Homology modeling of the human 5-HT1A, 5-HT2A, D1, and D2 receptors: model refinement with molecular dynamics simulations and docking evaluation

Identification of Potential Aldose Reductase Inhibitors Using Convolutional Neural Network-Based in Silico Screening

Aldose reductase (ALR2) is a notable enzyme of the polyol pathway responsible for aggravating diabetic neuropathy complications. The first step begins when it catalyzes the reduction of glucose to sorbitol with NADPH as a coenzyme. Elevated concentrations of sorbitol damage the tissues, leading to complications like neuropathy. Though considerable effort has been pushed toward the successful discovery of potent inhibitors, its discovery still remains an elusive task. To this end, we present a 3D convolutional neural network (3D-CNN) based ALR2 inhibitor classification technique by dealing with snapshots of images captured from 3D chemical structures with multiple rotations as input data. The CNN-based architecture was trained on the 360 sets of image data along each axis and further prediction on the Maybridge library by each of the models. Subjecting the retrieved hits to molecular docking leads to the identification of the top 10 molecules with high binding affinity. The hits displayed a better blood-brain barrier penetration (BBB) score (90% with more than four scores) as compared to standard inhibitors (38%), reflecting the superior BBB penetrating efficiency of the hits. Followed by molecular docking, the biological evaluation spotlighted five compounds as promising ALR2 inhibitors and can be considered as a likely prospect for further structural optimization with medicinal chemistry efforts to improve their inhibition efficacy and consolidate them as new ALR2 antagonists in the future. In addition, the study also demonstrated the usefulness of scaffold analysis of the molecules as a method for investigating the significance of structurally diverse compounds in data-driven studies. For reproducibility and accessibility purposes, all of the source codes used in our study are publicly available.

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.

Biophysical insights into OR2T7: Investigation of a potential prognostic marker for glioblastoma

Glioblastoma multiforme (GBM) is the most aggressive and prevalent form of brain cancer, with an expected survival of 12-15 months following diagnosis. GBM affects the glial cells of the central nervous system, which impairs regular brain function including memory, hearing, and vision. GBM has virtually no long-term survival even with treatment, requiring novel strategies to understand disease progression. Here, we identified a somatic mutation in OR2T7, a G-protein-coupled receptor (GPCR), that correlates with reduced progression-free survival for glioblastoma (log rank p-value = 0.05), suggesting a possible role in tumor progression. The mutation, D125V, occurred in 10% of 396 glioblastoma samples in The Cancer Genome Atlas, but not in any of the 2504 DNA sequences in the 1000 Genomes Project, suggesting that the mutation may have a deleterious functional effect. In addition, transcriptome analysis showed that the p38α mitogen-activated protein kinase (MAPK), c-Fos, c-Jun, and JunB proto-oncogenes, and putative tumor suppressors RhoB and caspase-14 were underexpressed in glioblastoma samples with the D125V mutation (false discovery rate < 0.05). Molecular modeling and molecular dynamics simulations have provided preliminary structural insight and indicate a dynamic helical movement network that is influenced by the membrane-embedded, cytofacial-facing residue 125, demonstrating a possible obstruction of G-protein binding on the cytofacial exposed region. We show that the mutation impacts the "open" GPCR conformation, potentially affecting Gα-subunit binding and associated downstream activity. Overall, our findings suggest that the Val125 mutation in OR2T7 could affect glioblastoma progression by downregulating GPCR-p38 MAPK tumor-suppression pathways and impacting the biophysical characteristics of the structure that facilitates Gα-subunit binding. This study provides the theoretical basis for further experimental investigation required to confirm that the D125V mutation in OR2T7 is not a passenger mutation. With validation, the aforementioned mutation could represent an important prognostic marker and a potential therapeutic target for glioblastoma.

Overcoming Depression with 5-HT2A Receptor Ligands

Depression is a multifactorial disorder that affects millions of people worldwide, and none of the currently available therapeutics can completely cure it. Thus, there is a need for developing novel, potent, and safer agents. Recent medicinal chemistry findings on the structure and function of the serotonin 2A (5-HT2A) receptor facilitated design and discovery of novel compounds with antidepressant action. Eligible papers highlighting the importance of 5-HT2A receptors in the pathomechanism of the disorder were identified in the content-screening performed on the popular databases (PubMed, Google Scholar). Articles were critically assessed based on their titles and abstracts. The most accurate papers were chosen to be read and presented in the manuscript. The review summarizes current knowledge on the applicability of 5-HT2A receptor signaling modulators in the treatment of depression. It provides an insight into the structural and physiological features of this receptor. Moreover, it presents an overview of recently conducted virtual screening campaigns aiming to identify novel, potent 5-HT2A receptor ligands and additional data on currently synthesized ligands acting through this protein.

In Vitro and In Silico Characterization of Kurarinone as a Dopamine D1A Receptor Antagonist and D2L and D4 Receptor Agonist

Alterations in the expression and/or activity of brain G-protein-coupled receptors (GPCRs) such as dopamine D₁R, D_2LR, D₃R, and D₄R, vasopressin V_1AR, and serotonin 5-HT_1AR are noted in various neurodegenerative diseases (NDDs). Since studies have indicated that flavonoids can target brain GPCRs and provide neuroprotection via inhibition of monoamine oxidases (hMAOs), our study explored the functional role of kurarinone, an abundant lavandulated flavonoid in Sophora flavescens, on dopamine receptor subtypes, V_1AR, 5-HT_1AR, and hMAOs. Radioligand binding assays revealed considerable binding of kurarinone on D₁R, D_2LR, and D₄R. Functional GPCR assays unfolded the compound's antagonist behavior on D₁R (IC₅₀ 42.1 ± 0.35 μM) and agonist effect on D_2LR and D₄R (EC₅₀ 22.4 ± 3.46 and 71.3 ± 4.94 μM, respectively). Kurarinone was found to inhibit hMAO isoenzymes in a modest and nonspecific manner. Molecular docking displayed low binding energies during the intermolecular interactions of kurarinone with the key residues of the deep orthosteric binding pocket and the extracellular loops of D₁R, D_2LR, and D₄R, validating substantial binding affinities to these prime targets. With appreciable D_2LR and D₄R agonism and D₁R antagonism, kurarinone might be a potential compound that can alleviate clinical symptoms of Parkinson's disease and other NDDs.

Identification of Novel CD39 Inhibitors Based on Virtual Screening and Enzymatic Assays

The accumulation of adenosine in the tumor microenvironment mediates immunosuppression and promotes tumor growth and proliferation. Intervention of the adenosine pathway is an important direction of antitumor immunity research. CD39 is an important ecto-nucleotidases for adenosine generation, therefore targeting the CD39-adenosine pathway is an emerging immune checkpoint for anticancer treatment. However, currently no CD39 inhibitor has been approved by the U.S. Food and Drug Administration. The development of CD39 drugs is urgent for clinical application. In this study, we combined homology modeling, virtual screening, and in vitro enzymatic activity to characterize the structural features of the CD39 protein and identify a triazinoindole-based compound as a CD39 inhibitor. The identified inhibitor and one of its analogues could effectively prevent the enzymatic activity of CD39 with IC₅₀ values of 27.42 ± 5.52 and 79.24 ± 12.21 μM, respectively. At the same time, the inhibitor significantly inhibited the adenosine monophosphate production in colorectal cancer cell lines (HT29 and MC38) and thereafter prevented cell proliferation. Molecular docking studies, mutagenesis, and microscale thermophoresis indicated that residues such as R85 could be the main contributor in binding triazinoindole compounds. The binding mode can potentially be utilized for hit-to-lead optimization, and the identified inhibitor can be further tested for its anticancer activity in vivo or may serve as a chemical agent to study CD39-related functions.

Efficiency of Homology Modeling Assisted Molecular Docking in G-protein Coupled Receptors

BACKGROUND

Molecular docking is in regular practice to assess ligand affinity on a target protein crystal structure. In the absence of protein crystal structure, the homology modeling or comparative modeling is the best alternative to elucidate the relationship details between a ligand and protein at the molecular level. The development of accurate homology modeling (HM) and its integration with molecular docking (MD) is essential for successful, rational drug discovery.

OBJECTIVE

The G-protein coupled receptors (GPCRs) are attractive therapeutic targets due to their immense role in human pharmacology. The GPCRs are membrane-bound proteins with the complex constitution, and the understanding of their activation and inactivation mechanisms is quite challenging. Over the past decade, there has been a rapid expansion in the number of solved G-protein-coupled receptor (GPCR) crystal structures; however, the majority of the GPCR structures remain unsolved. In this context, HM guided MD has been widely used for structure-based drug design (SBDD) of GPCRs.

METHODS

The focus of this review is on the recent (i) developments on HM supported GPCR drug discovery in the absence of GPCR crystal structures and (ii) application of HM in understanding the ligand interactions at the binding site, virtual screening, determining receptor subtype selectivity and receptor behaviour in comparison with GPCR crystal structures.

RESULTS

The HM in GPCRs has been extremely challenging due to the scarcity in template structures. In such a scenario, it is difficult to get accurate HM that can facilitate understanding of the ligand-receptor interactions. This problem has been alleviated to some extent by developing refined HM based on incorporating active /inactive ligand information and inducing protein flexibility. In some cases, HM proteins were found to outscore crystal structures.

CONCLUSION

The developments in HM have been highly operative to gain insights about the ligand interaction at the binding site and receptor functioning at the molecular level. Thus, HM guided molecular docking may be useful for rational drug discovery for the GPCRs mediated diseases.

Reliability of Docking-Based Virtual Screening for GPCR Ligands with Homology Modeled Structures: A Case Study of the Angiotensin II Type I Receptor

The number of solved G-protein-coupled receptor (GPCR) crystal structures has expanded rapidly, but most GPCR structures remain unsolved. Therefore, computational techniques, such as homology modeling, have been widely used to produce the theoretical structures of various GPCRs for structure-based drug design (SBDD). Due to the low sequence similarity shared by the transmembrane domains of GPCRs, accurate prediction of GPCR structures by homology modeling is quite challenging. In this study, angiotensin II type I receptor (AT1R) was taken as a typical case to assess the reliability of class A GPCR homology models for SBDD. Four homology models of angiotensin II type I receptor (AT1R) at the inactive state were built based on the crystal structures of CXCR4 chemokine receptor, CCR5 chemokine receptor, and δ-opioid receptor, and refined through molecular dynamics (MD) simulations and induced-fit docking, to allow for backbone and side-chain flexibility. Then, the quality of the homology models was assessed relative to the crystal structures in terms of two criteria commonly used in SBDD: prediction accuracy of ligand-binding poses and screening power of docking-based virtual screening. It was found that the crystal structures outperformed the homology models prior to any refinement in both assessments. MD simulations could generally improve the docking results for both the crystal structures and homology models. Moreover, the optimized homology model refined by MD simulations and induced-fit docking even shows a similar performance of the docking assessment to the crystal structures. Our results indicate that it is possible to establish a reliable class A GPCR homology model for SBDD through the refinement by integrating multiple molecular modeling techniques.

Comparative molecular field analysis and molecular dynamics studies of the dopamine D2 receptor antagonists without a protonatable nitrogen atom

The dopaminergic hypothesis of schizophrenia is the main concept explaining the direct reasons of schizophrenia and the effectiveness of current antipsychotics. All antipsychotics present on the market are potent dopamine D₂ receptor antagonists or partial agonists. In this work we investigate a series of dopamine D₂ receptor antagonists which do not fulfill the criteria of the classical pharmacophore model as they do not possess a protonatable nitrogen atom necessary to interact with the conserved Asp(3.32). Such compounds are interesting, inter alia, due to possible better pharmacokinetic profile when compared to basic, ionizable molecules. By means of homology modeling, molecular docking and molecular dynamics we determined that the compounds investigated interact with Asp(3.32) via their amide nitrogen atom. It was found that the studied compounds stabilize the receptor inactive conformation through the effect on the ionic lock, which is typical for GPCR antagonists. We constructed a CoMFA model for the studied compounds with the following statistics: R² = 0.95, Q² = 0.63. The quality of the CoMFA model was confirmed by high value of R² of the test set, equal 0.96. The CoMFA model indicated two regions where bulky substituents are favored and two regions where bulky substituents are not beneficial. Two red contour regions near carbonyl groups were identified meaning that negative charge would be favored here. Furthermore, the S-oxide group is connected with blue contour region meaning that positive charge is favored in this position. These findings may be applied for further optimization of the studied compound series.

Mechanism Exploration of Arylpiperazine Derivatives Targeting the 5-HT2A Receptor by In Silico Methods

As a G-protein coupled receptor, the 5-hydroxytryptamine 2A (5-HT_2A) receptor is known for its critical role in the cognitive, behavioural and physiological functions, and thus is a primary molecular target to treat psychiatric diseases, including especially depression. With purpose to explore the structural traits affecting the inhibitory activity, currently a dataset of 109 arylpiperazine derivatives as promising 5-HT_2A antagonists was built, based on which the ligand-based three-dimensional quantitative structure-activity relationship (3D-QSAR) study by using both comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) approaches was carried out. The resultant optimal CoMSIA model displays proper validity and predictability with cross-validated correlation coefficient Q² = 0.587, non-cross-validated correlation coefficient R²_ncv = 0.900 and predicted correlation coefficient for the test set of compounds R²_pre = 0.897, respectively. Besides, molecular docking was also conducted to investigate the binding mode between these ligands and the active site of the 5-HT_2A receptor. Meanwhile, as a docking supplementary tool to study the antagonists' conformation in the binding cavity, molecular dynamics (MD) simulation was also performed, providing further elucidation about the changes in the ligand-receptor complex. Lastly, some new molecules were also newly-designed based on the above results that are potential arylpiperazine antagonists of 5-HT_2A receptor. We hope that the present models and derived information may be of help for facilitating the optimization and design of novel potent antagonists as antidepressant drugs as well as exploring the interaction mechanism of 5-HT_2A antagonists.

Design, synthesis and preliminary evaluation of dopamine-amino acid conjugates as potential D1 dopaminergic modulators

The dopamine-amino acid conjugate DA-Phen was firstly designed to obtain a useful prodrug for the therapy of Parkinson's disease, but experimental evidence shows that it effectively interacts with D₁ dopamine receptors (D₁DRs), leading to an enhancement in cognitive flexibility and to the development of adaptive strategies in aversive mazes, together with a decrease in despair-like behavior. In this paper, homology modelling, molecular dynamics, and site mapping of D1 receptor were carried out with the aim of further performing docking studies on other dopamine conjugates compared with D1 agonists, in the attempt to identify new compounds with potential dopaminergic activity. Two new conjugates (DA-Trp 2C, and DA-Leu 3C) have been identified as the most promising candidates, and consequently synthesized. Preliminary evaluation in terms of distribution coefficient (D^pH7.4), stability in rat brain homogenate, and in human plasma confirmed that DA-Trp (2C), and DA-Leu (3C) could be considered as very valuable candidates for further in vivo studies as new dopaminergic drugs.

In vitro, molecular modeling and behavioral studies of 3-{[4-(5-methoxy-1H-indol-3-yl)-1,2,3,6-tetrahydropyridin-1-yl]methyl}-1,2-dihydroquinolin-2-one (D2AAK1) as a potential antipsychotic

Antipsychotics currently available to treat schizophrenia suffer several limitations: (1) they are efficient against positive but not negative and cognitive symptoms of the disease; (2) they help only a half of patients; (3) they have severe side effects including neurological and metabolic side effects. Thus, novel drugs to treat schizophrenia are highly demanded. We identified a novel dopamine D2 receptor antagonist, D2AAK1, with Ki of 58 nM using structure-based virtual screening. D2AAK1 possesses additional nanomolar or low micromolar affinity to D1, D3, 5-HT1A and 5-HT2A receptors, making it an ideal candidate for a multi-target drug. Here we present homology modeling, molecular docking and molecular dynamics of D2AAK1 and its molecular targets and animal studies of D2AAK1 as a potential antipsychotic. The main contact of D2AAK1 and all the receptors studied is the electrostatic interaction between the protonable nitrogen atom of the ligand and the conserved Asp(3.32) as typical for orthosteric ligands of aminergic GPCRs. We confirmed antagonistic/partial agonistic properties of D2AAK1 towards all the receptors in in vitro essays and in in silico studies as the ligand stabilizes the ionic lock interaction. We also demonstrated neuroleptic, anxiolytic and, importantly, procognitive properties of D2AAK1 in mouse models.

Photoprotective efficiency of PLGA-curcumin nanoparticles versus curcumin through the involvement of ERK/AKT pathway under ambient UV-R exposure in HaCaT cell line

Curcumin (Cur) has been demonstrated to have wide pharmacological window including anti-oxidant and anti-inflammatory properties. However, phototoxicity under sunlight exposure and poor biological availability limits its applicability. We have synthesized biodegradable and non-toxic polymer-poly (lactic-co-glycolic) acid (PLGA) encapsulated formulation of curcumin (PLGA-Cur-NPs) of 150 nm size range. Photochemically free curcumin generates ROS, lipid peroxidation and induces significant UVA and UVB mediated impaired mitochondrial functions leading to apoptosis/necrosis and cell injury in two different origin cell lines viz., mouse fibroblasts-NIH-3T3 and human keratinocytes-HaCaT as compared to PLGA-Cur-NPs. Molecular docking studies suggested that intact curcumin from nanoparticles, bind with BAX in BIM SAHB site and attenuate it to undergo apoptosis while upregulating anti-apoptotic genes like BCL2. Real time studies and western blot analysis with specific phosphorylation inhibitor of ERK1 and AKT1/2/3 confirm the involvement of ERK/AKT signaling molecules to trigger the survival cascade in case of PLGA-Cur-NPs. Our finding demonstrates that low level sustained release of curcumin from PLGA-Cur-NPs could be a promising way to protect the adverse biological interactions of photo-degradation products of curcumin upon the exposure of UVA and UVB. Hence, the applicability of PLGA-Cur-NPs could be suggested as prolonged radical scavenging ingredient in curcumin containing products.

In Silico and In Vitro Analysis of Bacoside A Aglycones and Its Derivatives as the Constituents Responsible for the Cognitive Effects of Bacopa monnieri

Bacopa monnieri has been used in Ayurvedic medicine to improve memory and cognition. The active constituent responsible for its pharmacological effects is bacoside A, a mixture of dammarane-type triterpenoid saponins containing sugar chains linked to a steroid aglycone skeleton. Triterpenoid saponins have been reported to be transformed in vivo to metabolites that give better biological activity and pharmacokinetic characteristics. Thus, the activities of the parent compounds (bacosides), aglycones (jujubogenin and pseudojujubogenin) and their derivatives (ebelin lactone and bacogenin A1) were compared using a combination of in silico and in vitro screening methods. The compounds were docked into 5-HT1A, 5-HT2A, D1, D2, M1 receptors and acetylcholinesterase (AChE) using AutoDock and their central nervous system (CNS) drug-like properties were determined using Discovery Studio molecular properties and ADMET descriptors. The compounds were screened in vitro using radioligand receptor binding and AChE inhibition assays. In silico studies showed that the parent bacosides were not able to dock into the chosen CNS targets and had poor molecular properties as a CNS drug. In contrast, the aglycones and their derivatives showed better binding affinity and good CNS drug-like properties, were well absorbed through the intestines and had good blood brain barrier (BBB) penetration. Among the compounds tested in vitro, ebelin lactone showed binding affinity towards M1 (Ki = 0.45 μM) and 5-HT2A (4.21 μM) receptors. Bacoside A and bacopaside X (9.06 μM) showed binding affinity towards the D1 receptor. None of the compounds showed any inhibitory activity against AChE. Since the stimulation of M1 and 5-HT2A receptors has been implicated in memory and cognition and ebelin lactone was shown to have the strongest binding energy, highest BBB penetration and binding affinity towards M1 and 5-HT2A receptors, we suggest that B. monnieri constituents may be transformed in vivo to the active form before exerting their pharmacological activity.

Exploring the binding properties of agonists interacting with human TGR5 using structural modeling, molecular docking and dynamics simulations

TGR5, act as a potential pharmacological target in the treatment of type II diabetes. In the computational study, structural modeling and binding site prediction of TGR5 receptor was performed. Two well-known agonists of TGR5 used to investigate the mode and mechanism of binding.

Interaction investigations of crustacean β-GBP recognition toward pathogenic microbial cell membrane and stimulate upon prophenoloxidase activation

In invertebrates, crustaceans' immune system consists of pattern recognition receptors (PRRs) instead of immunoglobulin's, which involves in the microbial recognition and initiates the protein-ligand interaction between hosts and pathogens. In the present study, PRRs namely β-1,3 glucan binding protein (β-GBP) from mangrove crab Episesarma tetragonum and its interactions with the pathogens such as bacterial and fungal outer membrane proteins (OMP) were investigated through microbial aggregation and computational interaction studies. Molecular recognition and microbial aggregation results of Episesarma tetragonum β-GBP showed the specific binding affinity toward the fungal β-1,3 glucan molecule when compared to other bacterial ligands. Because of this microbial recognition, prophenoloxidase activity was enhanced and triggers the innate immunity inside the host animal. Our findings disclose the role of β-GBP in molecular recognition, host-pathogen interaction through microbial aggregation, and docking analysis. In vitro results were concurred with the in silico docking, and molecular dynamics simulation analysis. This study would be helpful to understand the molecular mechanism of β-GBP and update the current knowledge on the PRRs of crustaceans.

Impact of template choice on homology model efficiency in virtual screening

Homology modeling is a reliable method of predicting the three-dimensional structures of proteins that lack NMR or X-ray crystallographic data. It employs the assumption that a structural resemblance exists between closely related proteins. Despite the availability of many crystal structures of possible templates, only the closest ones are chosen for homology modeling purposes. To validate the aforementioned approach, we performed homology modeling of four serotonin receptors (5-HT1AR, 5-HT2AR, 5-HT6R, 5-HT7R) for virtual screening purposes, using 10 available G-Protein Coupled Receptors (GPCR) templates with diverse evolutionary distances to the targets, with various approaches to alignment construction and model building. The resulting models were further validated in two steps by means of ligand docking and enrichment calculation, using Glide software. The final quality of the models was determined in virtual screening-like experiments by the AUROC score of the resulting ROC curves. The outcome of this research showed that no correlation between sequence identity and model quality was found, leading to the conclusion that the closest phylogenetic relative is not always the best template for homology modeling.

Toward activated homology models of the human M1 muscarinic acetylcholine receptor

Structure-based virtual screening offers a good opportunity for the discovery of selective M1 muscarinic acetylcholine receptor (mAChR) agonists for the treatment of Alzheimer's disease. However, no 3-D structure of an M1 mAChR is yet available and the homology models that have been previously reported are only able to identify antagonists in virtual screening experiments. In this study, we generated a homology model of the human M1 mAChR, based on the crystal structure of an M3 mAChR as the template. This initial model was modified, using the agonist-bound crystal structure of a β2-adrenergic receptor as a guide, to give two possible activated structures. The T192 side chain was adjusted in both structures and one of the structures also had the whole of transmembrane (TM) 5 rotated and tilted toward the inner channel of the transmembrane region. The binding sites of all three structures were then refined by induced-fit docking (IFD) with acetylcholine. Virtual screening experiments showed that all three refined models could efficiently differentiate agonists from decoy molecules, with the TM5-modified models also giving good agonist/antagonist selectivity. The whole range of agonists and antagonists was observed to bind within the orthosteric site of the structure obtained by IFD refinement alone, implying that it has inactive state character. In contrast, the two TM5-modified structures were unable to accommodate the antagonists, supporting the proposition that they possess activated state character.

Insights into the influence of 5-HT2c aminoacidic variants with the inhibitory action of serotonin inverse agonists and antagonists

Specific modulation of serotonin 5-HT(2C) G protein-coupled receptors may be therapeutic for obesity and neuropsychiatric disorders. The different efficacy of drugs targeting these receptors are due to the presence of genetic variants in population and this variability is still hard to predict. Therefore, in order to administer the more suitable drug, taking into account patient genotype, it is necessary to know the molecular effects of its gene nucleotide variations. In this work, starting from an accurate 3D model of 5-HT(2C), we focus on the prediction of the possible effect of some single nucleotide polymorphisms (SNPs) producing amino acidic changes in proximity of the 5-HT(2C) ligand binding site. Particularly we chose a set of 5-HT(2C) inverse agonists and antagonists which have high inhibitory activity. After prediction of the structures of the receptor-ligand complexes using molecular docking tools, we performed full atom molecular dynamics simulations in explicit lipid bilayer monitoring the interactions between ligands and trans-membrane helices of the receptor, trying to infer relations with their biological activity. Serotonin, as the natural ligand was chosen as reference compound to advance a hypothesis able to explain the receptor inhibition mechanism. Indeed we observed a different behavior between the antagonists and inverse agonist with respect to serotonin or unbounded receptor, which could be responsible, even if not directly, of receptor's inactivation. Furthermore, we analyzed five aminoacidic variants of 5HT(2C) receptor observing alterations in the interactions between ligands and receptor which give rise to changes of free energy values for every complex considered.

Prospecting for novel plant-derived molecules of Rauvolfia serpentina as inhibitors of Aldose Reductase, a potent drug target for diabetes and its complications

Aldose Reductase (AR) is implicated in the development of secondary complications of diabetes, providing an interesting target for therapeutic intervention. Extracts of Rauvolfia serpentina, a medicinal plant endemic to the Himalayan mountain range, have been known to be effective in alleviating diabetes and its complications. In this study, we aim to prospect for novel plant-derived inhibitors from R. serpentina and to understand structural basis of their interactions. An extensive library of R. serpentina molecules was compiled and computationally screened for inhibitory action against AR. The stability of complexes, with docked leads, was verified using molecular dynamics simulations. Two structurally distinct plant-derived leads were identified as inhibitors: indobine and indobinine. Further, using these two leads as templates, 16 more leads were identified through ligand-based screening of their structural analogs, from a small molecules database. Thus, we obtained plant-derived indole alkaloids, and their structural analogs, as potential AR inhibitors from a manually curated dataset of R. serpentina molecules. Indole alkaloids reported herein, as a novel structural class unreported hitherto, may provide better insights for designing potential AR inhibitors with improved efficacy and fewer side effects.

Homology modeling of dopamine D2 and D3 receptors: molecular dynamics refinement and docking evaluation

Dopamine (DA) receptors, a class of G-protein coupled receptors (GPCRs), have been targeted for drug development for the treatment of neurological, psychiatric and ocular disorders. The lack of structural information about GPCRs and their ligand complexes has prompted the development of homology models of these proteins aimed at structure-based drug design. Crystal structure of human dopamine D₃ (hD₃) receptor has been recently solved. Based on the hD₃ receptor crystal structure we generated dopamine D₂ and D₃ receptor models and refined them with molecular dynamics (MD) protocol. Refined structures, obtained from the MD simulations in membrane environment, were subsequently used in molecular docking studies in order to investigate potential sites of interaction. The structure of hD₃ and hD_2L receptors was differentiated by means of MD simulations and D₃ selective ligands were discriminated, in terms of binding energy, by docking calculation. Robust correlation of computed and experimental K_i was obtained for hD₃ and hD_2L receptor ligands. In conclusion, the present computational approach seems suitable to build and refine structure models of homologous dopamine receptors that may be of value for structure-based drug discovery of selective dopaminergic ligands.

Computational and experimental analysis of the transmembrane domain 4/5 dimerization interface of the serotonin 5-HT(1A) receptor

Experimental evidence suggests that most members of class A G-protein coupled receptors (GPCRs) can form homomers and heteromers in addition to functioning as single monomers. In particular, serotonin (5-HT) receptors were shown to homodimerize and heterodimerize with other GPCRs, although the details and the physiological role of the oligomerization has not yet been fully elucidated. Here we used computational modeling of the 5-HT(1A) receptor monomer and dimer to predict residues important for dimerization. Based on these results, we carried out rationally designed site-directed mutagenesis. The ability of the mutants to dimerize was evaluated using different FRET-based approaches. The reduced levels of acceptor photobleaching-Förster resonance energy transfer (FRET) and the lower number of monomers participating in oligomers, as assessed by lux-FRET, confirmed the decreased ability of the mutants to dimerize and the involvement of the predicted contacts (Trp175(4.64), Tyr198(5.41), Arg151(4.40), and Arg152(4.41)) at the interface. This information was reintroduced as constraints for computational protein-protein docking to obtain a high-quality dimer model. Analysis of the refined model as well as molecular dynamics simulations of wild-type (WT) and mutant dimers revealed compensating interactions in dimers composed of WT and W175A mutant. This provides an explanation for the requirement of mutations of Trp175(4.64) in both homomers for disrupting dimerization. Our iterative computational-experimental study demonstrates that transmembrane domains TM4/TM5 can form an interaction interface in 5-HT(1A) receptor dimers and indicates that specific amino acid interactions maintain this interface. The mutants and the optimized model of the dimer structure may be used in functional studies of serotonin dimers.