Three-dimensional pharmacophore hypotheses for the locust neuronal octopamine receptor (OAR3). Part 2: agonists.

Three-dimensional pharmacophore hypotheses were built from a set of 43 agonists against octopamine receptor class 3 (OAR3) in locust nervous tissue. Among the 10 chemical-featured models generated by program Catalyst/Hypo, a hypothesis including hydrogen-bond acceptor (HBA), hydrophobic (Hp), and hydrophobic aliphatic (HpA1) features was considered to be important and predictive in evaluating OAR3 agonists. While the ideal and null hypotheses had a cost of 156.40 and 239.20, respectively, the 10 resulting hypotheses possessed costs from 169.89 to 175.81. The best hypothesis that was confirmed to have a 95% chance of true correlation yielded a low RMS of 0.757 and high regression r of 0.933. Active agonists mapped well onto all the features of the hypothesis such as HBA, Hp, and HpA1. On the other hand, inactive compounds were shown to be difficult to achieve the energetically favorable conformation which is found in the active molecules in order to fit the 3-D chemical feature pharmacophore models.     

Three-dimensional common-feature hypotheses for octopamine agonist 2-(arylimino)imidazolidines.

Three-dimensional pharmacophore hypotheses were built from a set of 10 octopamine (OA) agonist 2-(Arylimino)imidazolidines (AIIs), 2-(Arylimino)thiazolidines (AITs) and 2-(Arylimino)oxazolidines (AIOs). Among the 10 common-featured models generated by program Catalyst/HipHop, a hypothesis including a ring aromatic (RA), a positive ionizable (PI) and three hydrophobic aliphatic (HpAl) features was considered to be important in evaluating the OA-agonist activity. Active OA agonist 2,6-Et2 AII mapped well onto all the RA, PI and HpAl features of the hypothesis. On the other hand, less active compounds were shown to be difficult to achieve the energetically favorable conformation which is found in the active molecules in order to fit the 3-D common-feature pharmacophore models. Taken together, 2,6-Et2-Ph and foramidine structures are important as OA agonists. The present studies on OA agonists demonstrate that a RA, a PI and three HpAl sites located on the molecule seem to be essential for OA-agonist activity.     

3D-pharmacophore model for RXRγ agonists

Three-dimensional pharmacophore models were generated for retinoid X receptor (RXR_γ) agonists using quantitative approach (CATALYST HypoRefine). One optimal pharmacophore model for selective RXR_γ agonists was determined through careful validation processes. The best quantitative model (Hypo-1) had five features and five excluded volumes: three hydrophobic aliphatic groups (HAL1, HAL2, and HAL3), one hydrophobic aromatic ring (HAR), and one hydrogen bond acceptor (HBA). The model was validated using a wide range of test molecules. It could predict agonist activity and identify highly potent molecules. The present results are valuable to discover and develop specific RXR_γ agonists with desired biological activities.     

Pharmacophore mapping of diverse classes of farnesyltransferase inhibitors

Protein farnesyltransferase (FTase) is a zinc-dependent enzyme that catalyzes the attachment of a farnesyl lipid group to the sulfur atom of a cysteine residue of numerous proteins involved in cell signaling including the oncogenic H-Ras protein. Pharmacophore models were developed by using Catalyst HypoGen program with a training set of 22 farnesyltransferase inhibitors (FTIs), which were carefully selected with great diversity in both molecular structure and bioactivity for discovering new potent FTIs. The best pharmacophore hypothesis (Hypo 1), consisting of four features, namely, one hydrogen-bond acceptor (HBA), one hydrophobic point (HY), and two ring aromatics (RA), has a correlation coefficient of 0.961, a root mean square deviation (RMSD) of 0.885, and a cost difference of 62.436, suggesting that a highly predictive pharmacophore model was successfully obtained. For the test series, a classification scheme was used to distinguish highly active from moderately active and inactive compounds on the basis of activity ranges. Hypo 1 was validated with 181 test set compounds, which has a correlation coefficient of 0.713 between estimated activity and experimentally measured activity. The model was further validated by screening a database spiked with 25 known inhibitors. The model picked up all 25 known inhibitors giving an enrichment factor of 10.892. The results demonstrate that the hypothesis derived in this study can be considered to be a useful and reliable tool in identifying structurally diverse compounds with desired biological activity.     

Chemical function-based pharmacophore generation of selective κ-opioid receptor agonists by catalyst and phase

Two chemical function-based pharmacophore models of selective κ-opioid receptor agonists were generated by using two different programs: Catalyst/HypoGen and Phase. The best output hypothesis (Hypo1) of HypoGen consisted of five features: one hydrogen-bond acceptor (HA), three hydrophobic points (HY), and one positive ionizable function (PI). The highest scoring model (Hypo2) produced by Phase comprised four features: one acceptor (A), one positive ionizable function (P), and two aromatic ring features (R). These two models (Hypo1 and Hypo2) were then validated by test set prediction and enrichment factors. They were shown to be able to identify highly potent κ-agonists within a certain range, and satisfactory enrichments were achieved. The features of these two pharmacophore models were similar and consistent with experiment data. The models produced here were also generally in accord with other reported models. Therefore, our pharmacophore models were considered as valuable tools for 3D virtual screening, and could be useful for designing novel κ-agonists.     

Integrated ligand and structure based studies of flavonoids as fatty acid biosynthesis inhibitors of Plasmodium falciparum

A common feature pharmacophore with two hydrogen-bond acceptor and one aromatic hydrophobic feature has been generated using seven active flavonoids. Docking studies of these compounds well corroborates with the pharmacophore model. Therefore models could be useful for identification of potential novel FAS-II inhibitors.     

Structure-based and shape-complemented pharmacophore modeling for the discovery of novel checkpoint kinase 1 inhibitors

Checkpoint kinase 1 (Chk1), a member of the serine/threonine kinase family, is an attractive therapeutic target for anticancer combination therapy. A structure-based modeling approach complemented with shape components was pursued to develop a reliable pharmacophore model for ATP-competitive Chk1 inhibitors. Common chemical features of the pharmacophore model were derived by clustering multiple structure-based pharmacophore features from different Chk1-ligand complexes in comparable binding modes. The final model consisted of one hydrogen bond acceptor (HBA), one hydrogen bond donor (HBD), two hydrophobic (HY) features, several excluded volumes and shape constraints. In the validation study, this feature-shape query yielded an enrichment factor of 9.196 and performed fairly well at distinguishing active from inactive compounds, suggesting that the pharmacophore model can serve as a reliable tool for virtual screening to facilitate the discovery of novel Chk1 inhibitors. Besides, these pharmacophore features were assumed to be essential for Chk1 inhibitors, which might be useful for the identification of potential Chk1 inhibitors.     

Pharmacophore identification of Raf-1 kinase inhibitors

A three-dimensional pharmacophore model was developed based on 25 currently available Raf-1 kinase inhibitors. The best pharmacophore hypothesis (Hypo1), consisting of four chemical features (one hydrogen-bond acceptor, one hydrogen-bond donor, and two hydrophobic groups), has a correlation coefficient of 0.972. The results of our study provide a valuable tool in designing new leads with desired biological activity by virtual screening.     

Toll-Like Receptor 7 Agonists: Chemical Feature Based Pharmacophore Identification and Molecular Docking Studies

Chemical feature based pharmacophore models were generated for Toll-like receptors 7 (TLR7) agonists using HypoGen algorithm, which is implemented in the Discovery Studio software. Several methods tools used in validation of pharmacophore model were presented. The first hypothesis Hypo1 was considered to be the best pharmacophore model, which consists of four features: one hydrogen bond acceptor, one hydrogen bond donor, and two hydrophobic features. In addition, homology modeling and molecular docking studies were employed to probe the intermolecular interactions between TLR7 and its agonists. The results further confirmed the reliability of the pharmacophore model. The obtained pharmacophore model (Hypo1) was then employed as a query to screen the Traditional Chinese Medicine Database (TCMD) for other potential lead compounds. One hit was identified as a potent TLR7 agonist, which has antiviral activity against hepatitis virus in vitro. Therefore, our current work provides confidence for the utility of the selected chemical feature based pharmacophore model to design novel TLR7 agonists with desired biological activity.     

Pharmacophore models generation by catalyst and phase consensus-based virtual screening protocol against PI3Kα inhibitors

Phosphoinositide 3-kinases (PI3Ks) family has emerged as promising targets for novel therapeutic agents against neoplastic diseases. Pharmacophore and 3D-quantitative structure–activity relationship modelling were applied to study the structure–activity relationship of PI3K inhibitors. The best HypoGen pharmacophore hypothesis Hypo1 with a correlation coefficient of 0.961 consists of one hydrogen-bond acceptor, one hydrogen-bond donor and two hydrophobic features, whereas the best phase hypothesis AADRRR.378 with favourable statistics (q² = 0.7368, r² = 0.9863) has two hydrogen-bond acceptors, one hydrogen-bond donor and three ring aromatic features. Multiple methods, such as Fischer validation, molecular docking and mapping of test set molecules, were carried out to validate these pharmacophore models. Furthermore, a comparative molecular similarity indices analysis candidate hypothesis model was generated as a supplement of pharmacophore hypothesis. Detailed protein–ligand binding information obtained by Glide was utilised in compound optimisation and virtual screening. A molecular database of 133 known inhibitors and 6179 decoys was built for a screening test to quantitatively analyse various hypotheses and scoring parameters. Finally, we designed a workflow integrating HypoGen pharmacophore searching, phase pharmacophore searching and molecular docking for screening the database. With an improved criterion of enrichment factor (EF = 17.43) and ROC curve (AUC = 0.946), this workflow would provide us an original method for novel PI3K inhibitors.     

Three-dimensional Pharmacophore Hypotheses for the Locust Neuronal Octopamine Receptor (OAR3): 1. Antagonists

Three-dimensional pharmacophore hypotheses were built from a set of 17 mianserin-like antagonists against octopamine receptor class 3 (OAR3) in locust nervous tissue. Among the ten chemical-featured models generated by program Catalyst/Hypo, three hypotheses were considered to be important and predictive in evaluating OAR3 antagonists. Predictions were fairly precise for all molecules but the three outliners including eresepine, metoclopramide and yohimbine. While the ideal and null hypotheses had a cost of 66.50 and 124.97, respectively, the ten resulting hypotheses possessed costs from 78.96 to 92.04. The best hypothesis that was confirmed to have a 95% chance of true correlation yielded a low RMS of 1.05 and high regression r of 0.934. Active antagonists mapped well onto all the features of the hypothesis such as hydrophobic, aromatic ring or positive ionizable features. On the other hand, inactive compounds lack of binding affinity were shown to be poorly capable of achieving an energetically favorable conformation shared by the active molecules in order to fit the 3D chemical feature pharmacophore models. In addition, from the comparison and conformation analysis it was proposed that positive ionizable feature contained a lower weight than hydrophobic or an aromatic ring one. Further research on the comparison of models from agonists and antagonists may help elucidate the mechanisms of OAR3 and other types of octopamine receptor-ligand interactions.     

Pharmacophore identification of KSP inhibitors

A three-dimensional pharmacophore model was developed based on 25 currently available KSP (kinesin spindle protein) inhibitors in Catalyst software package. The best pharmacophore hypothesis (Hypo1), consisting of four chemical features (one hydrogen-bond acceptor, one hydrogen-bond donor, one aromatic ring, and one hydrophobic group), has a correlation coefficient of 0.965. The results of our study provide a valuable tool in designing new leads with desired biological activity by virtual screening.     

The pheromone production of female Plodia interpunctella is inhibited by tyraminergic antagonists

Several compounds were found to suppress the calling behavior and in vitro pheromone biosynthesis of the Indian meal moth, Plodia interpunctella. The compounds were screened by means of a calling-behavior bioassay with female P. interpunctella. Five derivatives with activities in the nanomolar range were identified, in order of decreasing pheromonostatic activity: 4-hydroxybenzaldehyde semicarbazone (42) > 5-(4-methoxyphenyl)-1,3-oxazole (38) > 5-[4-(tert-butyl)phenyl]-1,3-oxazole (40) > 5-(3-methoxyphenyl)-1,3-oxazole (35) > 5-(4-cyanophenyl)-1,3-oxazole (36). These compounds also showed in vitro inhibitory activity in intracellular de novo pheromone biosynthesis, as determined with isolated pheromone-gland preparations that incorporated [1-(14)C]sodium acetate in the presence of the so-called pheromone-biosynthesis-activating neuropeptide (PBAN). The non-additive effect of the inhibitor with antagonist (yohimbine) for the tyramine (TA) receptor suggests that it could be a tyraminergic antagonist. Three-dimensional (3D) computer models were built from a set of compounds. Among the common-featured models generated by the program Catalyst/HipHop, aromatic-ring (AR) and H-bond-acceptor-lipophilic (HBAl) features were considered to be essential for inhibitory activity in the calling behavior and in vitro pheromone biosynthesis. Active compounds, including yohimbine, mapped well onto all the AR and HBAl features of the hypothesis. Less-active compounds were shown to be unable to achieve an energetically favorable conformation, consistent with our 3D common-feature pharmacophore models. The present hypothesis demonstrates that calling behavior and PBAN-stimulated incorporation of radioactivity are inhibited by tyraminergic antagonists.     

Design of antimalarial transmission blocking agents: Pharmacophore mapping of ligands active against stage-V mature gametocytes of Plasmodium falciparum

Abstract

The discovery of transmission-blocking (T-B) agents is crucial for preventing and complete removal of malaria infection. However, most of the existing antimalarials are only active against the asexual stages of Plasmodium parasite, but ineffective against the sexual stage (gametocytes). In this background, we have developed pharmacophore models against the stage-V mature gametocytes of P. falciparum parasites. The pharmacophore model (Hypo-1) showed five pharmacophoric features namely, one hydrogen bond donor (HBD), one hydrophobic aliphatic (HYAl), one ring aromatic (RA), and two hydrophobic aromatic (HYAr) essential for the anti-gametocytic activity. The amino, methyl, fused phenyl ring of the quinazoline heterocycle, two phenyl rings of biphenyl moiety (HBD, HYAl, HYAr1, HYAr2 and RA) are the crucial features responsible for the non-specific anti-gametocytic activity (PfG). Subsequently, the model (Hypo-2) developed against the stage-V female gametocytes (PffG) showed the contribution of three pharmacophoric features namely, two hydrogen bond acceptor (HYA) and one RA required for the anti-gametocytic activity. The sulfhydryl, imine and pyridyl groups are observed to be essential for anti-gametocytic activity against female gametocytes. Both the models (PfG and PfGG) showed the classification accuracies of 78.26 and 71.64% for training set compounds and 60.80 and 60.18% for the test set compounds, respectively, for classification of compounds into higher and lower active classes. Also, both the models were found to retain the higher active compounds (IC₅₀ <100?nM) in top 1% of total compounds (actives and decoys) as observed after screening the decoy set compounds.

Communicated by Ramaswamy H Sarma     

Identification of novel, less toxic PTP-LAR inhibitors using in silico strategies: pharmacophore modeling, SADMET-based virtual screening and docking

Human leukocyte antigen-related (PTP-LAR) is a receptor-like transmembrane phosphatase and a potential target for diabetes, obesity and cancer. In the present study, a sequence of in silico strategies (pharmacophore mapping, a 3D database searching, SADMET screening, and docking and toxicity studies) was performed to identify eight novel nontoxic PTP-LAR inhibitors. Twenty different pharmacophore hypotheses were generated using two methods; the best (hypothesis 2) consisted of three hydrogen-bond acceptor (A), one ring aromatic (R), and one hydrophobic aliphatic (Z) features. This hypothesis was used to screen molecules from several databases, such as Specs, IBS, MiniMaybridge, NCI, and an in-house PTP inhibitor database. In order to overcome the general bioavailability problem associated with phosphatases, the hits obtained were filtered by Lipinski’s rule of five and SADMET properties and validated by molecular docking studies using the available crystal structure 1LAR. These docking studies suggested the ligand binding pattern and interactions required for LAR inhibition. The docking analysis also revealed that sulfonylurea derivatives with an isoquinoline or naphthalene scaffold represent potential LAR drugs. The screening protocol was further validated using ligand pharmacophore mapping studies, which showed that the abovementioned interactions are indeed crucial and that the screened molecules can be presumed to possess potent inhibitory activities.     

Molecular modelling study on human histamine H1 receptor and its applications in virtual lead identification for designing novel inverse agonists

Human histamine H1 receptor (HHR1) is one of the G protein-coupled receptors (GPCRs) known for their constitutive activation in the absence of agonist binding. Inverse agonists are the compounds that inhibit this constitutive activity of GPCRs. HHR1 is involved in allergic reactions and is also known to be constitutively active. An updated quantitative pharmacophore model, Hypo1, has been developed using a diverse set of known HHR1 inverse agonists employing the HypoGen algorithm as implemented in Accelrys Discovery Studio 2.1. Hypo1 comprised four pharmacophore features (each one of hydrogen bond acceptor, hydrophobic, ring aromatic and positive ionisable group) along with a high correlation value of 0.944. This pharmacophore model was validated using an external test set containing 25 diverse inverse agonists and CatScramble method. Three chemical databases were screened for novel chemical scaffolds using Hypo1 as a query, to be utilised in drug design. The 3D structure of HHR1 has been constructed using human β2 adrenergic receptor. Molecular docking studies were performed with the database hit compounds using GOLD 4.1 program. The combination of all results led us to identify novel compounds to be deployed in designing new generation HHR1 inverse agonists.     

Discovery of potential pancreatic cholesterol esterase inhibitors using pharmacophore modelling, virtual screening, and optimization studies

Pancreatic cholesterol esterase (CEase) is a serine hydrolase involved in the hydrolysis of variety of lipids and transport of free cholesterol. In this study, pharmacophore hypotheses based on known inhibitors were generated using common feature pharmacophore generation protocol available in Discovery Studio program. The best pharmacophore model containing two hydrogen bond acceptor and three hydrophobic features was selected and validated. It was further used in screening three diverse chemical databases. Hit compounds were subjected to drug-likeness and molecular docking studies. Four hits, namely SEW00846, NCI0040784, GK03167, and CD10645, were selected based on the GOLD fitness score and interaction with active site amino acids. All hit compounds were further optimized to improve their binding in the active site. The optimized compounds were found to have improved binding at the active site. Strongly binding optimized hits at the active site can act as virtual leads in potent CEase inhibitor designing.     

Pharmacoinformatics analysis to identify inhibitors of Mtb-ASADH

Aspartate-semialdehyde dehydrogenase (ASADH; EC 1.2.1.11) is a key enzyme in the biosynthesis of essential amino acids in prokaryotes and fungi, inhibition of ASADH leads to the development of novel antitubercular agents. In the present work, a combined structure and ligand-based pharmacophore modeling, molecular docking, and molecular dynamics (MD) approaches were employed to identify potent inhibitors of mycobacterium tuberculosis (Mtb)-ASADH. The structure-based pharmacophore hypothesis consists of three hydrogen bond acceptor (HBA), two negatively ionizable, and one positively ionizable center, while ligand-based pharmacophore consists of additional one HBA and one hydrogen bond donor features. The validated pharmacophore models were used to screen the chemical databases (ZINC and NCI). The screened hits were subjected to ADME and toxicity filters, and subsequently to the molecular docking analysis. Best-docked 25 compounds carry the characteristics of highly electronegative functional groups (–COOH and –NO₂) on both sides and exhibited the H-bonding interactions with highly conserved residues Arg99, Arg249, and His256. For further validation of docking results, MD simulation studies were carried out on two representative compounds NSC51108 and ZINC04203124. Both the compounds remain bound to the key active residues of Mtb-ASADH during the MD simulations. These identified hits can be further used for lead optimization and in the design more potent inhibitors against Mtb-ASADH.     

Synthesis and biological evaluation of phenanthrenes as cytotoxic agents with pharmacophore modeling and ChemGPS-NP prediction as topo II inhibitors

In a structure-activity relationship (SAR) study, 3-methoxy-1,4-phenanthrenequinones, calanquinone A (6a), denbinobin (6b), 5-OAc-calanquinone A (7a) and 5-OAc-denbinobin (7b), have significantly promising cytotoxicity against various human cancer cell lines (IC(50) 0.08-1.66 μg/mL). Moreover, we also established a superior pharmacophore model for cytotoxicity (r = 0.931) containing three hydrogen bond acceptors (HBA1, HBA2 and HBA3) and one hydrophobic feature (HYD) against MCF-7 breast cancer cell line. The pharmacophore model indicates that HBA3 is an essential feature for the oxygen atom of 5-OH in 6a-b and for the carbonyl group of 5-OCOCH(3) in 7a-b, important for their cytotoxic properties. The SAR for moderately active 5a-b (5-OCH(3)), and highly active 6a-b and 7a-b, are also elaborated in a spatial aspect model. Further rational design and synthesis of new cytotoxic phenanthrene analogs can be implemented via this model. Additionally, employing a ChemGPS-NP based model for cytotoxicity mode of action (MOA) provides support for a preliminary classification of compounds 6a-b as topoisomerase II inhibitors.     

Ligand-based and structure-based approaches in identifying ideal pharmacophore against c-Jun N-terminal kinase-3

Structure and ligand based pharmacophore modeling and docking studies carried out using diversified set of c-Jun N-terminal kinase-3 (JNK3) inhibitors are presented in this paper. Ligand based pharmacophore model (LBPM) was developed for 106 inhibitors of JNK3 using a training set of 21 compounds to reveal structural and chemical features necessary for these molecules to inhibit JNK3. Hypo1 consisted of two hydrogen bond acceptors (HBA), one hydrogen bond donor (HBD), and a hydrophobic (HY) feature with a correlation coefficient (r²) of 0.950. This pharmacophore model was validated using test set containing 85 inhibitors and had a good r² of 0.846. All the molecules were docked using Glide software and interestingly, all the docked conformations showed hydrogen bond interactions with important hinge region amino acids (Gln155 and Met149) and these interactions were compared with Hypo1 features. The results of ligand based pharmacophore model (LBPM) and docking studies are validated each other. The structure based pharmacophore model (SBPM) studies have identified additional features, two hydrogen bond donors and one hydrogen bond acceptor. The combination of these methodologies is useful in designing ideal pharmacophore which provides a powerful tool for the discovery of novel and selective JNK3 inhibitors.