In silico identification of novel lead compounds with AT1 receptor antagonist activity: successful application of chemical database screening protocol.
ABSTRACT: AT1 receptor antagonists are clinically effective drugs for the treatment of hypertension, cardiovascular, and related disorders. In an attempt to identify new AT1 receptor antagonists, a pharmacophore-based virtual screening protocol was applied. The pharmacophore models were generated from 30 training set compounds. The best model was chosen on the basis of squared correlation coefficient of training set and internal test set. The validity of the developed model was also ensured using catScramble validation method and external test set prediction.The final model highlighted the importance of hydrogen bond acceptor, hydrophobic aliphatic, hydrophobic, and ring aromatic features. The model satisfied all the statistical criteria such as cost function analysis and correlation coefficient. The result of estimated activity for internal and external test set compounds reveals that the generated model has high prediction capability. The validated pharmacophore model was further used for mining of 56000 compound database (MiniMaybridge). Total 141 hits were obtained and all the hits were checked for druggability, this led to the identification of two active druggable AT1 receptor antagonists with diverse structure.A highly validated pharmacophore model generated in this study identified two novel druggable AT1 receptor antagonists. The developed model can also be further used for mining of other virtual database.
Project description:AIM: Both endothelin ETA receptor antagonists and angiotensin AT1 receptor antagonists lower blood pressure in hypertensive patients. A dual AT1 and ETA receptor antagonist may be more efficacious antihypertensive drug. In this study we identified the mode and mechanism of binding of imidazole series of compounds as dual AT1 and ETA receptor antagonists. METHODS: Molecular modeling approach combining quantum-polarized ligand docking (QPLD), MM/GBSA free-energy calculation and 3D-QSAR analysis was used to evaluate 24 compounds as dual AT1 and ETA receptor antagonists and to reveal their binding modes and structural basis of the inhibitory activity. Pharmacophore-based virtual screening and docking studies were performed to identify more potent dual antagonists. RESULTS: 3D-QSAR models of the imidazole compounds were developed from the conformer generated by QPLD, and the resulting models showed a good correlation between the predicted and experimental activity. The visualization of the 3D-QSAR model in the context of the compounds under study revealed the details of the structure-activity relationship: substitution of methoxymethyl and cyclooctanone might increase the activity against AT1 receptor, while substitution of cyclohexone and trimethylpyrrolidinone was important for the activity against ETA receptor; addition of a trimethylpyrrolidinone to compound 9 significantly reduced its activity against AT1 receptor but significantly increased its activity against ETA receptor, which was likely due to the larger size and higher intensities of the H-bond donor and acceptor regions in the active site of ETA receptor. Pharmacophore-based virtual screening followed by subsequent Glide SP, XP, QPLD and MM/GBSA calculation identified 5 potential lead compounds that might act as dual AT1 and ETA receptor antagonists. CONCLUSION: This study may provide some insights into the development of novel potent dual ETA and AT1 receptor antagonists. As a result, five compounds are found to be the best dual antagonists against AT1R and ETA receptors.
Project description:Pharmacophore queries from previously known potent selective A3 antagonists were generated by Chem-X. These queries were used to search a pharmacophore database of diverse compounds (CNS-Set). In vitro assays of 186 'hits' yielded over 30 active compounds, for four adenosine receptor subtypes. This search strategy may also be applicable to the discovery of new ligands via receptor homology data.
Project description:AIM:The transient receptor potential vanilloid type 1 (TRPV1) is responsible for pain perception in the peripheral nervous system (PNS). TRPV1 is thus considered a versatile target for development of non-opioid analgesics. RESULTS:Pharmacophore-based clustering of a publicly available data set of TRPV1 antagonists revealed a set of models, which were validated with data sets of inactive compounds, decoys and known drug candidates. The top ranked pharmacophore models were subsequently used for virtual screening. Based on a unique in-house protocol, a set of compounds was selected and biologically tested for modulation of TRPV1 in a voltage-clamp model. CONCLUSION:Pharmacophore models extracted from large public data sets are a valuable source for identification of novel scaffolds for TRPV1 receptor modulation.
Project description:The malignant brain tumor (MBT) repeat is an important epigenetic-code "reader" and is functionally associated with differentiation, gene silencing, and tumor suppression. (1-3) Small molecule probes of MBT domains should enable a systematic study of MBT-containing proteins and potentially reveal novel druggable targets. We designed and applied a virtual screening strategy that identified potential MBT antagonists in a large database of commercially available compounds. A small set of virtual hits was purchased and submitted to experimental testing. Nineteen of the purchased compounds showed a specific dose-dependent protein binding and will provide critical structure-activity information for subsequent lead generation and optimization.
Project description:The μ opioid receptor (MOR) is a prominent member of the G protein-coupled receptor family and the molecular target of morphine and other opioid drugs. Despite the long tradition of MOR-targeting drugs, still little is known about the ligand-receptor interactions and structure-function relationships underlying the distinct biological effects upon receptor activation or inhibition. With the resolved crystal structure of the β-funaltrexamine-MOR complex, we aimed at the discovery of novel agonists and antagonists using virtual screening tools, i.e. docking, pharmacophore- and shape-based modeling. We suggest important molecular interactions, which active molecules share and distinguish agonists and antagonists. These results allowed for the generation of theoretically validated in silico workflows that were employed for prospective virtual screening. Out of 18 virtual hits evaluated in in vitro pharmacological assays, three displayed antagonist activity and the most active compound significantly inhibited morphine-induced antinociception. The new identified chemotypes hold promise for further development into neurochemical tools for studying the MOR or as potential therapeutic lead candidates.
Project description:P2Y1 receptor (P2Y1R), which belongs to G protein-coupled receptors (GPCRs), is an important target in ADP-induced platelet aggregation. The crystal structure of P2Y1R has been solved recently, which revealed orthosteric and allosteric ligand-binding sites with the details of ligand-protein binding modes. And it suggests that P2Y1R antagonists, which recognize two distinct sites, could potentially provide an efficacious and safe antithrombotic profile. In present paper, 2D similarity search, pharmacophore based screening, and molecular docking were used to explore the potential natural P2Y1R antagonists. 2D similarity search was used to classify orthosteric and allosteric antagonists of P2Y1R. Based on the result, pharmacophore models were constructed and validated by the test set. Optimal models were selected to discover potential P2Y1R antagonists of orthosteric and allosteric sites from Traditional Chinese Medicine (TCM). And the hits were filtered by Lipinski's rule. Then molecular docking was used to refine the results of pharmacophore based screening and analyze the binding mode of the hits and P2Y1R. Finally, two orthosteric and one allosteric potential compounds were obtained, which might be used in future P2Y1R antagonists design. This work provides a reliable guide for discovering natural P2Y1R antagonists acting on two distinct sites from TCM.
Project description:The G-protein-coupled receptor free fatty acid receptor 1 (FFAR1), previously named GPR40, is a possible novel target for the treatment of type 2 diabetes. In an attempt to identify new ligands for this receptor, we performed virtual screening (VS) based on two-dimensional (2D) similarity, three-dimensional (3D) pharmacophore searches, and docking studies by using the structure of known agonists and our model of the ligand binding site, which was validated by mutagenesis. VS of a database of 2.6 million compounds followed by extraction of structural neighbors of functionally confirmed hits resulted in identification of 15 compounds active at FFAR1 either as full agonists, partial agonists, or pure antagonists. Site-directed mutagenesis and docking studies revealed different patterns of ligand-receptor interactions and provided important information on the role of specific amino acids in binding and activation of FFAR1.
Project description:The antagonist-bound crystal structure of the nociceptin receptor (NOP), from the opioid receptor family, was recently reported along with those of the other opioid receptors bound to opioid antagonists. We recently reported the first homology model of the 'active-state' of the NOP receptor, which when docked with 'agonist' ligands showed differences in the TM helices and residues, consistent with GPCR activation after agonist binding. In this study, we explored the use of the active-state NOP homology model for structure-based virtual screening to discover NOP ligands containing new chemical scaffolds. Several NOP agonist and antagonist ligands previously reported are based on a common piperidine scaffold. Given the structure-activity relationships for known NOP ligands, we developed a hybrid method that combines a structure-based and ligand-based approach, utilizing the active-state NOP receptor as well as the pharmacophoric features of known NOP ligands, to identify novel NOP binding scaffolds by virtual screening. Multiple conformations of the NOP active site including the flexible second extracellular loop (EL2) loop were generated by simulated annealing and ranked using enrichment factor (EF) analysis and a ligand-decoy dataset containing known NOP agonist ligands. The enrichment factors were further improved by combining shape-based screening of this ligand-decoy dataset and calculation of consensus scores. This combined structure-based and ligand-based EF analysis yielded higher enrichment factors than the individual methods, suggesting the effectiveness of the hybrid approach. Virtual screening of the CNS Permeable subset of the ZINC database was carried out using the above-mentioned hybrid approach in a tiered fashion utilizing a ligand pharmacophore-based filtering step, followed by structure-based virtual screening using the refined NOP active-state models from the enrichment analysis. Determination of the NOP receptor binding affinity of a selected set of top-scoring hits resulted in identification of several compounds with measurable binding affinity at the NOP receptor, one of which had a new chemotype for NOP receptor binding. The hybrid ligand-based and structure-based methodology demonstrates an effective approach for virtual screening that leverages existing SAR and receptor structure information for identifying novel hits for NOP receptor binding. The refined active-state NOP homology models obtained from the enrichment studies can be further used for structure-based optimization of these new chemotypes to obtain potent and selective NOP receptor ligands for therapeutic development.
Project description:Aminopeptidase N (APN) inhibitors have been reported to be effective in treating of life threatening diseases including cancer. Validated ligand- and structure-based pharmacophore mapping approaches were combined with Bayesian modeling and recursive partitioning to identify structural and physicochemical requirements for highly active APN inhibitors. Based on the assumption that ligand- and structure-based pharmacophore models are complementary, the efficacy of 'multiple pharmacophore screening' for filtering true positive virtual hits was investigated. These multiple pharmacophore screening methods were utilized to search novel virtual hits for APN inhibition. The number of hits was refined and reduced by recursive partitioning, drug-likeliness, pharmacokinetic property prediction, and comparative molecular-docking studies. Four compounds were proposed as the potential virtual hits for APN enzyme inhibition.
Project description:The nicotinic acetylcholine receptors (nAChRs) are a member of the ligand-gated ion channel family and play a key role in the transfer of information across neurological networks. The X-ray crystal structure of agonist-bound ?(7) acetylcholine binding protein (AChBP) has been recognized as the most appropriate template to model the ligand-binding domain of nAChR for studying the molecular mechanism of the receptor-ligand interactions. Virtual screening of the National Cancer Institute diversity set, a library of 1990 compounds with nonredundant pharmacophore profiles, using AutoDock against AChBPs revealed 51 potential candidates. In vitro radioligand competition assays using [(3)H] epibatidine against the AChBPs from the freshwater snails, Lymnaea stagnalis, and from the marine species, Aplysia californica and the mutant (AcY55W), revealed seven compounds from the list of candidates that had micromolar to nanomolar affinities for the AChBPs. Further investigation on ?(7)nAChR expressing in Xenopus oocytes and on the recombinant receptors with fluorescence resonance energy transfer (FRET)-based calcium sensor expressing in HEK cells showed that seven compounds were antagonists of ?(7)nAChR, only one compound (NSC34352) demonstrated partial agonistic effect at low dose (10 µM), and two compounds (NSC36369 and NSC34352) were selective antagonists on ?(7)nAchR with moderate potency. These hits serve as novel templates/scaffolds for development of more potent and specific in the AChR systems.