Selectivity and activation of dopamine D3R from molecular dynamics

Exploring the structural basis and atomistic binding mechanistic of the selective antagonist blockade at D3 dopamine receptor over D2 dopamine receptor

More recently, there has been a paradigm shift toward selective drug targeting in the treatment of neurological disorders, including drug addiction, schizophrenia, and Parkinson's disease mediated by the different dopamine receptor subtypes. Antagonists with higher selectivity for D₃ dopamine receptor (D3DR) over D₂ dopamine receptor (D2DR) have been shown to attenuate drug-seeking behavior and associated side effects compared to non-subtype selective antagonists. However, high conservations among constituent residues of both proteins, particularly at the ligand-binding pockets, remain a challenge to therapeutic drug design. Recent studies have reported the discovery of two small-molecules R-VK4-40 and Y-QA31 which substantially inhibited D3DR with >180-fold selectivity over D2DR. Therefore, in this study, we seek to provide molecular and structural insights into these differential binding mechanistic using meta-analytic computational simulation methods. Findings revealed that R-VK4-40 and Y-QA31 adopted shallow binding modes and were more surface-exposed at D3DR while on the contrary, they exhibited deep hydrophobic pocket binding at D2DR. Also, two non-conserved residues; Tyr36^1.39 and Ser182^45.51 were identified in D3DR, based on their crucial roles and contributions to the selective binding of R-VK4-40 and Y-QA31. Importantly, both antagonists exhibited high affinities in complex with D3DR compared to D2DR, while van der Waals energies contributed majorly to their binding and stability. Structural analyses also revealed the distinct stabilizing effects of both compounds on D3DR secondary architecture relative to D2DR. Therefore, findings herein pinpointed the origin and mechanistic of selectivity of the compounds, which may assist in the rational design of potential small molecules of the D₂ -like dopamine family receptor subtype with improved potency and selectivity.

Ligand Pose Predictions for Human G Protein-Coupled Receptors: Insights from the Amber-Based Hybrid Molecular Mechanics/Coarse-Grained Approach

Human G protein-coupled receptors (hGPCRs) are the most frequent targets of Food and Drug Administration (FDA)-approved drugs. Structural bioinformatics, along with molecular simulation, can support structure-based drug design targeting hGPCRs. In this context, several years ago, we developed a hybrid molecular mechanics (MM)/coarse-grained (CG) approach to predict ligand poses in low-resolution hGPCR models. The approach was based on the GROMOS96 43A1 and PRODRG united-atom force fields for the MM part. Here, we present a new MM/CG implementation using, instead, the Amber 14SB and GAFF all-atom potentials for proteins and ligands, respectively. The new implementation outperforms the previous one, as shown by a variety of applications on models of hGPCR/ligand complexes at different resolutions, and it is also more user-friendly. Thus, it emerges as a useful tool to predict poses in low-resolution models and provides insights into ligand binding similarly to all-atom molecular dynamics, albeit at a lower computational cost.

Discovery of CNS-Like D3R-Selective Antagonists Using 3D Pharmacophore Guided Virtual Screening

The dopamine D3 receptor is an important CNS target for the treatment of a variety of neurological diseases. Selective dopamine D3 receptor antagonists modulate the improvement of psychostimulant addiction and relapse. In this study, five and six featured pharmacophore models of D3R antagonists were generated and evaluated with the post-hoc score combining two survival scores of active and inactive. Among the Top 10 models, APRRR215 and AHPRRR104 were chosen based on the coefficient of determination (APRRR215: R²training = 0.80; AHPRRR104: R²training = 0.82) and predictability (APRRR215: Q²test = 0.73, R²predictive = 0.82; AHPRRR104: Q²test = 0.86, R²predictive = 0.74) of their 3D-quantitative structure⁻activity relationship models. Pharmacophore-based virtual screening of a large compound library from eMolecules (>3 million compounds) using two optimal models expedited the search process by a 100-fold speed increase compared to the docking-based screening (HTVS scoring function in Glide) and identified a series of hit compounds having promising novel scaffolds. After the screening, docking scores, as an adjuvant predictor, were added to two fitness scores (from the pharmacophore models) and predicted Ki (from PLSs of the QSAR models) to improve accuracy. Final selection of the most promising hit compounds were also evaluated for CNS-like properties as well as expected D3R antagonism.

α2A- and α2C-Adrenoceptors as Potential Targets for Dopamine and Dopamine Receptor Ligands

The poor norepinephrine innervation and high density of Gi/o-coupled α_2A- and α_2C-adrenoceptors in the striatum and the dense striatal dopamine innervation have prompted the possibility that dopamine could be an effective adrenoceptor ligand. Nevertheless, the reported adrenoceptor agonistic properties of dopamine are still inconclusive. In this study, we analyzed the binding of norepinephrine, dopamine, and several compounds reported as selective dopamine D₂-like receptor ligands, such as the D₃ receptor agonist 7-OH-PIPAT and the D₄ receptor agonist RO-105824, to α₂-adrenoceptors in cortical and striatal tissue, which express α_2A-adrenoceptors and both α_2A- and α_2C-adrenoceptors, respectively. The affinity of dopamine for α₂-adrenoceptors was found to be similar to that for D₁-like and D₂-like receptors. Moreover, the exogenous dopamine receptor ligands also showed high affinity for α_2A- and α_2C-adrenoceptors. Their ability to activate Gi/o proteins through α_2A- and α_2C-adrenoceptors was also analyzed in transfected cells with bioluminescent resonance energy transfer techniques. The relative ligand potencies and efficacies were dependent on the Gi/o protein subtype. Furthermore, dopamine binding to α₂-adrenoceptors was functional, inducing changes in dynamic mass redistribution, adenylyl cyclase activity, and ERK1/2 phosphorylation. Binding events were further studied with computer modeling of ligand docking. Docking of dopamine at α_2A- and α_2C-adrenoceptors was nearly identical to its binding to the crystallized D₃ receptor. Therefore, we provide conclusive evidence that α_2A- and α_2C-adrenoceptors are functional receptors for norepinephrine, dopamine, and other previously assumed selective D₂-like receptor ligands, which calls for revisiting previous studies with those ligands.

Structural and Functional Effect of an Oscillating Electric Field on the Dopamine-D3 Receptor: A Molecular Dynamics Simulation Study

Dopamine as a neurotransmitter plays a critical role in the functioning of the central nervous system. The structure of D3 receptor as a member of class A G-protein coupled receptors (GPCRs) has been reported. We used MD simulation to investigate the effect of an oscillating electric field, with frequencies in the range 0.6–800 GHz applied along the z-direction, on the dopamine-D3R complex. The simulations showed that at some frequencies, the application of an external oscillating electric field along the z-direction has a considerable effect on the dopamine-D3R. However, there is no enough evidence for prediction of changes in specific frequency, implying that there is no order in changes. Computing the correlation coefficient parameter showed that increasing the field frequency can weaken the interaction between dopamine and D3R and may decrease the Arg128{3.50}-Glu324{6.30} distance. Because of high stability of α helices along the z-direction, applying an oscillating electric field in this direction with an amplitude 10-time higher did not have a considerable effect. However, applying the oscillating field at the frequency of 0.6 GHz along other directions, such as X-Y and Y-Z planes, could change the energy between the dopamine and the D3R, and the number of internal hydrogen bonds of the protein. This can be due to the effect of the direction of the electric field vis-à-vis the ligands orientation and the interaction of the oscillating electric field with the dipole moment of the protein.

Chemogenomics knowledgebase and systems pharmacology for hallucinogen target identification-Salvinorin A as a case study

Drug abuse is a serious problem worldwide. Recently, hallucinogens have been reported as a potential preventative and auxiliary therapy for substance abuse. However, the use of hallucinogens as a drug abuse treatment has potential risks, as the fundamental mechanisms of hallucinogens are not clear. So far, no scientific database is available for the mechanism research of hallucinogens. We constructed a hallucinogen-specific chemogenomics database by collecting chemicals, protein targets and pathways closely related to hallucinogens. This information, together with our established computational chemogenomics tools, such as TargetHunter and HTDocking, provided a one-step solution for the mechanism study of hallucinogens. We chose salvinorin A, a potent hallucinogen extracted from the plant Salvia divinorum, as an example to demonstrate the usability of our platform. With the help of HTDocking program, we predicted four novel targets for salvinorin A, including muscarinic acetylcholine receptor 2, cannabinoid receptor 1, cannabinoid receptor 2 and dopamine receptor 2. We looked into the interactions between salvinorin A and the predicted targets. The binding modes, pose and docking scores indicate that salvinorin A may interact with some of these predicted targets. Overall, our database enriched the information of systems pharmacological analysis, target identification and drug discovery for hallucinogens.

Two Binding Geometries for Risperidone in Dopamine D3 Receptors: Insights on the Fast-Off Mechanism through Docking, Quantum Biochemistry, and Molecular Dynamics Simulations

Risperidone is an atypical antipsychotic used in the treatment of schizophrenia and of symptoms of irritability associated with autism spectrum disorder (ASD). Its main action mechanism is the blockade of D2-like receptors acting over positive and negative symptoms of schizophrenia with small risk of extrapyramidal symptoms (EPS) at doses corresponding to low/moderate D2 occupancy. Such a decrease in the side effect incidence can be associated with its fast unbinding from D2 receptors in the nigrostriatal region allowing the recovery of dopamine signaling pathways. We performed docking essays using risperidone and the D3 receptor crystallographic data and results suggested two possible distinct orientations for risperidone at the binding pocket. Orientation 1 is more close to the opening of the binding site and has the 6-fluoro-1,2 benzoxazole fragment toward the bottom of the D3 receptor cleft, while orientation 2 is deeper inside the binding pocket with the same fragment toward to the receptor surface. In order to unveil the implications of these two binding orientations, classical molecular dynamics and quantum biochemistry computations within the density functional theory formalism and the molecular fractionation with conjugate caps framework were performed. Quantum mechanics/molecular mechanics suggests that orientation 2 (considering the contribution of Glu90) is slightly more energetically stable than orientation 1 with the main contribution coming from residue Asp110. The residue Glu90, positioned at the opening of the binding site, is closer to orientation 1 than 2, suggesting that it may have a key role in stability through attractive interaction with risperidone. Therefore, although orientations 1 and 2 are both likely to occur, we suggest that the occurrence of the first may contribute to the reduction of side effects in patients taking risperidone due to the reduction of dopamine receptor occupancy in the nigrostriatal region through a mechanism of fast dissociation. The atypical effect may be obtained simply by either delaying D3R full blockage by spatial hindrance of orientation 1 at the binding site or through an effective blockade followed by orientation 1 fast dissociation. While the molecular interpretation suggested in this work shed some light on the potential molecular mechanisms accounting for the reduced extrapyramidal symptoms observed during risperidone treatment, further studies are necessary in order to evaluate the implications of both orientations during the receptor activation/inhibition. Altogether these data highlight important hot spots in the dopamine receptor binding site bringing relevant information for the development of novel/derivative agents with atypical profile.

Difference and Influence of Inactive and Active States of Cannabinoid Receptor Subtype CB2: From Conformation to Drug Discovery

Cannabinoid receptor 2 (CB2), a G protein-coupled receptor (GPCR), is a promising target for the treatment of neuropathic pain, osteoporosis, immune system, cancer, and drug abuse. The lack of an experimental three-dimensional CB2 structure has hindered not only the development of studies of conformational differences between the inactive and active CB2 but also the rational discovery of novel functional compounds targeting CB2. In this work, we constructed models of both inactive and active CB2 by homology modeling. Then we conducted two comparative 100 ns molecular dynamics (MD) simulations on the two systems-the active CB2 bound with both the agonist and G protein and the inactive CB2 bound with inverse agonist-to analyze the conformational difference of CB2 proteins and the key residues involved in molecular recognition. Our results showed that the inactive CB2 and the inverse agonist remained stable during the MD simulation. However, during the MD simulations, we observed dynamical details about the breakdown of the "ionic lock" between R131(3.50) and D240(6.30) as well as the outward/inward movements of transmembrane domains of the active CB2 that bind with G proteins and agonist (TM5, TM6, and TM7). All of these results are congruent with the experimental data and recent reports. Moreover, our results indicate that W258(6.48) in TM6 and residues in TM4 (V164(4.56)-L169(4.61)) contribute greatly to the binding of the agonist on the basis of the binding energy decomposition, while residues S180-F183 in extracellular loop 2 (ECL2) may be of importance in recognition of the inverse agonist. Furthermore, pharmacophore modeling and virtual screening were carried out for the inactive and active CB2 models in parallel. Among all 10 hits, two compounds exhibited novel scaffolds and can be used as novel chemical probes for future studies of CB2. Importantly, our studies show that the hits obtained from the inactive CB2 model mainly act as inverse agonist(s) or neutral antagonist(s) at low concentration. Moreover, the hit from the active CB2 model also behaves as a neutral antagonist at low concentration. Our studies provide new insight leading to a better understanding of the structural and conformational differences between two states of CB2 and illuminate the effects of structure on virtual screening and drug design.

Structural signatures of DRD4 mutants revealed using molecular dynamics simulations: Implications for drug targeting

Human Dopamine Receptor D4 (DRD4) orchestrates several neurological functions and represents a target for many psychological disorders. Here, we examined two rare variants in DRD4; V194G and R237L, which elicit functional alterations leading to disruption of ligand binding and G protein coupling, respectively. Using atomistic molecular dynamics (MD) simulations, we provide in-depth analysis to reveal structural signatures of wild and mutant complexes with their bound agonist and antagonist ligands. We constructed intra-protein network graphs to discriminate the global conformational changes induced by mutations. The simulations also allowed us to elucidate the local side-chain dynamical variations in ligand-bound mutant receptors. The data suggest that the mutation in transmembrane V (V194G) drastically disrupts the organization of ligand binding site and causes disorder in the native helical arrangement. Interestingly, the R237L mutation leads to significant rewiring of side-chain contacts in the intracellular loop 3 (site of mutation) and also affects the distant transmembrane topology. Additionally, these mutations lead to compact ICL3 region compared to the wild type, indicating that the receptor would be inaccessible for G protein coupling. Our findings thus reveal unreported structural determinants of the mutated DRD4 receptor and provide a robust framework for design of effective novel drugs.

Computational Advances for the Development of Allosteric Modulators and Bitopic Ligands in G Protein-Coupled Receptors

Allosteric modulators of G protein-coupled receptors (GPCRs), which target at allosteric sites, have significant advantages against the corresponding orthosteric compounds including higher selectivity, improved chemical tractability or physicochemical properties, and reduced risk of receptor oversensitization. Bitopic ligands of GPCRs target both orthosteric and allosteric sites. Bitopic ligands can improve binding affinity, enhance subtype selectivity, stabilize receptors, and reduce side effects. Discovering allosteric modulators or bitopic ligands for GPCRs has become an emerging research area, in which the design of allosteric modulators is a key step in the detection of bitopic ligands. Radioligand binding and functional assays ([(35)S]GTPγS and ERK1/2 phosphorylation) are used to test the effects for potential modulators or bitopic ligands. High-throughput screening (HTS) in combination with disulfide trapping and fragment-based screening are used to aid the discovery of the allosteric modulators or bitopic ligands of GPCRs. When used alone, these methods are costly and can often result in too many potential drug targets, including false positives. Alternatively, low-cost and efficient computational approaches are useful in drug discovery of novel allosteric modulators and bitopic ligands to help refine the number of targets and reduce the false-positive rates. This review summarizes the state-of-the-art computational methods for the discovery of modulators and bitopic ligands. The challenges and opportunities for future drug discovery are also discussed.

Allosteric Binding Site and Activation Mechanism of Class C G-Protein Coupled Receptors: Metabotropic Glutamate Receptor Family

Metabotropic glutamate receptors (mGluR) are mainly expressed in the central nervous system (CNS) and contain eight receptor subtypes, named mGluR1 to mGluR8. The crystal structures of mGluR1 and mGluR5 that are bound with the negative allosteric modulator (NAM) were reported recently. These structures provide a basic model for all class C of G-protein coupled receptors (GPCRs) and may aid in the design of new allosteric modulators for the treatment of CNS disorders. However, these structures are only combined with NAMs in the previous reports. The conformations that are bound with positive allosteric modulator (PAM) or agonist of mGluR1/5 remain unknown. Moreover, the structural information of the other six mGluRs and the comparisons of the mGluRs family have not been explored in terms of their binding pockets, the binding modes of different compounds, and important binding residues. With these crystal structures as the starting point, we built 3D structural models for six mGluRs by using homology modeling and molecular dynamics (MD) simulations. We systematically compared their allosteric binding sites/pockets, the important residues, and the selective residues by using a series of comparable dockings with both the NAM and the PAM. Our results show that several residues played important roles for the receptors' selectivity. The observations of detailed interactions between compounds and their correspondent receptors are congruent with the specificity and potency of derivatives or compounds bioassayed in vitro. We then carried out 100 ns MD simulations of mGluR5 (residue 26-832, formed by Venus Flytrap domain, a so-called cysteine-rich domain, and 7 trans-membrane domains) bound with antagonist/NAM and with agonist/PAM. Our results show that both the NAM and the PAM seemed stable in class C GPCRs during the MD. However, the movements of "ionic lock," of trans-membrane domains, and of some activation-related residues in 7 trans-membrane domains of mGluR5 were congruent with the findings in class A GPCRs. Finally, we selected nine representative bound structures to perform 30 ns MD simulations for validating the stabilities of interactions, respectively. All these bound structures kept stable during the MD simulations, indicating that the binding poses in this present work are reasonable. We provided new insight into better understanding of the structural and functional roles of the mGluRs family and facilitated the future structure-based design of novel ligands of mGluRs family with therapeutic potential.

Antipsychotic haloperidol binding to the human dopamine D3 receptor: beyond docking through QM/MM refinement toward the design of improved schizophrenia medicines

As the dopamine D3R receptor is a promising target for schizophrenia treatment, an improved understanding of the binding of existing antipsychotics to this receptor is crucial for the development of new potent and more selective therapeutic agents. In this work, we have used X-ray cocrystallization data of the antagonist eticlopride bound to D3R as a template to predict, through docking essays, the placement of the typical antipsychotic drug haloperidol at the D3R receptor binding site. Afterward, classical and quantum mechanics/molecular mechanics (QM/MM) computations were employed to improve the quality of the docking calculations, with the QM part of the simulations being accomplished by using the density functional theory (DFT) formalism. After docking, the calculated QM improved total interaction energy EQMDI = -170.1 kcal/mol was larger (in absolute value) than that obtained with classical molecular mechanics improved (ECLDI = -156.3 kcal/mol) and crude docking (ECRDI = -137.6 kcal/mol) procedures. The QM/MM computations reveal the pivotal role of the Asp110 amino acid residue in the D3R haloperidol binding, followed by Tyr365, Phe345, Ile183, Phe346, Tyr373, and Cys114. Besides, it highlights the relevance of the haloperidol hydroxyl group axial orientation, which interacts with the Tyr365 and Thr369 residues, enhancing its binding to dopamine receptors. Finally, our computations indicate that functional substitutions in the 4-clorophenyl and in the 4-hydroxypiperidin-1-yl fragments (such as C3H and C12H hydrogen replacement by OH or COOH) can lead to haloperidol derivatives with distinct dopamine antagonism profiles. The results of our work are a first step using in silico quantum biochemical design as means to impact the discovery of new medicines to treat schizophrenia.