmacophoric elements derived by the indirect approach applied on several series of 5-HT₃ ligands have been exploited to gain insights into the ligand binding modalities and to speculate on the mechanistic role of the structural components. The analysis of the three-dimensional model allows one to distinguish among amino acids that exert key roles in ligand interactions, subunit architecture, receptor assembly and receptor dynamics. For some of these, alternative roles with respect to the ones hypothesized by experimentalists are assigned. Different binding modalities for agonists and antagonists are highlighted, and residues which probably play a role in the transduction of binding into a change in conformational state of the receptor are suggested. Received: 27 July 2000 / Accepted: 15 September 2000 / Published online: 21 December 2000     

Comparative receptor mapping of serotoninergic 5-HT3 and 5-HT4 binding sites*

The clinical use of currently available drugs acting at the5-HT₄ receptor has been hampered by their lack of selectivityover 5-HT₃ binding sites. For this reason, there is considerableinterest in the medicinal chemistry of these serotonin receptor subtypes, andsignificant effort has been made towards the discovery of potent and selectiveligands. Computer-aided conformational analysis was used to characterizeserotoninergic 5-HT₃ and 5-HT₄ receptorrecognition. On the basis of the generally accepted model of the5-HT₃ antagonist pharmacophore, we have performed a receptormapping of this receptor binding site, following the active analog approach(AAA) defined by Marshall. The receptor excluded volume was calculated as theunion of the van der Waals density maps of nine active ligands(pK_i 8.9), superimposed in pharmacophoric conformations.Six inactive analogs (pK_i < 7.0) were subsequently used todefine the essential volume, which in its turn can be used to define theregions of steric intolerance of the 5-HT₃ receptor. Five activeligands (pK_i 9.3) at 5-HT₄ receptors wereused to construct an antagonist pharmacophore for this receptor, and todetermine its excluded volume by superimposition of pharmacophoricconformations. The volume defined by the superimposition of five inactive5-HT₄ receptor analogs that possess the pharmacophoric elements(pK_i 6.6) did not exceed the excluded volume calculated forthis receptor. In this case, the inactivity may be due to the lack of positiveinteraction of the amino moiety with a hypothetical hydrophobic pocket, whichwould interact with the voluminous substituents of the basic nitrogen ofactive ligands. The difference between the excluded volumes of both receptorshas confirmed that the main difference is indeed in the basic moiety. Thus,the 5-HT₃ receptor can only accommodate small substituents inthe position of the nitrogen atom, whereas the 5-HT₄ receptorrequires more voluminous groups. Also, the basic nitrogen is located at ca.8.0 Å from the aromatic moiety in the 5-HT₄ antagonistpharmacophore, whereas this distance is ca. 7.5 Å in the5-HT₃ antagonist model. The comparative mapping of bothserotoninergic receptors has allowed us to confirm the three-componentpharmacophore accepted for the 5-HT₃ receptor, as well as topropose a steric model for the 5-HT₄ receptor binding site. Thisstudy offers structural insights to aid the design of new selective ligands,and the resulting models have received some support from the synthesis of twonew active and selective ligands: 24 (K_i(5-HT₃)= 3.7 nM; K_i(5-HT₄) > 1000 nM) and 25(K_i(5-HT₄) = 13.7 nM;K_i(5-HT₃) > 10 000 nM).     

Molecular Structure and Affinity to 5-HT1A Receptor of Chlorophenyl(Piperazinylalkyl)Phthalimides

Abstract

X-ray crystallography, quantum-chemical calculations and conformational analysis have been employed to study chlorophenyl(piperazinylalkyl)phthalimides, potential ligands of 5-HT_1A receptor. The molecular recognition of investigated compounds by 5-HT_1Aserotonin receptor has been estimated according to their ability to inhibit the [³H8]-DPAT binding. The model for 5-HT_1A pharmacophore has been proposed based on crystal structures of N-(aryl)piperazinyl — alkylphthalimides.     

Docking flexible molecules: A case study of three proteins

A genetic algorithm (GA) conformation search method is used to dock a series of flexible molecules into one of three proteins. The proteins examined are thermolysin (tmn), carboxypeptidase A (cpa), and dihydrofolate reductase (dfr). In the latter two proteins, the crystal ligand was redocked. For thermolysin, we docked eight ligands into a protein conformation derived from a single crystal structure. The bound conformations of the other ligands in tmn are known. In the cpa and dfr cases, and in seven of the eight tmn ligands, the GA docking method found conformations within 1.6 Å root mean square (rms) of the relaxed crystal conformation. © 1995 John Wiley & Sons, Inc.     

3D-QSAR using `Multiconformer' alignment: The use of HASL in the analysis of 5-HT1A thienopyrimidinone ligands†

The observed 5-HT_1A and ₁-adrenergic receptor (₁-AR) receptor binding properties of a series of 23 thienopyrimidinones were used to develop HASL 3D-QSAR models. A single, low energy conformer of the most active analogue in the series, which was consistent with NMR structural studies, was chosen as a template molecule. Alignments of all the molecules to the template were provided by an Amber/MM2 superposition force field. In this manner, each molecule was represented by five separate low energy conformers which were subsequently used in the generation of HASL 3D-QSAR models. Models derived from multiple conformers were found to exhibit enhanced predictivity compared to models based on single, low energy conformers. In addition, the use of contour imaging of HASL multi-conformer model interactions was found to lead to a more consistent interpretation of those molecular features most significant for 5-HT_1A receptor binding.     

Determining molecular structures and conformations directly from electron diffraction using a genetic algorithm.

A global optimization strategy, based upon application of a genetic algorithm (GA), is demonstrated as an approach for determining the structures of molecules possessing significant conformational flexibility directly from gas-phase electron diffraction data. In contrast to the common approach to molecular structure determination, based on trial-and-error assessment of structures available from quantum chemical calculations, the GA approach described here does not require expensive quantum mechanical calculations or manual searching of the potential energy surface of the sample molecule, relying instead upon simple comparison between the experimental and calculated diffraction pattern derived from a proposed trial molecular structure. Structures as complex as all-trans retinal and p-coumaric acid, both important chromophores in photosensing processes, may be determined by this approach. In the examples presented here, we find that the GA approach can determine the correct conformation of a flexible molecule described by 11 independent torsion angles. We also demonstrate applications to samples comprising a mixture of two distinct molecular conformations. With these results we conclude that applications of this approach are very promising in elucidating the structures of large molecules directly from electron diffraction data.     

Design,Sustainable Synthesis and Biological Evaluation of a Novel Dual α2A/5-HT7 Receptor Antagonist with Antidepressant-Like Properties

The complex pathophysiology of depression, together with the limits of currently available antidepressants, has resulted in the continuous quest for alternative therapeutic strategies. Numerous findings suggest that pharmacological blockade of α₂-adrenoceptor might be beneficial for the treatment of depressive symptoms by increasing both norepinephrine and serotonin levels in certain brain areas. Moreover, the antidepressant properties of 5-HT₇ receptor antagonists have been widely demonstrated in a large set of animal models. Considering the potential therapeutic advantages in targeting both α₂-adrenoceptors and 5-HT₇ receptors, we designed a small series of arylsulfonamide derivatives of (dihydrobenzofuranoxy)ethyl piperidines as dually active ligands. Following green chemistry principles, the designed compounds were synthesized entirely using a sustainable mechanochemical approach. The identified compound 8 behaved as a potent α_2A/5-HT₇ receptor antagonist and displayed moderate-to-high selectivity over α₁-adrenoceptor subtypes and selected serotonin and dopaminergic receptors. Finally, compound 8 improved performance of mice in the forced swim test, displaying similar potency to the reference drug mirtazapine.     

Flexible docking of ligands into synthetic receptors using a two-sided incremental construction algorithm

We present a new algorithm for the fast and reliable structure prediction of synthetic receptor-ligand complexes. Our method is based on the protein-ligand docking program FlexX and extends our recently introduced docking technique for synthetic receptors, which has been implemented in the program FlexR. To handle the flexibility of the relevant molecules, we apply a novel docking strategy that uses an adaptive two-sided incremental construction algorithm which incorporates the structural flexibility of both the ligand and synthetic receptor. We follow an adaptive strategy, in which one molecule is expanded by attaching its next fragment in all possible torsion angles, whereas the other (partially assembled) molecule serves as a rigid binding partner. Then the roles of the molecules are exchanged. Geometric filters are used to discard partial conformations that cannot realize a targeted interaction pattern derived in a graph-based precomputation phase. The process is repeated until the entire complex is built up. Our algorithm produces promising results on a test data set comprising 10 complexes of synthetic receptors and ligands. The method generated near-native solutions compared to crystal structures in all but one case. It is able to generate solutions within a couple of minutes and has the potential of being used as a virtual screening tool for searching for suitable guest molecules for a given synthetic receptor in large databases of guests and vice versa.