The D3 dopamine receptor
is a therapeutic target for treating various nervous system disorders
such as schizophrenia, Parkinson’s disease, depression, and
addictive behaviors. The crystal structure of the D3 receptor bound
to an antagonist was recently described; however,
the structural features that contribute to agonist-induced conformational
changes and signaling properties are not well understood. We have
previously described the conformation-dependent tolerance and slow
response termination (SRT) signaling properties of the D3 receptor
and identified the C147 residue in the second intracellular loop (IL2)
of the D3 receptor as important for the tolerance property. Interestingly,
while IL2 and the C147 residue, in particular, were important for
dopamine- and quinpirole-induced tolerance, this residue did not affect
the severe tolerance induced by the high affinity, D3 receptor-selective
agonist, PD128907. Here, we used D2/D3 receptor chimeras and site-specific
D3 receptor mutants to identify another residue, D187, in the second
extracellular loop (EC2) of the human D3 receptor that mediates the
tolerance property induced by PD128907, quinpirole, pramipexole, and
dopamine. Molecular dynamics simulations confirmed the distinct conformation
adopted by D3 receptor during tolerance and suggested that in the
tolerant D3 receptor the D187 residue in EC2 forms a salt bridge with
the H354 residue in EC3. Indeed, site-directed mutation of the H354
residue resulted in loss of PD1287907-induced tolerance. The mapping
of specific amino acid residues that contribute to agonist-dependent
conformation changes and D3 receptor signaling properties refines
the agonist-bound D3 receptor pharmacophore model which will help
develop novel D3 receptor agonists.
Structure−function; signal transduction; desensitization; functional
selectivity; D3 receptor conformation; potassium
The Plasmodium falciparum and P. berghei genomes each contain three dipeptidyl aminopeptidase (dpap) homologs. dpap1 and -3 are critical for asexual growth, but the role of dpap2, the gametocyte-specific homolog, has not been tested. If DPAPs are essential for transmission as well as asexual growth, then a DPAP inhibitor could be used for treatment and to block transmission. To directly analyze the role of DPAP2, a dpap2-minus P. berghei (Pbdpap2Δ) line was generated. The Pbdpap2Δ parasites grew normally, differentiated into gametocytes, and generated sporozoites that were infectious to mice when fed to a mosquito. However, Pbdpap1 transcription was >2-fold upregulated in the Pbdpap2Δ clonal lines, possibly compensating for the loss of Pbdpap2. The role of DPAP1 and -3 in the dpap2Δ parasites was then evaluated using a DPAP inhibitor, ML4118S. When ML4118S was added to the Pbdpap2Δ parasites just before a mosquito membrane feed, mosquito infectivity was not affected. To assess longer exposures to ML4118S and further evaluate the role of DPAPs during gametocyte development in a parasite that causes human malaria, the dpap2 deletion was repeated in P. falciparum. Viable P. falciparum dpap2 (Pfdpap2)-minus parasites were obtained that produced morphologically normal gametocytes. Both wild-type and Pfdpap2-negative parasites were sensitive to ML4118S, indicating that, unlike many antimalarials, ML4118S has activity against parasites at both the asexual and sexual stages and that DPAP1 and -3 may be targets for a dual-stage drug that can treat patients and block malaria transmission.
The HIV-1 capsid (CA) protein plays essential roles in both early and late stages of virl replication and has emerged as a novel drug target. We report hybrid structure-based virtual screening to identify small molecules with the potential to interact with the N-terminal domain (NTD) of HIV-1 CA and disrupt early, preintegration steps of the HIV-1 replication cycle. The small molecule 4,4′-[dibenzo[b,d]furan-2,8-diylbis(5-phenyl-1H-imidazole-4,2-diyl)]dibenzoic acid (CK026), which had anti-HIV-1 activity in single- and multiple-round infections but failed to inhibit viral replication in peripheral blood mononuclear cells (PBMCs), was identified. Three analogues of CK026 with reduced size and better drug-like properties were synthesized and assessed. Compound I-XW-053 (4-(4,5-diphenyl-1H-imidazol-2-yl)benzoic acid) retained all of the antiviral activity of the parental compound and inhibited the replication of a diverse panel of primary HIV-1 isolates in PBMCs, while displaying no appreciable cytotoxicity. This antiviral activity was specific to HIV-1, as I-XW-053 displayed no effect on the replication of SIV or against a panel of nonretroviruses. Direct interaction of I-XW-053 was quantified with wild-type and mutant CA protein using surface plasmon resonance and isothermal titration calorimetry. Mutation of Ile37 and Arg173, which are required for interaction with compound I-XW-053, crippled the virus at an early, preintegration step. Using quantitative PCR, we demonstrated that treatment with I-XW-053 inhibited HIV-1 reverse transcription in multiple cell types, indirectly pointing to dysfunction in the uncoating process. In summary, we have identified a CA-specific compound that targets and inhibits a novel region in the NTD-NTD interface, affects uncoating, and possesses broad-spectrum anti-HIV-1 activity.
The human immunodeficiency virus type 1 (HIV-1) promoter or long-terminal repeat (LTR) regulates viral gene expression by interacting with multiple viral and host factors. The viral transactivator protein Tat plays an important role in transcriptional activation of HIV-1 gene expression. Functional domains of Tat and its interaction with transactivation response element RNA and cellular transcription factors have been examined. Genetic variation within tat of different HIV-1 subtypes has been shown to affect the interaction of the viral transactivator with cellular and/or viral proteins, influencing the overall level of transcriptional activation as well as its action as a neurotoxic protein. Consequently, the genetic variability within tat may impact the molecular architecture of functional domains of the Tat protein that may impact HIV pathogenesis and disease. Tat as a therapeutic target for anti-HIV drugs has also been discussed.
Pregnane X Receptor (PXR), a master regulator of drug metabolism and inflammation, is abundantly expressed in the gastrointestinal tract. Baicalein and its O-glucuronide baicalin are potent anti-inflammatory and anti-cancer herbal flavonoids that undergo a complex cycle of interconversion in the liver and gut. We sought to investigate the role these flavonoids play in inhibiting gut inflammation by an axis involving PXR and other potential factors. The consequences of PXR regulation and activation by the herbal flavonoids, baicalein and baicalin were evaluated in vitro in human colon carcinoma cells and in vivo using wild-type, Pxr-null, and humanized (hPXR) PXR mice. Baicalein, but not its glucuronidated metabolite baicalin, activates PXR in a Cdx2-dependent manner in vitro, in human colon carcinoma LS174T cells, and in the murine colon in vivo. While both flavonoids abrogate dextran sodium sulfate (DSS)-mediated colon inflammation in vivo, oral delivery of a potent bacterial β-glucuronidase inhibitor eliminates baicalin’s effect on gastrointestinal inflammation by preventing the microbial conversion of baicalin to baicalien. Finally, reduction of gastrointestinal inflammation requires the binding of Cdx2 to a specific proximal site on the PXR promoter. Pharmacological targeting of intestinal PXR using natural metabolically labile ligands could serve as effective and potent therapeutics for gut inflammation that avert systemic drug interactions.
The dopamine D3 receptor has been implicated as a potential target for drug development in various complex psychiatric disorders including psychosis, drug dependence, and Parkinson’s disease. In our overall goal to develop molecules with preferential affinity at D3 receptors, we undertook a hybrid drug development approach by combining a known dopamine agonist moiety with a substituted piperazine fragment. In the present study, three compounds produced this way with preferential D3 agonist activity, were tested at D3 receptors with mutations in the agonist binding pocket of three residues known to be important for agonist binding activity. At S192A and T369V, the hybrid agonist compounds produced an interaction profile in [3H]spiperone binding assays similar to that of the parent 5-OH-DPAT and 7-OH-DPAT molecules. The loss of affinity at the S192A mutant was most prominent for 5-OH-DPAT and its corresponding hybrid compound D-237. D110N did not show any radioligand binding. Homology modeling indicated that 7-OH-DPAT-derived D-315 uniquely shares H-bonding with Tyr365 which produced favorable interaction and no loss of H-bonding in the S192A mutant, suggesting that agonist activity may not be solely controlled by residues in the binding pocket.
Dopamine D3 receptor; Parkinson’s disease; hybrid dopamine agonists; 7-OH-DPAT; 5-OH-DPAT; homology modeling
Malaria is endemic in most developing countries, with nearly 500 million cases estimated to occur each year. The need to design a new generation of antimalarial drugs that can combat the most drug-resistant forms of the malarial parasite is well recognized. In this study, we wanted to develop inhibitors of key proteins that form the invasion machinery of the malarial parasite. A critical feature of host-cell invasion by apicomplexan parasites is the interaction between the carboxy terminal tail of myosin A (MyoA) and the myosin tail interacting protein (MTIP). Using the co-crystal structure of the Plasmodium knowlesi MTIP and the MyoA tail peptide as input to the hybrid structure-based virtual screening approach, we identified a series of small molecules as having the potential to inhibit MTIP-MyoA interactions. Of the initial fifteen compounds tested, a pyrazole-urea compound inhibited P. falciparum growth with an EC50 value of 145 nM. We screened an additional 51 compounds belonging to the same chemical class and identified eight compounds with EC50 values less than 400 nM. Interestingly, the compounds appeared to act at several stages of the parasite’s life cycle to block growth and development. The pyrazole-urea compounds identified in this study could be effective antimalarial agents because they competitively inhibit a key protein-protein interaction between MTIP and MyoA responsible for the gliding motility and invasive features of the malarial parasite.
Antimalarials; gliding motility; hybrid structure based method; myosin A; myosin tail interacting protein; plasmodium falciparum; pyrazole urea; virtual screening
Consistent asymmetry of the left-right (LR) axis is a crucial aspect of vertebrate embryogenesis. Asymmetric gene expression of the TGFβ superfamily member Nodal related 1 (Nr1) in the left lateral mesoderm plate is a highly conserved step regulating the situs of the heart and viscera. In Xenopus, movement of maternal serotonin (5HT) through gap-junctional paths at cleavage stages dictates asymmetry upstream of Nr1. However, the mechanisms linking earlier biophysical asymmetries with this transcriptional control point are not known.
To understand how an early physiological gradient is transduced into a late, stable pattern of Nr1 expression we investigated epigenetic regulation during LR patterning. Embryos injected with mRNA encoding a dominant-negative of Histone Deacetylase (HDAC) lacked Nr1 expression and exhibited randomized sidedness of the heart and viscera (heterotaxia) at stage 45. Timing analysis using pharmacological blockade of HDACs implicated cleavage stages as the active period. Inhibition during these early stages was correlated with an absence of Nr1 expression at stage 21, high levels of heterotaxia at stage 45, and the deposition of the epigenetic marker H3K4me2 on the Nr1 gene. To link the epigenetic machinery to the 5HT signaling pathway, we performed a high-throughput proteomic screen for novel cytoplasmic 5HT partners associated with the epigenetic machinery. The data identified the known HDAC partner protein Mad3 as a 5HT-binding regulator. While Mad3 overexpression led to an absence of Nr1 transcription and randomized the LR axis, a mutant form of Mad3 lacking 5HT binding sites was not able to induce heterotaxia, showing that Mad3's biological activity is dependent on 5HT binding.
HDAC activity is a new LR determinant controlling the epigenetic state of Nr1 from early developmental stages. The HDAC binding partner Mad3 may be a new serotonin-dependent regulator of asymmetry linking early physiological asymmetries to stable changes in gene expression during organogenesis.
Xenopus; left-right asymmetry; laterality; Nodal; HDAC
The pregnane X receptor (PXR) is a key transcriptional regulator of many genes [e.g., cytochrome P450s (CYP2C9, CYP3A4, CYP2B6), MDR1] involved in xenobiotic metabolism and excretion.
As part of an evaluation of different approaches to predict compound affinity for nuclear hormone receptors, we used the molecular docking program GOLD and a hybrid scoring scheme based on similarity weighted GoldScores to predict potential PXR agonists in the ToxCast database of pesticides and other industrial chemicals. We present some of the limitations of different in vitro systems, as well as docking and ligand-based computational models.
Each ToxCast compound was docked into the five published crystallographic structures of human PXR (hPXR), and 15 compounds were selected based on their consensus docking scores for testing. In addition, we used a Bayesian model to classify the ToxCast compounds into PXR agonists and nonagonists. hPXR activation was determined by luciferase-based reporter assays in the HepG2 and DPX-2 human liver cell lines.
We tested 11 compounds, of which 6 were strong agonists and 2 had weak agonist activity. Docking results of additional compounds were compared with data reported in the literature. The prediction sensitivity of PXR agonists in our sample ToxCast data set (n = 28) using docking and the GoldScore was higher than with the hybrid score at 66.7%. The prediction sensitivity for PXR agonists using GoldScore for the entire ToxCast data set (n = 308) compared with data from the NIH (National Institutes of Health) Chemical Genomics Center data was 73.8%.
Docking and the GoldScore may be useful for prioritizing large data sets prior to in vitro testing with good sensitivity across the sample and entire ToxCast data set for hPXR agonists.
Bayesian model; docking; GoldScore; hybrid scoring; PXR; ToxCast
This study examined how the quaternary organic ammonium ion, benzyltriethylamine (BTEA), binds to the Na,K-ATPase to produce membrane potential (VM)-dependent inhibition and tested the prediction that such a VM-dependent inhibitor would display electrogenic binding kinetics. BTEA competitively inhibited K+ activation of Na,K-ATPase activity and steady-state 86Rb+ occlusion. The initial rate of 86Rb+ occlusion was decreased by BTEA to a similar degree whether it was added to the enzyme prior to or simultaneously with Rb+, a demonstration that BTEA inhibits the Na,K-ATPase without being occluded. Several BTEA structural analogues reversibly inhibited Na,K-pump current, but none blocked current in a VM-dependent manner except BTEA and its para-nitro derivative, pNBTEA. Under conditions that promoted electroneutral K+-K+ exchange by the Na,K-ATPase, step changes in VM elicited pNBTEA-activated ouabain-sensitive transient currents that had similarities to those produced with the K+ congener, Tl+. pNBTEA- and Tl+-dependent transient currents both displayed saturation of charge moved at extreme negative and positive VM, equivalence of charge moved during and after step changes in VM, and similar apparent valence. The rate constant (ktot) for Tl+-dependent transient current asymptotically approached a minimum value at positive VM. In contrast, ktot for pNBTEA-dependent transient current was a “U”-shaped function of VM with a minimum value near 0 mV. Homology models of the Na,K-ATPase alpha subunit suggested that quaternary amines can bind to two extracellularly-accessible sites, one of them located at K+ binding sites positioned between transmembrane helices 4, 5, and 6. Altogether, these data revealed important information about electrogenic ion binding reactions of the Na,K-ATPase that are not directly measurable during ion transport by this enzyme.
Oxidized low density lipoprotein (oxLDL) uptake by macrophages is mediated by scavenger receptors and leads to unregulated cholesterol accumulation. Micellar nanolipoblockers (NLBs) consist of alkyl chains and polyethylene glycol on mucic acid. NLBs functionalized with anionic groups inhibit oxLDL uptake via the scavenger receptor A (SR-A). Molecular modeling and docking approaches were used to understand the structure-activity relationship (SAR) between NLBs and SR-A. Six NLB models were docked to the SR-A homology model to investigate charge placement and clustering. NLB models with the most favorable binding energy were also the most effective oxLDL inhibitors in THP-1 macrophages. Mutant SR-A models were generated by replacing charged residues with alanine. All charged residues in the region were necessary, with Lys60, Lys63 and Lys66 having the greatest effect on binding. We hypothesize that structural studies aided by theoretical modeling and docking can be used to design promising NLB candidates with optimal binding properties.
Atherosclerosis; low density lipoproteins; nanolipoblocker; scavenger receptor model; docking and scoring
Shape is a fundamentally important molecular feature that often determines the fate of a compound in terms of molecular interactions with preferred and non-preferred biological targets. Complementarity of binding in small molecule-protein, peptide-receptor, antigen-antibody and protein-protein interactions is key to life and survival, but also to targeting molecules with bioactivity. We review the application of shape in various biological systems such as substrate recognition, ligand specificity / selectivity and antibody recognition in the context of computational methods such as docking, quantitative structure activity relationships, classification models and similarity search algorithms. These in silico pharmacology methods have recently demonstrated the importance and applicability of determining molecular shape in drug discovery, virtual screening and predictive toxicology. The results from recently published studies show that shape and shape-based descriptors are at least as useful as other traditional molecular descriptors.
Antibody; Depth; Descriptors; Dopamine receptors; Molecular shape; Nuclear hormone receptor; Pharmacophore
The human pregnane X receptor (PXR) is a transcriptional regulator of many genes involved in xenobiotic metabolism and excretion. Reliable prediction of high affinity binders with this receptor would be valuable for pharmaceutical drug discovery to predict potential toxicological responses
Materials and Methods
Computational models were developed and validated for a dataset consisting of human PXR (PXR) activators and non-activators. We used support vector machine (SVM) algorithms with molecular descriptors derived from two sources, Shape Signatures and the Molecular Operating Environment (MOE) application software. We also employed the molecular docking program GOLD in which the GoldScore method was supplemented with other scoring functions to improve docking results.
The overall test set prediction accuracy for PXR activators with SVM was 72% to 81%. This indicates that molecular shape descriptors are useful in classification of compounds binding to this receptor. The best docking prediction accuracy (61%) was obtained using 1D Shape Signature descriptors as a weighting factor to the GoldScore. By pooling the available human PXR data sets we revealed those molecular features that are associated with human PXR activators.
These combined computational approaches using molecular shape information may assist scientists to more confidently identify PXR activators.
docking; hybrid methods; machine learning; pregnane X receptor; shape signatures descriptors; support vector machine
The goals of the present study were to apply a generalized regression model and support vector machine (SVM) models with Shape Signatures descriptors, to the domain of blood—brain barrier (BBB) modeling.
Materials and Methods
The Shape Signatures method is a novel computational tool that was used to generate molecular descriptors utilized with the SVM classification technique with various BBB datasets. For comparison purposes we have created a generalized linear regression model with eight MOE descriptors and these same descriptors were also used to create SVM models.
The generalized regression model was tested on 100 molecules not in the model and resulted in a correlation r2=0.65. SVM models with MOE descriptors were superior to regression models, while Shape Signatures SVM models were comparable or better than those with MOE descriptors. The best 2D shape signature models had 10-fold cross validation prediction accuracy between 80–83% and leave-20%-out testing prediction accuracy between 80–82% as well as correctly predicting 84% of BBB+ compounds (n=95) in an external database of drugs.
Our data indicate that Shape Signatures descriptors can be used with SVM and these models may have utility for predicting blood—brain barrier permeation in drug discovery.
blood—brain barrier; principal component analysis; regression; shape signatures; support vector machine
Transcriptional regulation of some genes involved in xenobiotic detoxification and apoptosis is performed via the human pregnane X receptor (PXR) which in turn is activated by structurally diverse agonists including steroid hormones. Activation of PXR has the potential to initiate adverse effects, altering drug pharmacokinetics or perturbing physiological processes. Reliable computational prediction of PXR agonists would be valuable for pharmaceutical and toxicological research. There has been limited success with structure-based modeling approaches to predict human PXR activators. Slightly better success has been achieved with ligand-based modeling methods including quantitative structure-activity relationship (QSAR) analysis, pharmacophore modeling and machine learning. In this study, we present a comprehensive analysis focused on prediction of 115 steroids for ligand binding activity towards human PXR. Six crystal structures were used as templates for docking and ligand-based modeling approaches (two-, three-, four- and five-dimensional analyses). The best success at external prediction was achieved with 5D-QSAR. Bayesian models with FCFP_6 descriptors were validated after leaving a large percentage of the dataset out and using an external test set. Docking of ligands to the PXR structure co-crystallized with hyperforin had the best statistics for this method. Sulfated steroids (which are activators) were consistently predicted as non-activators while, poorly predicted steroids were docked in a reverse mode compared to 5α-androstan-3β-ol. Modeling of human PXR represents a complex challenge by virtue of the large, flexible ligand-binding cavity. This study emphasizes this aspect, illustrating modest success using the largest quantitative data set to date and multiple modeling approaches.
Promiscuous proteins generally bind a large array of diverse ligand structures. This may be facilitated by a very large binding site, multiple binding sites, or a flexible binding site that can adjust to the size of the ligand. These aspects also increase the complexity of predicting whether a molecule will bind or not to such proteins which frequently function as exogenous compound sensors to respond to toxic stress. For example, transporters may prevent absorption of some molecules, and enzymes may convert them to more readily excretable compounds (or alternatively activate them prior to further clearance by other detoxification enzymes). Nuclear hormone receptors may respond to ligands and then affect downstream gene expression to upregulate both enzymes and transporters to increase the clearance for the same or different molecules. We have assessed the ability of many different ligand-based and structure-based computational approaches to model and predict the activation of human PXR by steroidal compounds. We find the most effective computational approach to identify potential steroidal PXR agonists which are clinically relevant due to their widespread use in clinical medicine and the presence of mimics in the environment.
G-protein coupled receptors (GPCRs) comprise a large superfamily of proteins that are targets for nearly 50% of drugs in clinical use today. In the past, the use of structure-based drug design strategies to develop better drug candidates has been severely hampered due to the absence of the receptor’s three-dimensional structure. However, with recent advances in molecular modeling techniques and better computing power, atomic level details of these receptors can be derived from computationally derived molecular models. Using information from these models coupled with experimental evidence, it has become feasible to build receptor pharmacophores. In this study, we demonstrate the use of the Hybrid Structure Based (HSB) method that can be used effectively to screen and identify prospective ligands that bind to GPCRs. Essentially; this multi-step method combines ligand-based methods for building enriched libraries of small molecules and structure-based methods for screening molecules against the GPCR target. The HSB method was validated to identify retinal and its analogues from a random dataset of ∼300,000 molecules. The results from this study showed that the 9 top-ranking molecules are indeed analogues of retinal. The method was also tested to identify analogues of dopamine binding to the dopamine D2 receptor. Six of the ten top-ranking molecules are known analogues of dopamine including a prodrug, while the other thirty-four molecules are currently being tested for their activity against all dopamine receptors. The results from both these test cases have proved that the HSB method provides a realistic solution to bridge the gap between the ever-increasing demand for new drugs to treat psychiatric disorders and the lack of efficient screening methods for GPCRs.
GPCRs; Virtual screening; Structure-based methods; Shape Signatures; Dopamine receptors; Scoring functions